diff --git a/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Data-Melbourne_F_fixed.csv b/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Data-Melbourne_F_fixed.csv
new file mode 100644
index 00000000..2194708b
--- /dev/null
+++ b/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Data-Melbourne_F_fixed.csv	
@@ -0,0 +1,1383 @@
+Serial number,Average Outflow,Average Inflow,Energy Consumption,Ammonia,Biological Oxygen Demand,Chemical Oxygen Demand,Total Nitrogen,Average Temperature,Maximum temperature,Minimum temperature,Atmospheric pressure,Average humidity,Total rainfall,Average visibility,Average wind speed,Maximum wind speed,Year,Month,Day
+0,2.941,2.589,175856,27,365,730,60.378,19.3,25.1,12.6,0,56,1.52,10,26.9,53.5,2014,1,1
+1,2.936,2.961,181624,25,370,740,60.026,17.1,23.6,12.3,0,63,0,10,14.4,27.8,2014,1,2
+2,2.928,3.225,202016,42,418,836,64.522,16.8,27.2,8.8,0,47,0.25,10,31.9,61.1,2014,1,5
+3,2.928,3.354,207547,36,430,850,63,14.6,19.9,11.1,0,49,0,10,27,38.9,2014,1,6
+4,2.917,3.794,202824,46,508,1016,65.59,13.4,19.1,8,0,65,0,10,20.6,35.2,2014,1,7
+5,2.912,3.75,247691,40,410,820,61.786,18.9,27.3,7.7,0,52,0,0,15.6,31.7,2014,1,8
+6,2.355,3.507,224706,51,555,1110,68.82,25.9,32.4,12.1,0,39,0,0,26.7,46.5,2014,1,9
+7,2.366,3.188,212440,41,365,730,62.218,17.7,24.6,13,0,69,0,9.8,13.1,25.9,2014,1,12
+8,3.923,3.378,202676,26,355,710,61.433,26.4,36,12.7,0,44,0,0,19.8,51.9,2014,1,13
+9,3.912,3.425,202411,42,530,830,66.354,35.5,43.5,28.5,0,20,0,0,27.8,57.6,2014,1,14
+10,2.971,3.775,171123,47,435,870,65.531,32.1,42.9,23.7,0,29,0,0,18,35.2,2014,1,15
+11,3.833,3.763,193509,43,295,590,59.548,33.9,43.1,23.7,0,24,0,0,19.3,46.5,2014,1,16
+12,2.984,3.487,205761,38,600,1200,68.82,19.2,23.1,15.2,0,64,0,10,24.8,31.7,2014,1,19
+13,3.236,3.604,184108,38,465,930,64.568,18.4,24.7,15.8,0,66,0,10,25.6,35.2,2014,1,20
+14,2.95,3.6,200044,38,505.5,1011,65.59,17.6,22.6,14,0,61,0,10,25,37,2014,1,21
+15,2.935,3.481,173825,47,470,980,76,16.3,23.4,10,0,59,0,0,17.4,29.4,2014,1,22
+16,2.937,3.623,230632,39,431,862,64.847,23.6,33.7,10.2,0,52,1.52,8.5,14.8,27.8,2014,1,23
+17,3.308,3.785,236472,45,380,760,62.09,16.3,22.8,12.8,0,72,4.32,10,21.9,31.7,2014,1,24
+18,2.933,3.596,214057,36,345,690,63.227,29.3,35.5,16.7,0,26,0,0,32.6,48.2,2014,1,27
+19,2.94,3.642,204062,29,286.5,573,54.63,27.2,42.1,17.6,0,34,0,10,25.7,51.9,2014,1,28
+20,3.427,3.519,245524,31,360,720,61.496,17.7,23.7,13,0,64,0,10,20.2,33.5,2014,1,29
+21,2.98,3.541,230113,38,380,840,65.374,22.6,31.1,12.9,0,55,0,8,13.3,22.2,2014,1,30
+22,2.997,3.526,214635,43,344,688,63.521,31.7,40.5,23,0,23,0,0,15.6,33.5,2014,2,2
+23,2.978,3.542,210017,44,390.5,781,62.569,19.2,0,13.8,0,56,0.51,10,29.6,38.9,2014,2,3
+24,2.983,3.332,201393,35,391.5,783,62.218,17.7,25,10.8,0,54,0,10,25.7,44.6,2014,2,4
+25,2.989,3.249,201578,48,270,740,55,22.5,30.9,10.6,0,42,0,0,20,51.9,2014,2,5
+26,2.991,3.408,190528,46,385,770,63.38,28.7,35.3,14.2,0,27,0,0,29.8,51.9,2014,2,6
+27,2.989,3.498,177913,41,377.5,755,62.371,21.8,0,13,0,36,0,10,25.4,57.6,2014,2,9
+28,2.967,3.488,174894,34,435.5,871,64.366,17.6,23.7,12,0,61,0,9.7,20.6,31.7,2014,2,10
+29,2.965,3.448,196915,36,320,871,64.301,20.1,27.3,11.9,0,68,0,6.4,14.8,20.6,2014,2,11
+30,3.625,3.426,164381,35,420.5,841,64.301,22.1,28.1,14.9,0,69,0,7.7,13.9,24.1,2014,2,12
+31,2.991,3.456,231265,37,416.5,833,64.366,22.6,26.4,17.7,0,62,0,8.2,8.1,16.5,2014,2,13
+32,2.995,3.611,178585,37,357.5,715,61.825,17.1,23,12.7,0,68,0.25,10,19.8,35.2,2014,2,16
+33,3.356,3.601,203040,33,330,828,58,18.1,25.7,11.8,0,60,0,10,12.6,25.9,2014,2,17
+34,2.97,3.703,212571,37,453.5,907,65.42,21.6,31.9,11.5,0,57,0,10,15.4,27.8,2014,2,18
+35,3.812,3.585,211797,37,405.5,811,62.023,15.7,25.7,10,0,65,7.37,9.2,22.8,51.9,2014,2,19
+36,3.092,3.561,217368,30,404.5,809,62.218,14.9,20.2,10,0,55,0,10,27.4,44.6,2014,2,20
+37,3.129,3.519,186966,30,280,949,64.366,17.4,24.6,12.8,0,67,0,10,11.3,22.2,2014,2,23
+38,2.721,3.39,233170,37,421.5,843,64.522,19.2,30,12.5,0,62,0,0,17,42.4,2014,2,24
+39,2.994,3.478,240026,37,472,944,65.878,21.1,36.4,12,0,50,0,10,20.4,38.9,2014,2,25
+40,2.977,3.564,221132,44,489.5,979,65.59,15.5,21.5,10,0,61,0,9.7,20,35.2,2014,2,26
+41,3.146,3.67,189753,41,434.5,869,64.522,15.2,21.3,9.6,0,59,0,10,23.3,35.2,2014,2,27
+42,3.17,3.563,248635,42,351,702,62.16,17,23,12,0,67,0,10,15,27.8,2014,3,2
+43,3.177,3.569,226624,37,320,870,66,19.8,27,11.8,0,65,0,10,16.1,42.4,2014,3,3
+44,3.175,3.441,208340,34,437,874,65.531,26.7,34.1,13.5,0,42,0,10,24.8,38.9,2014,3,4
+45,3.182,3.505,217462,33,400.5,801,61.866,16.1,25.9,13.6,0,63,0,10,21.9,27.8,2014,3,5
+46,3.595,3.521,232162,39,477.5,955,65.59,15.7,21,11.7,0,61,0,10,17.4,25.9,2014,3,6
+47,3.044,3.571,213487,39,434,868,64.301,18.1,22.7,11.6,0,74,0,10,17,31.7,2014,3,7
+48,3.033,3.448,227709,39,410,820,63.578,24.5,35.2,17.7,0,37,0,0,17,38.9,2014,3,10
+49,3.156,3.599,249208,48,360,840,65.531,21.5,32.1,14,0,60,3.3,10,17,35.2,2014,3,11
+50,3.155,3.349,228459,44,465,930,64.411,15.6,21.3,9.7,0,59,0,10,16.3,29.4,2014,3,12
+51,3.145,3.31,230038,41,405,810,62.218,17.2,23.7,9.6,0,66,0,10,13,25.9,2014,3,13
+52,3.158,3.499,199081,42,355,710,62.371,15.7,20,10.8,0,52,1.02,10,21,42.4,2014,3,16
+53,3.151,3.476,201565,36,375,750,61.825,18.3,25.3,11.6,0,65,0,10,18.5,35.2,2014,3,17
+54,3.157,3.402,239774,31,425,850,64.366,16.7,25.1,9.6,0,62,0,10,14.1,25.9,2014,3,18
+55,3.158,3.36,222446,35,530,930,65,15.6,23,9.2,0,66,0,10,15.4,29.4,2014,3,19
+56,3.021,3.4,219441,35,457.5,915,65.577,23.1,31.1,9.2,0,28,0,0,22.6,37,2014,3,20
+57,2.482,3.451,230837,40,485,970,65.59,13.2,16.8,9,0,66,0,9.8,13.5,27.8,2014,3,23
+58,3.063,3.426,236305,32,422.5,845,64.301,14.7,18.3,8.9,0,76,1.02,10,15,25.9,2014,3,24
+59,3.077,3.427,233045,30,462.5,925,64.411,18.3,24.3,11.9,0,66,0,10,11.7,22.2,2014,3,25
+60,2.735,3.444,244547,46,422.5,845,64.301,20.3,27.3,12.5,0,70,5.59,8.9,11.9,27.8,2014,3,26
+61,2.972,3.431,233574,34,450,855,64.411,19.6,25.9,15.9,0,84,7.87,8.9,12.6,29.4,2014,3,27
+62,2.997,3.516,246220,41,415,830,64.412,20.2,26.6,14,0,69,0,10,15.2,38.9,2014,3,30
+63,3.003,3.568,267399,35,420,840,65.486,25.2,32,15.4,0,43,0,0,23.5,42.4,2014,3,31
+64,3.004,3.652,289188,41,472.5,945,66.354,26.9,33.7,5.5,0,38,0,0,34.6,46.5,2014,4,1
+65,2.936,3.444,241800,37,380,920,64,16.9,26,13,0,80,0,9.3,16.7,37,2014,4,2
+66,2.97,3.416,257357,37,457.5,915,64.366,15.1,17.3,13.3,0,70,0.25,10,22.2,31.7,2014,4,3
+67,2.97,3.191,254817,40,405,810,62.374,16.4,23.2,11,0,77,0,10,13.1,35.2,2014,4,6
+68,2.993,3.592,265212,36,390,780,62.218,19.9,25.2,10.8,0,53,0,0,21.7,38.9,2014,4,7
+69,3.008,3.432,264549,37,220,835,64.412,17.3,21,15.6,0,86,16.26,8.7,14.8,42.4,2014,4,8
+70,2.905,3.38,310372,32,365,730,61.24,16.4,17.5,16,0,97,18.03,6.3,10.9,18.3,2014,4,9
+71,3.009,3.468,330334,24,323,646,59.603,17.1,18.2,16,0,96,10.41,51.1,14.6,33.5,2014,4,10
+72,3,3.432,288220,34,335,670,61.866,14.1,20.4,8,0,76,0,10,14.6,27.8,2014,4,13
+73,4.799,5.071,300570,44,340,744,56,14.3,20.3,8.1,0,69,0,10,16.9,27.8,2014,4,14
+74,3.041,3.621,272809,42,357.5,715,62.218,14,19.5,8,0,77,0.25,9.8,14.8,25.9,2014,4,15
+75,3.615,3.494,295544,28,345,690,59.446,14.9,22.6,8.9,0,73,0,0,11.5,20.6,2014,4,16
+76,3.042,3.495,214921,34,371,742,62.023,12.4,18.9,9,0,72,1.52,10,18.9,35.2,2014,4,18
+77,3.618,3.483,244534,33,310,740,62.218,15.9,19,10.9,0,48,1.52,0,44.4,59.4,2014,4,21
+78,3.012,3.492,241273,31,340,680,62.023,13.3,17.3,9.5,0,87,3.05,9.7,11.7,37,2014,4,22
+79,3.004,3.417,226195,35,365,730,62.061,14.9,18.8,8.7,0,56,0.51,9.8,15,29.4,2014,4,23
+80,3.016,3.575,197036,38,370,740,61.186,15.7,20.1,3.5,0,47,0,0,25.9,37,2014,4,25
+81,2.996,3.411,200407,42,340,690,60,10.8,16.1,4.8,0,61,0,10,17.6,35.2,2014,4,27
+82,3.27,3.401,221851,36,415,830,63.689,18.8,21,4.2,0,60,0,10,43,57.6,2014,4,28
+83,2.977,3.376,254684,42,407,814,62.246,12.8,20,8.6,0,87,7.87,9.5,17.2,37,2014,4,29
+84,3.109,3.39,210285,27,302.5,605,53.59,9.5,16,4.7,0,72,0,10.9,18.5,40.7,2014,4,30
+85,3.109,3.367,271464,29,400,800,61.384,11.8,16,4.5,0,57,0,10,20.6,37,2014,5,1
+86,3.118,3.322,201502,32,357,714,61.825,10.4,14,7,0,79,1.02,9.8,20.4,35.2,2014,5,4
+87,3.117,3.537,260493,43,260,720,62.16,12.1,16.3,8.3,0,75,0.25,10,15.6,25.9,2014,5,5
+88,3.123,3.478,284909,37,380,760,61.339,10.8,14,8.7,0,78,0.51,10,15.6,24.1,2014,5,6
+89,3.138,3.339,305726,41,385,770,60.757,8.1,14.5,3,0,73,0.25,10,14.1,25.9,2014,5,7
+90,3.217,3.37,285409,46,370,740,61.051,11,17.5,2.3,0,58,0,0,14.3,31.7,2014,5,8
+91,3.124,3.393,242891,43,380,760,62.218,12.2,19,7,0,80,0.51,10,12.4,18.3,2014,5,11
+92,3.109,3.435,244843,32,435,870,63.467,12.1,18.5,6,0,76,0,10,10.7,22.2,2014,5,12
+93,3.909,4.357,261172,36,210,760,57,13.5,20.4,5.2,0,72,0,10,14.6,25.9,2014,5,13
+94,3.162,3.565,269218,40,392.5,785,61.748,16.3,21,7.4,0,62,0,10,30.9,46.5,2014,5,14
+95,3.156,3.48,300138,34,450,900,63.995,17.2,21.6,13.1,0,56,0,0,36.5,46.5,2014,5,15
+96,3.16,3.926,294444,31,367.5,735,61.396,17.1,21.2,15,0,61,0,0,32.6,40.7,2014,5,18
+97,2.971,3.575,299317,34,395,790,61.396,17.2,23,12,0,66,0,0,29.1,42.4,2014,5,19
+98,2.969,3.621,295754,35,440,880,63.728,14.5,22.1,9,0,76,0,10,15.6,31.7,2014,5,20
+99,3.512,3.475,288762,30,390,816,62.023,17.9,23.4,8.6,0,65,0,10,27.4,44.6,2014,5,21
+100,2.806,3.325,304978,33,408,816,61.496,17.8,21,14.6,0,65,3.3,9.8,22.2,40.7,2014,5,22
+101,2.771,3.098,277934,42,355,710,61.719,15.1,19.5,8.8,0,83,0,10,22.4,44.6,2014,5,25
+102,2.733,3.049,271449,30,400,800,61.496,17.9,19.4,8.6,0,68,0,10,30.7,46.5,2014,5,26
+103,2.996,3.363,269010,26,420,840,64.256,14.8,20,10.5,0,72,0.51,10,20.4,27.8,2014,5,27
+104,3.003,3.424,255480,37,392.5,785,61.866,12.2,18.3,7,0,79,0.25,10,15.6,27.8,2014,5,28
+105,3.02,3.371,259464,38,430,815,61,9.9,15,4.6,0,78,0,10,8.1,16.5,2014,5,29
+106,2.996,3.427,244163,31,355,710,61.866,12,14.3,8.7,0,94,5.33,82,5.9,16.5,2014,6,1
+107,3.012,3.431,263614,36,392.5,785,61.339,13.1,15,8.1,0,91,2.29,7.9,13.1,25.9,2014,6,2
+108,3.015,3.502,261779,31,387.5,775,62.061,12.8,16.3,8,0,52,0,0,11,21.8,2014,6,3
+109,3,3.52,194840,38,370,667,61.863,12.9,18,8.2,0,54,3.3,51.3,12,25.9,2014,6,4
+110,3.025,3.569,284030,49,383,766,61.786,9.9,14.9,7,0,56,0,0,7.4,18.3,2014,6,5
+111,3.028,2.807,299010,41,370,740,60.952,11.4,15,5.9,0,56,0.25,0,9.8,20.6,2014,6,6
+112,3.03,4.139,244693,34,350,700,61.228,10.2,14.2,3,0,54,0,51.5,10.9,22.2,2014,6,9
+113,3.186,3.472,239908,42,540,785,60,11.1,18.1,6.3,0,74,0,0,17.8,25.9,2014,6,10
+114,3.001,3.386,269410,43,450,900,63.052,12.4,16.2,6.4,0,74,0,0,25.2,42.4,2014,6,11
+115,3.558,3.726,280648,39,435,870,63.775,12.7,15,9.5,0,75,3.3,10.3,24.1,42.4,2014,6,12
+116,2.975,3.593,250741,35,330,660,61.866,10.9,14.3,7.6,0,79,0.51,0,18,21.8,2014,6,15
+117,3.751,4.333,256136,42,250,711,62.355,11.2,16,8.3,0,52,1.52,51.8,19.4,29.4,2014,6,16
+118,4.515,4.521,260096,34,382,764,61.866,11.6,15.1,8.7,0,76,0,0,11.3,20.6,2014,6,17
+119,3.341,3.605,273464,33,346.5,693,60.662,9.8,13.1,6,0,71,0,10.6,12.6,38.9,2014,6,18
+120,3.014,3.543,270896,35,368.5,737,61.384,10.1,11,5.4,0,52,0,0,31.1,44.6,2014,6,19
+121,3.219,3.42,262206,38,330,750,58,12.4,14.5,7.7,0,75,0,0,35.9,68.3,2014,6,22
+122,3.167,3.689,299892,32,310,620,58.036,8.7,14.6,4.9,0,72,2.79,51.8,26.3,53.5,2014,6,23
+123,3.011,3.553,297802,24,308,616,56.8,10.6,13.6,4.1,0,70,0,0,32.8,74.1,2014,6,24
+124,3.122,3.386,303524,42,568.5,1137,68.183,12.7,15.3,7.7,0,66,0.25,0,29.1,44.6,2014,6,25
+125,2.96,3.306,316848,43,360,720,60.786,11.8,15,6.7,0,66,0,0,27.4,51.9,2014,6,26
+126,3.012,3.586,274982,39,367.5,735,60.981,7.5,11.7,5,0,52,5.59,512,22.8,35.2,2014,6,29
+127,3.228,3.386,281415,33,360,774,60.758,9.7,12.3,4.8,0,50,0.51,51.8,19.8,33.5,2014,6,30
+128,3.018,3.319,291995,44,347.5,695,61.533,11.1,12,7.4,0,75,0,10,16.9,25.9,2014,7,1
+129,3.413,3.606,260039,40,367.5,735,61.541,10.6,15.8,5.5,0,68,0,10,20.4,42.4,2014,7,2
+130,3.015,3.529,274374,39,380.5,761,61.541,8.7,12,5.4,0,82,0,10,35.9,53.5,2014,7,3
+131,3.014,3.424,277587,35,290,580,55.946,9.2,13.2,3.9,0,86,0.25,10.9,16.7,31.7,2014,7,6
+132,3.029,3.283,275868,36,367,734,60.662,10.4,15.3,3.1,0,74,0,10,33,50,2014,7,7
+133,2.715,3.306,279933,33,410,737,50,10.9,13.6,7.9,0,67,0,10,43.5,68.3,2014,7,8
+134,3.275,3.309,311573,37,255,510,57.99,7.7,12.2,4.8,0,84,8.13,9.5,18.3,40.7,2014,7,9
+135,3.011,3.331,305095,49,250,500,58.526,8.9,13.5,4.2,0,80,0,10,26.1,38.9,2014,7,10
+136,3.01,3.525,286865,39,277,554,58.616,11.1,13,3.2,0,67,0,10,17.2,22.2,2014,7,13
+137,3.016,3.389,312907,40,307.5,615,58.617,9.2,12.4,6.6,0,72,0,10,16.5,37,2014,7,14
+138,3.333,3.403,307497,39,300,600,58.616,10,11.6,6.8,0,78,0.51,10,22.6,38.9,2014,7,15
+139,3.021,3.377,256799,31,250,586,54.63,10.4,13.8,7,0,73,0,10,27,38.9,2014,7,16
+140,3.012,3.403,219150,38,337.5,675,60.991,7.2,11.8,4.5,0,70,3.81,10,27.2,57.6,2014,7,17
+141,3.015,3.343,273029,37,372.5,745,61.033,7.6,12.8,4,0,87,0,10,8.3,18.3,2014,7,20
+142,3.009,3.345,342539,31,382.5,765,60.406,7.3,13.4,3,0,86,0.25,6.9,8.9,14.8,2014,7,21
+143,3.278,3.571,354523,40,370,740,60.629,5,10.1,0,0,97,0,4.7,7.8,14.8,2014,7,22
+144,3.013,3.46,352130,40,420,840,62.257,8.6,12.4,-0.4,0,78,0,0,16.5,29.4,2014,7,23
+145,2.988,3.535,339981,39,430,920,46,11.3,14,4.3,0,76,0,10,24.4,35.2,2014,7,24
+146,3.003,3.438,366871,35,306.5,613,56.089,11.3,16.4,5.4,0,71,0,10,29.4,50,2014,7,27
+147,3.17,3.44,315535,33,325,650,61.396,12.2,16.2,7.5,0,67,0.25,10,32.8,46.5,2014,7,28
+148,3.326,3.484,292272,31,341.5,683,61.396,13.8,16,9.1,0,71,0,10,29.1,48.2,2014,7,29
+149,3.03,3.431,300308,36,350,779,61.396,14.8,18,10.2,0,63,0,10,30.6,55.4,2014,7,30
+150,3.264,3.492,315762,29,373,746,60.563,9.1,18.6,4,0,62,6.1,9.2,33.3,53.5,2014,7,31
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+152,1.606,3.28,322902,36,369,738,60.601,8.8,14.1,1.4,0,55,0,9.7,16.1,25.9,2014,8,4
+153,3.354,3.175,323313,37,340,706,57,12.3,15.8,4.5,0,62,0,10,13.5,24.1,2014,8,5
+154,3.097,3.613,319754,39,344.5,689,61.533,10.2,15.3,7.6,0,78,0.51,9.7,14.3,22.2,2014,8,6
+155,3.049,3.486,325743,34,352.5,705,61.24,10.8,12.8,10,0,83,0.51,1.5,13,22.2,2014,8,7
+156,3.048,3.347,285829,33,368.5,737,60.662,10.2,15.3,6.7,0,62,0,10,21.5,40.7,2014,8,8
+157,3.219,3.416,306656,37,336.5,673,60.563,6.4,12.3,3.8,0,79,5.33,10,18.9,40.7,2014,8,10
+158,3.025,3.326,326631,30,310,631,59.849,6.6,11.1,3.1,0,79,0,10,11.9,27.8,2014,8,11
+159,3.371,4.007,362228,27,390,780,58.612,8.2,11.5,3.3,0,85,0,10,10.7,22.2,2014,8,12
+160,3.737,4.389,346222,25,309,618,56.764,10,13.5,6.4,0,80,0.51,9.8,10.2,24.1,2014,8,13
+161,4.558,4.834,219950,25,311,622,56.892,7.3,14.5,2.5,0,78,0,10,10.6,18.3,2014,8,14
+162,3.576,4.076,330714,32,240,734,55,10.9,14,7.3,0,75,0,10,22.6,33.5,2014,8,17
+163,3.399,3.648,349739,36,424,848,63.091,10.3,12.7,8.2,0,88,3.81,9.7,18,27.8,2014,8,18
+164,3.352,3.577,323562,24,355,710,59.446,9.9,12,8,0,70,0,10,14.8,24.1,2014,8,19
+165,3.32,3.687,318822,25,478.5,957,63.643,9.5,12.4,5.8,0,75,0,10,11.1,18.3,2014,8,20
+166,3.025,3.53,341913,22,385,770,58.612,10.8,17,5.5,0,73,0,10,17.6,27.8,2014,8,21
+167,3.052,3.261,341476,30,320,640,60.682,11.7,15.5,7.7,0,70,0.51,10,16.5,25.9,2014,8,24
+168,3.048,3.574,333601,25,280,661,59.446,10.6,15.1,7.8,0,91,2.79,6.9,12.6,24.1,2014,8,25
+169,3.041,3.455,305988,35,342.5,685,60.406,10.9,17.7,5,0,80,0.25,10,10.4,22.2,2014,8,26
+170,3.207,3.443,304984,31,509.5,1019,63.643,10.1,19,2.7,0,76,0,8,8,18.3,2014,8,27
+171,3.21,3.552,253707,38,400,800,61.033,11.3,20.3,2.3,0,70,0,5.5,7.2,18.3,2014,8,28
+172,3.061,3.472,316189,33,335,670,61.591,16.2,21,9.9,0,49,0,0,37,51.9,2014,8,31
+173,3.068,3.357,296212,22,387.5,775,59.446,9.7,15.9,7,0,84,8.89,9.7,16.5,27.8,2014,9,1
+174,3.204,3.422,298283,42,400,680,56,8.6,13.8,4.9,0,76,1.52,10,20.9,38.9,2014,9,2
+175,3.09,3.419,293375,36,343.5,687,60.505,7.7,13.1,2,0,74,0,10,11.7,22.2,2014,9,3
+176,3.05,3.528,281730,36,412.5,825,61.033,9.1,14.6,1.7,0,78,0,10,11.7,22.2,2014,9,4
+177,3.319,3.396,294510,35,345,690,60.857,13.6,19.8,4.7,0,56,0,10,22.6,50,2014,9,7
+178,3.16,3.551,235658,42,452.5,905,63.931,17.2,21.2,8.2,0,50,0,10,46.9,64.8,2014,9,8
+179,3.152,3.496,281629,35,625,1250,68.183,12.9,19.6,8,0,79,12.95,9.7,22.4,59.4,2014,9,9
+180,3.149,3.664,240832,32,380,955,63.885,14.4,18,7.4,0,57,3.81,9.3,24.3,33.5,2014,9,10
+181,3.251,3.537,282142,37,475,950,63.643,9.3,15.4,4,0,68,0,10,19.8,38.9,2014,9,11
+182,3.256,3.828,264255,27,330,660,58.711,8.3,14.1,2.9,0,74,0,10,9.1,16.5,2014,9,14
+183,3.604,4.176,287358,34,425,850,62.257,13.3,18.1,6.4,0,79,0,9.2,14.1,24.1,2014,9,15
+184,3.908,4.724,295183,30,410,820,61.24,10.4,14,6.9,0,82,2.03,9.2,17,31.7,2014,9,16
+185,4.202,4.355,322165,37,360,940,62.479,16.5,26,6.6,0,62,1.52,10,28.9,57.6,2014,10,6
+186,3.768,4.26,331715,33,382.5,765,60.563,11.3,16.9,6.7,0,64,0.25,10,20,38.9,2014,10,7
+187,3.459,3.998,310535,38,386.5,773,60.406,12.8,19.8,6.5,0,70,0.25,10,13.5,24.1,2014,10,8
+188,3.897,3.674,299576,31,387.5,775,61.591,17.3,23.5,7.4,0,48,0,0,21.1,44.6,2014,10,9
+189,3.003,3.686,257216,39,370,681,61,16.5,31.3,6.9,0,55,2.03,10.3,21.3,35.2,2014,10,12
+190,3.179,3.769,266428,39,375,750,61.748,10.2,15.6,7.6,0,67,7.11,10,28,44.6,2014,10,13
+191,3.271,3.605,263099,34,325,650,60.662,9.6,15.6,4.6,0,61,0,10,22,42.4,2014,10,14
+192,3.322,3.992,252674,25,350,700,59.239,11.4,15.7,4.3,0,64,0,10,15.4,27.8,2014,10,15
+193,3.331,3.759,237415,25,348.5,697,60.073,11.3,15.9,7,0,71,1.27,9.8,15.7,27.8,2014,10,16
+194,3.591,4.062,244135,42,355,710,62.569,15.8,28.2,9,0,55,0,10,28.9,48.2,2014,10,19
+195,3.728,3.533,242707,41,280,995,63.052,12.7,21,5.5,0,59,0,0,19.1,33.5,2014,10,20
+196,3.093,4.072,259769,51,414.5,829,63.006,21,27.6,5,0,48,0,0,27.6,57.6,2014,10,21
+197,3.531,3.915,245832,52,422.5,845,64.849,20.8,31.3,13.7,0,56,0,8.2,22.8,46.5,2014,10,22
+198,3.483,3.595,248445,48,370,740,62.246,16.1,26,13,0,81,0,9,13.1,33.5,2014,10,23
+199,3.357,3.661,283443,29,407.5,815,61.69,19.2,25.2,11.5,0,52,16.51,9.5,21.5,42.4,2014,10,26
+200,3.33,3.583,305252,24,310,620,57.281,13.1,25.2,8,0,55,0.76,10,26.1,50,2014,10,27
+201,3.267,3.59,287551,34,360,735,64,13.6,20,8,0,62,0.51,10.9,21.1,38.9,2014,10,28
+202,3.039,3.516,169942,40,421,842,63.729,15.6,23,7.7,0,64,0,10,10.7,27.8,2014,10,29
+203,3.939,4.498,263759,41,412.5,825,61.891,14.7,24,8,0,65,0,10,14.4,29.4,2014,10,30
+204,4.378,4.414,272029,38,327.5,655,61.033,11.2,17,6.7,0,65,0,10,15.7,31.7,2014,11,2
+205,3.455,3.638,272830,26,305,610,53.636,18.4,29.3,10.4,0,37,0,10,28.9,42.4,2014,11,4
+206,3.398,3.709,245850,32,260,655,61.339,12.3,18.2,7,0,60,0,10,19.1,31.7,2014,11,5
+207,3.057,3.809,283417,48,370,740,62.412,16.1,27,7.3,0,50,0,10,14.8,31.7,2014,11,6
+208,3.43,3.639,221996,39,370,740,62.218,13.9,19.9,8,0,61,0,10,18.9,29.4,2014,11,9
+209,3.313,3.472,257268,28,350,700,60.424,14.3,20.5,8.3,0,57,0,10,23,35.2,2014,11,10
+210,3.115,3.475,277460,28,365,730,58.612,12,18.3,5.9,0,63,0,10,15.4,27.8,2014,11,11
+211,3.752,4.458,241697,26,455,910,62.941,16.9,27.4,5,0,53,0,0,12.2,27.8,2014,11,12
+212,3.746,3.868,250057,40,350,715,54,27.2,33.4,18.9,0,20,0,0,20.2,37,2014,11,13
+213,3.438,3.814,265479,21,216,432,53.053,14.5,20.2,10.1,0,62,0.51,10,20.9,35.2,2014,11,16
+214,3.4,3.75,224226,37,335,670,62.023,14.1,21.2,8,0,59,0.25,10,18.3,37,2014,11,17
+215,2.529,3.749,250850,41,412.5,825,62.218,15.1,20.2,7.3,0,63,0,10,14.3,25.9,2014,11,18
+216,3.542,3.938,249239,48,430,840,63.885,23.5,29,9.6,0,26,0,0,26.3,59.4,2014,11,19
+217,3.827,4.17,266688,44,350,700,63.521,20.9,31.2,15,0,55,0,10,23.3,44.6,2014,11,20
+218,3.62,3.992,116638,34,267.5,535,55.506,18.2,25.7,12,0,64,0,10,15.4,46.5,2014,11,23
+219,3.994,4.05,254734,33,360,720,62.023,13.7,22.8,8.6,0,80,4.57,10,19.4,42.4,2014,11,24
+220,3.846,3.889,261025,35,360,600,54,14.7,21.6,8.5,0,55,0,10,18.5,29.4,2014,11,25
+221,3.216,3.628,269985,37,380,760,61.866,14.1,18,8.5,0,64,0,9.7,16.9,27.8,2014,11,26
+222,3.366,3.788,278556,25,415,830,63.155,14,18.8,10,0,67,0,10,15.4,29.4,2014,11,27
+223,3.644,3.852,270675,41,347,694,62.865,28.1,35,14.2,0,37,0,10,29.6,64.8,2014,11,30
+224,3.424,3.745,263073,34,320,640,60.938,19.7,28.7,15,0,72,0.51,10,14.4,33.5,2014,12,1
+225,3.489,3.759,254788,40,755,1510,68.183,19.1,27.2,14.7,0,68,0,10,14.6,29.4,2014,12,2
+226,3.485,3.763,258868,50,472.5,945,64.477,18.6,23.2,15.2,0,84,10.92,8.4,15.2,29.4,2014,12,3
+227,2.878,3.744,283142,42,290,775,61.533,20.5,26,16,0,74,0.25,9.8,17.8,25.9,2014,12,4
+228,3.799,4.033,270596,22,380.5,761,59.446,15.2,17.3,13.2,0,88,0.76,9,15.6,27.8,2014,12,7
+229,3.506,3.52,226507,28,340,680,59.545,16.2,20.1,13.9,0,72,0,10,17.2,25.9,2014,12,8
+230,2.74,2.854,262896,30,420,840,63.136,15.5,21.5,10.9,1015.7,71,0,16.3,11.6,20.6,2014,12,9
+231,3.779,4.215,249125,30,290,760,69,17.1,20.3,10.7,0,50,0.51,9.8,19.4,31.7,2014,12,10
+232,3.861,4.326,271225,36,442.5,885,63.886,16.6,20.7,13.8,0,76,0.25,10,23.2,40.7,2014,12,11
+233,3.747,3.932,203326,35,385,770,61.668,18.8,26.9,14,0,66,0,10,15.4,29.4,2014,12,14
+234,3.688,3.939,235077,34,380,760,61.866,18.6,25.1,13.5,0,74,0,9,13.1,24.1,2014,12,15
+235,3.238,3.635,270652,34,420,1130,67.315,18.4,33.6,8.7,0,35,0,10,28.3,64.8,2014,12,16
+236,3.429,4.027,247302,34,533.5,1067,64.953,15.9,23,8.5,0,48,0,0,16.1,29.4,2014,12,17
+237,4.893,5.121,229587,30,460,920,63.931,15,24.4,9,0,61,1.78,9.8,21.7,61.1,2014,12,18
+238,3.598,4.028,271184,34,290,755,60,23.2,33.3,10.6,0,47,0,9.8,14.3,35.2,2014,12,21
+239,3.418,3.735,266258,34,405,810,61.24,22.7,26,15.8,0,67,0.51,10,9.4,22.2,2014,12,22
+240,3.257,3.552,257576,25,415,830,63.201,17.9,28.7,10,0,67,0,9.8,18.5,31.7,2014,12,23
+241,3.269,4.05,246012,30,345,690,62.061,14.1,19.9,7.9,0,57,0,10,17.2,31.7,2014,12,26
+242,3.06,3.744,222378,34,370,680,63.227,24.1,33.4,10.7,0,32,0,0,16.7,35.2,2014,12,28
+243,3.848,3.984,186601,34,415,830,63.885,16.6,28.6,10.6,0,48,1.02,10,27.8,53.5,2014,12,29
+244,3.492,3.835,200055,41,405,810,62.243,15.9,24.2,8,0,52,0,10,21.9,44.6,2014,12,30
+245,3.499,3.793,219828,42,470,940,66.354,19.4,32,10.8,0,63,0,10,14.3,35.2,2015,1,1
+246,3.546,4.045,214449,40,365,730,62.019,16.8,24.8,11,0,64,0,10,17.6,31.7,2015,1,4
+247,3.863,4.326,221233,39,360,900,70,18.7,24.6,11.3,0,65,0,10,16.3,25.9,2015,1,5
+248,4.137,4.487,271295,29,465,930,65.049,22.7,33,13.8,0,62,0,9.3,14.4,37,2015,1,6
+249,3.689,4.051,310031,38,482.5,965,65.878,29.2,40.3,16.3,0,43,1.52,10,20.9,50,2015,1,7
+250,1.795,3.704,259810,37,442.5,885,64.523,21.9,29.9,16,0,72,2.79,8,14.4,35.2,2015,1,8
+251,3.044,4.3,184752,32,375,750,61.668,20.5,28.1,14.8,0,69,0,10,17.6,31.7,2015,1,11
+252,2.809,4.459,185148,36,425,850,65.531,25.3,31.2,14.6,0,49,0,10,17.6,35.2,2015,1,12
+253,3.634,3.719,287118,40,350,865,63.885,21.1,25.5,17,0,78,11.18,10.6,24.8,46.5,2015,1,13
+254,3.026,3.651,292543,32,355,710,61.396,17.4,22.6,14,0,72,0,10,28.5,42.4,2015,1,14
+255,3.095,3.713,266493,39,405.5,811,61.591,15.1,20.5,9.6,0,71,0,10,17.2,29.4,2015,1,15
+256,3.035,3.402,203637,50,405,810,62.214,15.7,20.1,11.6,0,52,0,10,23.2,31.7,2015,1,18
+257,3.327,3.527,226385,40,395,790,62.569,17.2,24,10,0,55,0,0,21.5,42.4,2015,1,19
+258,3.213,2.713,251356,44,422,844,64.522,23.8,30.1,10.1,0,47,0,10,20,38.9,2015,1,20
+259,3.38,4.108,258384,50,320,945,68,24.9,33.7,17,0,50,0,8.4,16.9,35.2,2015,1,21
+260,4.411,5.017,236364,53,425.5,851,65.531,25.4,36,16.7,0,52,0,0,15.7,37,2015,1,22
+261,4.127,4.055,234543,49,450,900,64.523,20,29.6,11.9,0,58,0,9.8,18.1,35.2,2015,1,24
+262,4.035,4.2,236791,38,340,680,62.218,15.3,21.5,7.5,0,54,0,10,23.2,33.5,2015,1,26
+263,3.056,3.916,269257,39,360,720,61.814,15.9,20.5,11,0,58,0,10,25.2,35.2,2015,1,27
+264,4.1,5.32,268005,38,405,810,61.591,17.6,25.5,10.7,0,52,0,10,28,50,2015,1,28
+265,5.985,4.579,202419,43,290,875,64.522,16.4,22.8,10.4,0,57,0,10,25.6,42.4,2015,1,29
+266,2.146,3.882,184654,49,290,580,58.389,15.8,23,12,0,71,0.51,9.7,24.3,33.5,2015,1,31
+267,4.605,4.563,223394,40,346.5,693,62.317,15.7,19,12.2,0,74,1.52,10,24.6,33.5,2015,2,1
+268,4.75,6.509,210924,32,380,760,62.023,17.4,23.6,13.9,0,64,0,10,21.7,35.2,2015,2,2
+269,5.969,6.553,241560,31,397.5,795,62.061,17.2,22.7,13.7,0,58,0,10,22.8,31.7,2015,2,3
+270,5.969,6.302,247056,43,350,865,73,15.3,20.2,10.6,0,66,0.25,10,19.1,35.2,2015,2,4
+271,6.361,7.9,235506,42,452.5,905,64.366,19.1,28,10.1,0,63,0,10,15.9,27.8,2015,2,5
+272,4.879,4.666,246107,38,420,840,64.366,17.1,26.7,13,0,67,0,10,21.3,29.4,2015,2,8
+273,4.272,4.533,242358,35,383.5,767,61.866,19.9,28,12.7,0,64,0,10,15.9,27.8,2015,2,9
+274,3.71,4.105,224013,36,370,840,65.531,23.9,31.1,14.9,0,58,0,0,16.9,40.7,2015,2,10
+275,3.658,4.028,228766,36,425,850,65.531,22.1,35.4,15.9,0,61,0,10,22,38.9,2015,2,11
+276,4.355,4.672,252061,37,370,740,62.023,18.9,28,14,0,63,0,10,15.6,37,2015,2,12
+277,4.082,3.767,265724,38,407.5,815,61.339,20.1,26.9,14.7,0,79,0,10,12.4,27.8,2015,2,14
+278,3.082,3.859,264516,30,340,680,62.443,26.2,34.7,14.6,0,41,0,10,14.8,29.4,2015,2,15
+279,3.894,4.117,249175,38,350,890,74,19.5,28.8,15.6,0,64,0,10,21.3,31.7,2015,2,16
+280,3.758,3.917,251137,39,435,870,64.256,17.6,20.7,16,0,75,0,10,15.4,20.6,2015,2,17
+281,3.744,3.799,242665,42,455,910,64.411,18.7,21.6,15.8,0,78,0,10,15.9,24.1,2015,2,18
+282,3.037,3.801,234605,36,375,750,62.875,21.5,31,15,0,70,0,10,13,25.9,2015,2,19
+283,4.186,4.223,252788,39,350,610,58.754,27.8,37,19,0,42,0,10,24.1,48.2,2015,2,22
+284,3.418,3.737,256896,36,333.5,667,61.396,17.9,30,14.9,0,67,13.72,9.2,22.2,38.9,2015,2,23
+285,3.428,4.257,243380,33,395,790,62.023,16.7,20.5,13.7,0,64,0,10,18.3,33.5,2015,2,24
+286,3.729,4.16,209192,33,390,780,61.866,20.4,27.6,13.5,0,66,0,10,12.8,22.2,2015,2,25
+287,3.419,3.883,252085,50,550,1100,68.82,19,25.3,13.9,0,72,0,10,13.5,24.1,2015,2,26
+288,4.189,4.452,294669,36,335,670,61.396,15,21.6,9,0,70,0,10,18.3,33.5,2015,3,1
+289,4.18,4.032,305444,37,360,610,56,18.5,24.1,8.7,0,59,0,10,10.6,16.5,2015,3,2
+290,4.483,4.823,291851,40,395,790,61.591,17.3,23,13,0,67,0,10,12.4,22.2,2015,3,3
+291,3.9,4.039,291310,46,350,700,61.885,17.8,25,9,0,51,0.25,9.7,22.8,42.4,2015,3,4
+292,3.312,3.895,249632,41,415,830,64.522,15.4,20.3,9.2,0,49,0,10,25.7,38.9,2015,3,5
+293,3.465,3.716,251624,43,465,930,64.523,16.4,20.8,12,0,80,1.02,10,17.6,37,2015,3,6
+294,3.493,3.789,248311,39,330,660,62.317,18.1,24.4,12.2,0,60,0,10,15.6,33.5,2015,3,9
+295,3.521,3.787,290098,36,540,1260,68.82,16.1,23.3,10,0,61,0,10,12.8,24.1,2015,3,10
+296,3.519,3.61,277457,35,375,750,61.434,17.6,26.6,9.3,0,57,0,10,15,29.4,2015,3,11
+297,3.536,3.835,278587,39,365,730,61.942,15.9,20,10.2,0,52,0,9.8,25,35.2,2015,3,12
+298,2.961,3.605,294721,39,290,580,58.616,13.8,21,8.5,0,69,0,10,19.3,35.2,2015,3,15
+299,3.173,3.717,286156,36,360,720,61.591,21.3,24.2,7.7,0,40,0,0,20.4,40.7,2015,3,16
+300,3.599,3.532,268211,44,641,1282,68.82,21.4,27,14.7,0,48,1.27,9,29.1,53.5,2015,3,17
+301,2.934,3.992,209680,44,360,860,62,20.2,26,14.6,0,62,0,10,20.7,57.6,2015,3,18
+302,4.147,3.606,228052,42,415,830,65.531,19.8,33,10,0,52,0,10,28.9,61.1,2015,3,19
+303,3.561,4.495,267762,43,380,760,62.441,23.2,28,8.2,0,38,0,10,28,44.6,2015,3,22
+304,3.697,4.166,276968,44,440,880,64.477,18,27,11.9,0,58,0,10,23.9,40.7,2015,3,23
+305,3.47,3.516,254816,36,850,1700,68.82,13.4,15,10.7,0,56,0,10,19.8,31.7,2015,3,24
+306,2.946,3.578,288791,48,470,940,65.114,14,21,7,0,54,0,10,15.9,33.5,2015,3,25
+307,2.962,3.68,293262,37,540,1027,65.114,14.5,19,6.9,0,51,0,10,29.6,44.6,2015,3,26
+308,3.049,2.972,257723,43,380,760,61.451,16,24,6.6,0,58,0,0,13.1,24.1,2015,3,29
+309,3.696,4.259,260068,35,350,855,58,16.1,24,8.4,0,64,0,10,12,27.8,2015,3,30
+310,2.987,3.816,264152,34,420,970,64.477,19.8,27,9.2,0,50,0,0,18.1,44.6,2015,3,31
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+312,3.266,3.687,199607,42,370,740,61.186,13.2,19,5.2,0,67,0,10,18.1,27.8,2015,4,3
+313,3.147,3.608,203120,38,410,820,62.061,16.4,18,7.2,0,40,0,0,10.4,20.6,2015,4,6
+314,2.698,3.47,235405,35,480,885,65.59,12.3,17,8.4,0,82,8.89,8.5,27,40.7,2015,4,7
+315,2.977,2.679,266782,26,432.5,865,62.94,12.5,17,6.6,0,76,0,10,16.3,31.7,2015,4,8
+316,3.418,4.126,263134,36,495,990,64.757,12.9,18.3,6.2,0,72,0,10,14.8,22.2,2015,4,9
+317,3.267,3.522,283802,38,310,620,59.316,11.5,18.3,5,0,73,0,10,13.1,27.8,2015,4,12
+318,3.231,3.635,290642,30,475,950,65.114,14.6,21,12,0,68,0,9.5,8.5,14.8,2015,4,13
+319,2.963,3.603,307803,37,442.5,885,63.995,19.3,25,16,0,56,0,10,24.6,38.9,2015,4,14
+320,2.972,3.445,328693,30,590,900,66,19.6,27,14,0,64,0,10,21.9,51.9,2015,4,15
+321,3.364,3.901,324639,37,480,960,65.114,13.3,18,8,0,70,0,10,11.1,25.9,2015,4,16
+322,3.018,4.054,226162,29,320,640,60.632,9.6,13,5,0,66,0,10,21.1,46.5,2015,4,19
+323,3.789,3.732,281335,43,480,960,64.28,10.1,15.3,5,0,65,0,10,19.3,35.2,2015,4,20
+324,3.418,3.37,349614,34,395,790,61.24,12,17,7,0,71,0,10,16.9,31.7,2015,4,21
+325,3.93,6.605,222194,29,342.5,685,61.866,14.8,18.1,11.5,0,82,0,10,19.8,31.7,2015,4,22
+326,5.774,9.622,299114,29,510,970,65.114,14.9,17,12,0,86,0,9.3,12,20.6,2015,4,23
+327,3.277,4.007,346056,26,387.5,775,59.603,11.3,15.2,9.9,0,78,0,9.7,22.2,33.5,2015,4,26
+328,4.23,3.846,309250,34,485,970,65.114,11.3,14.4,8,0,78,0,10,14.6,25.9,2015,4,27
+329,2.91,3.144,317141,35,367.5,735,60.406,10.5,15,5.8,0,82,0,10,12,25.9,2015,4,28
+330,4.702,5.906,259241,42,520,945,62,10.4,17,6,0,74,0,10,11.1,18.3,2015,4,29
+331,4.401,4.079,300014,42,460,920,63.004,11.9,19,5,0,69,0,10,11.7,22.2,2015,4,30
+332,3.844,4.465,322354,35,367.5,735,60.406,11.6,18,6.5,0,78,0,9.3,12.4,22.2,2015,5,3
+333,4.272,5.115,316828,33,370,740,61.591,17.2,22,11.8,0,49,0,9.3,36.9,55.4,2015,5,4
+334,4.468,4.126,278662,34,430,860,63.949,12.1,16,8,0,56,0,10,27,57.6,2015,5,5
+335,3.571,3.874,262781,49,460,920,64.523,10.9,16,8,0,68,0,9.7,23,40.7,2015,5,6
+336,3.659,3.822,275288,34,530,940,65.114,11.1,14.3,9,0,71,0,10,21.5,42.4,2015,5,7
+337,3.572,4.096,329601,35,305,610,56.089,12.9,15,10,0,73,0,9.7,28,44.6,2015,5,10
+338,3.535,3.935,307695,35,372.5,745,61.396,13.6,15.2,12,0,66,0,9.8,22,38.9,2015,5,11
+339,3.566,4.077,351864,33,380,760,60.563,9,16.2,5,0,69,0,9.8,29.1,51.9,2015,5,12
+340,3.434,4.018,361830,25,290,570,40,9.3,12,7,0,73,0,10,24.3,33.5,2015,5,13
+341,3.396,3.711,341750,30,325,650,61.24,12.2,15,10.5,0,85,0,8.2,21.7,31.7,2015,5,14
+342,4.316,5.744,374614,26,295,590,53.295,12.9,20,6,0,68,0,10,17.8,25.9,2015,5,17
+343,3.429,3.224,359322,33,337.5,675,61.591,14.9,19,11,0,54,0,0,25,46.5,2015,5,18
+344,4.392,4.919,263942,36,370,750,61.396,13.5,16,11,0,83,0,10,26.5,42.4,2015,5,19
+345,3.505,3.748,361360,34,380,760,61.396,11.9,18,8.8,0,81,0,8.4,21.9,33.5,2015,5,20
+346,3.882,4.158,368798,27,297.5,595,53.295,10.3,12,8,0,94,0,9,10.6,18.3,2015,5,21
+347,3.653,3.961,334780,33,382.5,765,60.406,10.3,17,6,0,71,0,0,14.8,24.1,2015,5,24
+348,3.244,3.697,361330,36,440,975,68,9.9,16,5,0,72,0,0,20.2,27.8,2015,5,25
+349,3.38,3.786,378301,31,410,820,61.396,12.3,15,9.5,0,65,0,0,27.4,44.6,2015,5,26
+350,3.558,3.979,324196,28,350,700,59.603,13.7,17,11.9,0,74,0,10,35.7,42.4,2015,5,27
+351,3.815,4.688,307174,31,368,736,60.563,13.4,19,6,0,64,0,10,22.8,35.2,2015,5,28
+352,3.865,3.716,246106,40,460,710,61.608,8.3,16,3,0,50,0,9.8,21.3,35.2,2015,5,31
+353,2.958,3.652,267978,34,320,640,59.948,7.2,10,5,0,78,0,10,18,27.8,2015,6,1
+354,3.699,3.979,266112,37,405,810,61.033,8.1,10,6,0,92,0,9.5,9.8,20.6,2015,6,2
+355,3.483,3.633,295506,38,365,730,60.563,7.6,11,4,0,77,0,10,13,37,2015,6,3
+356,2.989,3.54,303551,37,407.5,815,60.758,7.6,10,6.7,0,50,0,10,33.5,42.4,2015,6,4
+357,3.651,3.837,285824,31,395,790,61.866,10.7,13,8.8,0,76,0,9.8,17.4,27.8,2015,6,5
+358,3.453,4.079,275973,35,320,890,62,13.7,17,5,0,66,0,9.3,28.7,40.7,2015,6,8
+359,3.096,3.286,313947,32,345,690,60.406,8.6,13,5,0,73,0,10,18.1,31.7,2015,6,9
+360,3.068,3.367,294143,32,420,840,62.257,8.8,11.2,3,0,72,0,10,13,24.1,2015,6,10
+361,2.971,3.194,312226,37,480.5,961,63.643,7.5,13,3,0,52,0,9.8,7.6,14.8,2015,6,11
+362,2.96,3.452,307405,38,383.5,767,60.406,10.8,17,6,0,78,0,10,8.9,16.5,2015,6,14
+363,2.967,3.434,266534,42,750,1500,68.183,12.6,17,10,0,50,0,7.2,5,20.6,2015,6,15
+364,2.944,3.304,286756,40,440,920,63.155,12.7,15.2,11,0,56,0,10,8.3,22.2,2015,6,16
+365,2.987,4.158,290286,40,450,900,63.201,11.8,14,9.8,0,56,0,9.8,14.4,25.9,2015,6,17
+366,3,3.218,271786,34,456,912,62.895,8.7,11.3,5,0,54,0,10,15.9,29.4,2015,6,18
+367,3.011,3.581,256123,38,562.5,1125,68.183,7.3,12,3,0,66,0,10,26.1,51.9,2015,6,21
+368,3.022,3.512,264775,39,370,800,60.885,10.4,12,5,0,66,0,10,38.7,51.9,2015,6,22
+369,3.26,3.471,329228,49,370,840,63.312,13.2,17,8.9,0,65,0,10,31.9,46.5,2015,6,23
+370,3.023,3.18,235591,42,760,875,60,11.1,16,7.9,0,77,0,9.8,15.2,22.2,2015,6,24
+371,3.022,3.105,255570,45,450,900,63.729,11.4,13,10,0,74,0,10,13.1,27.8,2015,6,25
+372,3.013,3.188,272990,46,371,742,61.256,9.9,14,5,0,77,0,10,8.5,16.5,2015,6,28
+373,3.024,3.138,266714,41,485,970,63.643,7.8,13,3.5,0,51,0,9.8,8.5,14.8,2015,6,29
+374,3.019,3.154,277412,36,521,1042,64.12,9.8,12.4,5,0,70,0,10,9.8,15.3,2015,6,30
+375,2.992,3.252,267615,35,437.5,875,63.84,11.1,14,9,0,59,0,9.5,22.2,33.5,2015,7,1
+376,2.849,3.27,262835,33,360,730,61.19,7.3,11.1,3,0,70,0,10,18.1,40.7,2015,7,2
+377,3.048,3.223,230251,44,515,1030,64.953,9.9,15,7,0,60,0,9.5,33.7,44.6,2015,7,5
+378,2.961,3.204,228277,34,494,988,64.953,8.3,11,7,0,80,0,1,26.5,35.2,2015,7,6
+379,2.653,3.292,268192,42,526.5,1053,63.643,8.1,14,2,0,83,0,10,12,22.2,2015,7,7
+380,3.026,3.228,255014,42,370,884,66,10.7,14,8.7,0,71,0,10,17.2,25.9,2015,7,8
+381,3.03,3.345,320720,37,490,980,63.643,9.7,12,6,0,71,0,10,22.6,35.2,2015,7,9
+382,3.037,3.356,186893,25,340,680,59.396,9,11,6,0,92,0,5,28,38.9,2015,7,12
+383,2.901,4.444,258631,20,250,500,53.152,8.7,12,6.8,0,77,0,10,24.6,33.5,2015,7,13
+384,3.399,3.456,345185,31,200,593,54.531,5.9,9,3,0,81,0,10,20,50,2015,7,14
+385,3.029,3.46,350890,37,327,654,60.406,7.4,9,5,0,82,0,10,9.8,20.6,2015,7,15
+386,3.274,3.356,295550,38,395,790,61.033,8.4,12,6,0,79,0,9.7,21.1,29.4,2015,7,16
+387,3.006,3.245,266787,30,440,880,60.852,5.2,13,-1,0,75,0,10,10,20.6,2015,7,19
+388,3.607,3.818,208687,36,450,960,58,9.8,14,5,0,61,0,10,27,48.2,2015,7,20
+389,3.008,3.381,256514,41,497.5,995,64.953,12.7,15.2,11,0,67,0,9.5,39.6,55.4,2015,7,21
+390,3.007,3.36,264696,48,480,960,64.12,9.8,15.3,6,0,74,0,1,18.9,31.7,2015,7,22
+391,3.108,3.437,279179,37,489,978,64.953,10.4,14,7,0,81,0,1,22.8,33.5,2015,7,23
+392,3.155,3.242,288225,30,300,760,61.19,6.6,11,4,0,67,0,10,27.8,61.1,2015,7,26
+393,3.403,3.741,301315,36,415,830,63.091,8.9,13,6.9,0,73,0,10,20.6,31.7,2015,7,27
+394,2.998,3.713,306927,26,590,1180,68.183,9.9,14,5.8,0,74,0,1,13.9,22.2,2015,7,28
+395,3.449,3.809,264852,26,488.5,977,64.953,9.3,13,7,0,67,0,1,28.9,55.4,2015,7,29
+396,3.318,3.722,267722,40,495,990,64.12,7.8,11,4,0,73,0,1,32,64.8,2015,7,30
+397,3.23,3.667,334956,41,425,850,62.479,10.1,14,6,0,62,0,9.8,27.4,38.9,2015,8,2
+398,2.995,3.686,330269,32,340,1050,51,5.6,10,2,0,67,0,10,20,37,2015,8,3
+399,3.575,3.621,328755,36,450,900,62.367,8.6,10,6,0,66,0,9.8,22,31.7,2015,8,4
+400,2.984,3.577,341811,29,554,1108,68.183,7.4,11,4,0,76,0,9.8,23.9,40.7,2015,8,5
+401,3.447,3.664,305398,28,400,800,58.612,9.3,13,6,0,85,0,10,17.2,31.7,2015,8,6
+402,3.274,3.67,314875,42,440,880,63.248,9.5,12,7.8,0,72,0,10,31.9,57.6,2015,8,9
+403,2.992,3.527,306061,45,460,920,62.524,9.8,15,6,0,69,0,10,27.2,53.5,2015,8,10
+404,3.067,3.451,313726,27,360,952,63.312,10.9,14,7,0,57,0,10,31.1,48.2,2015,8,11
+405,2.98,3.363,307656,23,500,1000,64.477,8.9,12,7,0,81,0,10,16.7,24.1,2015,8,12
+406,2.979,3.342,297035,34,460,920,63.201,10.5,12,8,0,65,0,10,16.7,25.9,2015,8,13
+407,4.322,4.798,315056,47,415,830,63.312,11.3,15,8,0,67,0,9.3,21.7,35.2,2015,8,16
+408,3.305,3.744,363624,45,450,900,62.524,6.6,11,4,0,77,0,10,18.7,33.5,2015,8,17
+409,3.215,3.779,335108,43,412.5,825,60.757,7.8,10,5.6,0,78,0,10,6.3,16.5,2015,8,18
+410,2.924,3.764,317375,42,470,840,61,8.8,13,4.7,0,64,0,10,16.1,44.6,2015,8,19
+411,3.098,3.658,338254,44,470,940,64.477,13,16,11,0,55,0,0,39.3,51.9,2015,8,20
+412,3.261,3.536,324078,45,410,820,61.463,10.9,16,7,0,74,0,10,15.2,22.2,2015,8,23
+413,3.056,2.88,342521,44,415,830,63.248,10.3,12,9,0,73,0,10,28,37,2015,8,24
+414,2.702,3.948,291742,47,438,876,63.091,9.9,13,7,0,76,0,9.8,17.4,31.7,2015,8,25
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+416,3.289,3.545,225561,42,310,735,61.198,9.4,11.2,6.6,0,92,0,9.3,17.2,29.4,2015,8,27
+417,2.994,3.475,258161,41,380,760,60.728,8.7,11,6.5,0,78,0,10,13.7,22.2,2015,8,30
+418,2.997,3.303,247673,36,425,850,62.83,8.4,13,1.8,0,68,0,10,11.7,20.6,2015,8,31
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+420,2.954,3.449,283458,37,330,880,60,12.3,18,9,0,73,0,10,15.4,37,2015,9,2
+421,3.033,3.306,298037,51,500,1000,63.643,9.4,13.1,4,0,79,0,10,17.8,35.2,2015,9,3
+422,3.01,3.31,296488,50,417,834,63.312,10.8,15,8,0,66,0,9.8,29.3,50,2015,9,6
+423,3.025,3.28,255120,43,435,870,63.293,9.4,12,8,0,71,0,9.5,22.6,40.7,2015,9,7
+424,3.012,3.247,263866,48,340,780,61.632,10.3,13,9,0,77,0,8.9,17,31.7,2015,9,8
+425,1.868,3.394,299105,48,455,910,63.201,10.9,14,8,0,74,0,10,14.4,31.7,2015,9,9
+426,3.491,3.356,284981,45,470,940,64.12,9.3,16,4,0,77,0,10,13.5,29.4,2015,9,10
+427,2.934,3.38,246534,36,413,826,62.218,18.8,24,15,0,49,0,0,32.4,48.2,2015,9,13
+428,3.136,3.385,296682,30,380,769,52,18,25.7,9.9,0,55,0,9,27.8,48.2,2015,9,14
+429,2.99,3.261,288903,29,313.5,627,58.136,10.6,16,6,0,69,0,10,18.5,35.2,2015,9,15
+430,4.36,5.105,304905,33,380,760,61.339,10.6,15,7,0,77,0,9.8,11.7,27.8,2015,9,16
+431,5.116,6.025,289703,26,313.5,627,57.178,10.9,14,8.8,0,78,0,9.7,14.3,27.8,2015,9,17
+432,5.381,5.589,286984,36,350,747,62.218,16.8,22,13,0,55,0,10,26.9,42.4,2015,9,20
+433,3.229,3.711,248065,37,494,988,64.12,10.1,17.1,5.9,0,69,0,10,22.2,37,2015,9,21
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+435,3.003,3.592,228784,54,661,1322,68.183,8.6,12.6,4,0,62,0,10,18.5,31.7,2015,9,23
+436,3.257,3.476,236778,51,449,898,62.895,9.1,15,1.9,0,74,0,10,15.4,27.8,2015,9,24
+437,3.3,3.735,230818,38,442.5,885,63.097,13.3,21,5,0,53,0,10,13.7,33.5,2015,9,27
+438,3.289,3.578,208883,45,514,1028,64.12,13.3,22,6,0,56,0,10,13.9,22.2,2015,9,28
+439,3.033,3.472,236426,48,458.5,917,63.774,12.3,17,9.8,0,67,0,10,14.4,27.8,2015,9,29
+440,2.978,3.435,277242,54,570,1193,86,10,17,4,0,66,0,10,17.6,25.9,2015,9,30
+441,3.124,3.376,201316,41,449.5,899,63.931,21.6,28,17,0,33,0,0,31.3,51.9,2015,10,2
+442,2.969,3.296,238051,39,479,958,64.953,18.5,28,11,0,53,0,0,13.3,27.8,2015,10,4
+443,2.959,3.336,223142,40,434,868,64.849,26.4,34.1,19,0,23,0,0,33.5,48.2,2015,10,5
+444,3.181,3.61,275130,43,442,884,64.367,19.2,35,9,0,35,0,10,30.6,64.8,2015,10,6
+445,2.979,3.479,303446,45,454,908,63.403,11.5,16,8,0,60,0,10,20.7,33.5,2015,10,7
+446,2.998,3.712,285342,46,560,996,64.477,15.4,25,9,0,62,0,0,12.8,33.5,2015,10,8
+447,3.369,3.546,280161,39,439.5,879,63.091,15.3,26,10,0,79,0,7.4,18,31.7,2015,10,11
+448,2.974,3.365,239798,39,418,836,62.303,11.3,15,5,0,71,0,10,17.6,29.4,2015,10,12
+449,2.953,3.418,277537,35,342,684,61.24,13.4,21,7,0,71,0,10,12.6,29.4,2015,10,13
+450,2.964,3.272,302267,44,430,582,68,22,28,17,0,46,0,10,23.3,38.9,2015,10,14
+451,2.979,3.551,293161,42,254,508,58.616,24.4,34,16,0,25,0,0,19.3,44.6,2015,10,15
+452,2.963,3.463,271285,37,415,830,62.322,12.4,19,6,0,66,0,0,13.1,22.2,2015,10,18
+453,4.107,4.156,239881,35,427.5,855,63.729,19.4,28,10,0,36,0,0,17.4,31.7,2015,10,19
+454,2.99,3.394,264259,48,420,865,64.849,23.2,32,15,0,47,0,9.5,18.3,35.2,2015,10,20
+455,2.927,3.297,262920,34,470,940,64.953,12.4,18,10,0,79,0,9.8,22.8,33.5,2015,10,21
+456,2.834,3.001,290372,40,450,900,63.886,12.1,16,10,0,73,0,9.7,21.9,33.5,2015,10,22
+457,2.855,2.95,271698,36,400,800,63.227,22,32,13,0,35,0,9.7,29.8,53.5,2015,10,25
+458,2.129,2.891,265113,48,380,1115,70,11.9,16,9,0,70,0,10,26.9,40.7,2015,10,26
+459,2.488,2.748,237002,48,470,940,64.953,15.7,23,8,0,47,0,10,18.9,44.6,2015,10,27
+460,2.544,3.127,261331,48,645,1290,68.183,17.8,26,10,0,49,0,6.3,16.1,33.5,2015,10,28
+461,3.355,3.706,268448,48,485,970,64.953,19.2,26,10.7,0,43,0,0,13.7,31.7,2015,10,29
+462,3.412,3.319,248447,50,380,760,62.374,17.1,26,13,0,76,0,9.5,15.9,38.9,2015,11,1
+463,2.898,3.221,267357,50,380,845,63.136,14.1,18,9,0,68,0,10,12.6,20.6,2015,11,3
+464,2.889,3.279,278282,53,495,990,64.477,20.5,27,16.8,0,72,0,7.7,15.6,29.4,2015,11,4
+465,2.897,3.364,244110,33,360,720,62.023,18.7,24,15,0,82,0,10,14.6,63,2015,11,5
+466,3.36,3.641,303666,37,325,650,61.591,19.3,26,13,0,34,0,0,16.3,35.2,2015,11,8
+467,3.065,3.574,300547,49,430.5,861,64.321,22.8,34,14,0,41,0,9.2,18.1,33.5,2015,11,9
+468,3.152,3.459,277916,50,552.5,1105,68.183,12.3,15,10.8,0,79,0,9.8,18,29.4,2015,11,10
+469,3.076,3.451,291609,50,580,1110,92,14.8,18,12,0,50,0,9.7,9.4,14.8,2015,11,11
+470,2.887,3.337,301484,50,530,1060,64.477,16.5,23,12,0,75,0,10,16.7,27.8,2015,11,12
+471,3.22,3.508,238098,43,437.5,875,63.136,14.9,22,10.8,0,71,0,10,16.5,25.9,2015,11,15
+472,3.276,3.663,253699,42,405,810,61.942,21.3,27,14,0,45,0,0,20.2,44.6,2015,11,16
+473,2.992,3.551,258243,47,487.5,975,65.717,19.4,33,10,0,42,0,9.8,17.6,44.6,2015,11,17
+474,2.993,3.442,277745,47,530,1060,64.477,25.1,29,20,0,34,0,10,15.9,35.2,2015,11,18
+475,3.123,3.859,262671,50,380,945,64.367,20.1,33,14,0,64,0,9.8,16.7,44.6,2015,11,19
+476,3.189,3.419,272561,50,420,840,63.201,15.3,21,12,0,61,0,10,15,27.8,2015,11,22
+477,3.173,3.384,305234,50,450,900,63.201,15.4,21,9.8,0,63,0,10,15.4,29.4,2015,11,23
+478,3.902,4.112,265673,41,585,1170,68.183,18.3,27,11,0,50,0,10,16.3,42.4,2015,11,24
+479,3.403,3.796,267475,42,450,1030,72,23.4,34,8,0,26,0,10,40.2,68.3,2015,11,25
+480,3.203,3.431,275814,46,545,1090,68.183,11.3,17,5,0,47,0,10,25.9,48.2,2015,11,26
+481,3.444,3.638,271563,44,417.5,835,63.358,14.5,25,8.5,0,64,0,10,16.7,35.2,2015,11,29
+482,1.927,3.398,280864,50,370,1100,67.264,21.4,32,13,0,44,0,10,23.9,51.9,2015,11,30
+483,3.462,3.402,276888,50,370,920,63.312,14.1,23,7,0,45,0,10,23.5,46.5,2015,12,1
+484,3.013,3.282,269369,50,370,870,63.84,12.9,18,8,0,54,0,10,18.3,33.5,2015,12,2
+485,3.021,3.204,279465,50,490,840,64.477,15.6,27,9,0,65,0,10,12.4,27.8,2015,12,3
+486,3.43,3.647,167532,40,360,760,62.019,21.8,29.3,17,0,64,0,10,14.1,24.1,2015,12,6
+487,3.027,3.265,231881,50,340,920,78,23.4,27,20,0,64,0,10,17.6,42.4,2015,12,7
+488,2.997,3.392,257198,50,380,900,64.367,21.9,36,13,0,53,0,10,25,48.2,2015,12,8
+489,3.587,4.109,279211,48,570,940,64.477,17.7,27,10.6,0,59,0,10,16.1,33.5,2015,12,9
+490,3.213,2.942,223469,44,520,860,64.953,18.2,26,11,0,49,0,10,18,29.4,2015,12,10
+491,3.56,4.035,248592,47,280,760,61.827,19.4,29,10.6,0,34,0,0,15.4,29.4,2015,12,13
+492,3.305,3.819,261120,46,420,990,63.201,20.8,27,16,0,60,0,7.6,15.7,25.9,2015,12,15
+493,3.672,3.851,253265,45,660,900,64.477,22.5,29,15,0,57,0,0,22.4,46.5,2015,12,16
+494,3.021,3.387,274939,44,320,940,64.367,28.6,36.2,19.8,0,26,0,0,20.9,44.6,2015,12,17
+495,3.106,3.598,207493,50,360,790,62.569,20.9,0,13,0,55,0,10,20.4,50,2015,12,20
+496,3.663,3.768,190031,35,380,760,66,15.6,20,11,0,56,0,10,22.4,35.2,2015,12,21
+497,3.622,3.77,208327,49,340,900,63.729,19,25,14,0,61,0,10,14.4,24.1,2015,12,22
+498,3.8,3.85,230542,48,450,1000,63.886,22.1,29,14.7,0,59,0,10,17.4,33.5,2015,12,23
+499,3.053,3.404,185676,48,422.98,845.96,64.894,26.2,35,12,0,29,0,6.6,35.4,53.5,2015,12,25
+500,3.485,3.627,189064,44,280,660,61.834,16.7,22,11,0,62,0,10,14.8,25.9,2015,12,28
+501,3.048,3.463,175314,37,320,690,61.668,18.8,27,12,0,60,0,0,14.4,27.8,2015,12,29
+502,3.103,3.297,174974,35,360,860,64.738,29.4,35,23,0,19,0,0,19.1,31.7,2015,12,30
+503,3.095,3.273,204968,50,422.98,845.96,64.366,20.5,28,16,0,61,0,10,19.1,27.8,2016,1,1
+504,3.086,3.272,175665,54,280,730,61.844,20.1,27,14,0,62,0,10,14.8,31.7,2016,1,3
+505,3.071,3.266,187587,51,320,800,61.962,19.1,24,14,0,66,0,10,11.3,22.2,2016,1,4
+506,3.069,3.217,179315,49,340,840,57,20.4,25,16,0,66,0,10,11.7,29.4,2016,1,5
+507,3.085,3.547,183456,43,630,970,65.59,19.8,25,15,0,70,0,10,22.6,40.7,2016,1,6
+508,2.537,3.377,203716,50,570,910,65.59,17.9,23,13.9,0,61,0,10,25,35.2,2016,1,7
+509,3.653,3.562,211567,44,280,700,63.364,24.6,34,17,0,36,0,0,14.4,25.9,2016,1,10
+510,3.785,3.709,229446,49,320,970,65.531,23.1,37,15,0,51,0,10,16.1,57.6,2016,1,11
+511,2.745,3.434,231955,46,360,880,65.531,21.7,36,15,0,60,0,10,13.7,35.2,2016,1,12
+512,3.458,3.215,269373,43,360,870,65.004,28.9,43,16.9,0,32,0,10,28,48.2,2016,1,13
+513,3.354,3.585,252342,43,550,1000,65.114,14.3,18,12,0,61,0,10,23,38.9,2016,1,14
+514,3.46,3.933,242024,46,320,760,63.521,26.7,32,21,0,23,0,0,24.3,42.4,2016,1,17
+515,3.274,3.641,216526,36,370,900,65.531,23.9,36.3,13,0,31,0,10,16.1,38.9,2016,1,18
+516,3.238,3.563,246403,38,410,1000,64.847,23.9,33,17.8,0,48,0,10,13.7,25.9,2016,1,19
+517,3.085,3.335,203753,36,380,750,61.668,22,30,18,0,74,0,8.2,16.1,29.4,2016,1,20
+518,3.014,3.295,242712,36,420,1000,70,19.5,27,16.9,0,79,0,8.7,10.6,40.7,2016,1,21
+519,3.033,3.216,163031,52,510,830,65.59,18.3,23,15,0,76,0,9.7,18.5,31.7,2016,1,24
+520,2.954,3.237,186628,49,310,850,64.366,22.8,29,17.9,0,57,0,10,12.2,31.7,2016,1,26
+521,4.115,4.9,247019,45,650,950,65.114,23.7,28.1,21,0,60,0,10,31.5,46.5,2016,1,27
+522,4.408,4.099,284997,51,460,780,61.619,19.3,29,13,0,78,0,9.5,18.7,33.5,2016,1,28
+523,3.028,3.503,280083,49,320,590,58.488,14.9,20,10,0,72,0,10,20.4,40.7,2016,1,31
+524,3.024,3.38,260268,50,320,680,61.533,19.7,25,15,0,67,0,8.5,12.8,25.9,2016,2,1
+525,4.193,4.705,246364,50,350,930,66,23.5,32,17,0,54,0,9,18.3,27.8,2016,2,2
+526,4.173,4.149,254234,40,300,740,61.69,17.5,21,16,0,66,2.03,10,26.7,37,2016,2,3
+527,4.09,4.288,287372,41,370,760,61.748,17.7,21,14,0,71,0,10,20.9,33.5,2016,2,4
+528,4.112,4.236,248066,36,300,680,62.348,22.4,31,16,0,61,0,10,16.1,29.4,2016,2,7
+529,3.001,3.425,245010,45,430,840,63.838,19.5,24,17,0,63,0,10,18.3,27.8,2016,2,8
+530,3.199,3.745,233490,46,450,810,62.218,19.9,25,16,0,66,0,10,13.9,22.2,2016,2,9
+531,3.132,3.504,208796,36,560,820,62.622,20.1,24,17,0,62,0,10,16.5,22.2,2016,2,10
+532,2.735,3.412,205307,50,540,1100,68.82,19.7,25,15,0,64,0,10,17.6,29.4,2016,2,11
+533,0.187,4.761,239544,38,360,770,67,18.3,25,12,0,55,0,10,19.1,35.2,2016,2,14
+534,2.344,4.887,230809,33,340,660,62.218,19.4,27.7,13.9,1013.2,45,0,12.6,21.5,37,2016,2,15
+535,4.094,5.327,256059,30,370,700,62.218,15.1,18,13,0,55,0,10,27,38.9,2016,2,16
+536,3.703,4.961,272004,20,400,730,59.603,17.9,23,14.8,0,73,0,9.8,23.5,35.2,2016,2,17
+537,3.961,4.368,222314,32,350,810,61.866,18.3,23,15,0,68,0,10,11.3,18.3,2016,2,18
+538,3.885,3.919,222672,21,300,660,60.267,20.4,28,14,0,52,0,0,14.1,24.1,2016,2,21
+539,3.143,3.691,210987,50,230,730,63.393,25.1,33,19,0,37,0,0,15.4,51.9,2016,2,22
+540,3.384,3.844,215544,46,360,840,65.531,29.3,40,23,0,32,0,0,23.7,53.5,2016,2,23
+541,5.409,6.357,219079,32,580,750,62.622,22.1,28.2,18.9,0,72,0,10,14.8,31.7,2016,2,24
+542,5.371,5.975,207570,42,560,840,65.59,20.1,30,12,0,64,0,10,17.6,31.7,2016,2,25
+543,4.9,5.051,192139,50,330,1000,64.366,18.6,23,14,0,61,0,10,18.3,27.8,2016,2,28
+544,3.954,4.018,177134,50,360,710,62.048,18.5,26,13,0,73,0,9.5,15,35.2,2016,2,29
+545,4.17,4.504,201268,49,490,890,66.354,25.1,34,17.9,0,31,0,0,20.7,35.2,2016,3,1
+546,4.152,4.438,229270,49,480,920,74,23.6,36,16.5,0,47,0,10,17.8,35.2,2016,3,2
+547,3.538,4.094,272464,44,410,520,58.766,19.6,26,15,0,64,0,10,12.4,20.6,2016,3,3
+548,4.237,4.759,248067,55,340,360,58.806,21.1,28,15.1,0,72,0,10,13.5,27.8,2016,3,6
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+592,4.819,5.984,213211,50,470,790,62.973,17.8,20,15,0,88,0,9.8,25.4,57.6,2016,5,8
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+598,4.242,4.53,255636,49,670,900,65.59,15.4,18.7,12,0,67,0,10,30.7,59.4,2016,5,16
+599,4.498,5.055,266683,40,620,900,65.114,14,17,11.2,0,58,0,10,16.1,29.4,2016,5,17
+600,3.708,4.041,283088,53,720,1100,68.82,15.2,19,13,0,56,0,10,22.6,29.4,2016,5,18
+601,4.858,5.546,248615,50,600,1000,65.59,14.6,17,9.8,0,73,0,10,20.6,38.9,2016,5,19
+602,4.363,4.332,206024,52,530,910,65.59,16.9,21,11,0,58,0.51,10,34.4,53.5,2016,5,22
+603,3.858,4.555,287972,50,520,970,73,11.9,16,8.7,0,68,0,10,21.7,42.4,2016,5,23
+604,3.915,4.801,313503,50,610,970,65.114,10.9,16,7,0,72,0,10,20.4,42.4,2016,5,24
+605,4.509,5.079,289080,44,380,880,63.93,11.2,15,9,0,81,0,9.2,33.5,57.6,2016,5,25
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+608,3.74,4.804,280345,41,340,800,60.572,7.4,14,1,0,70,0,10,12.2,22.2,2016,5,30
+609,4.16,6.063,297279,45,480,960,64.28,8.8,16,4,0,68,0,10,12.4,20.6,2016,5,31
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+611,4.704,4.832,315064,44,420,840,62.414,9.1,13,6,0,90,0,5.5,7.2,14.8,2016,6,2
+612,4.446,7.225,253529,29,330,700,61.339,11.6,14,7.5,0,90,0,8.4,9.1,22.2,2016,6,5
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+614,4.761,5.065,263832,51,480,820,62.973,11.5,14,8,0,85,0,9.7,18.5,31.7,2016,6,7
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+617,5.929,5.092,246666,49,422.98,845.96,62.942,10.7,15,6,0,71,0,9.7,20.9,31.7,2016,6,10
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+619,3.99,4.962,265425,39,390,740,61.591,9.8,14,7,0,72,0,10,22.8,27.8,2016,6,14
+620,4.239,4.832,167116,50,590,800,62.775,10.7,17,7,0,73,0,10,21.1,46.5,2016,6,15
+621,4.017,4.632,274879,53,520,910,64.477,11.9,14,9.7,0,80,0,10,31.9,48.2,2016,6,16
+622,4.9,5.185,267020,45,660,750,62.397,11.3,12.3,9.9,0,89,0,82,16.3,31.7,2016,6,19
+623,4.77,4.776,202008,39,320,1000,63.664,10.8,12.4,8,0,87,0,8.7,17.6,27.8,2016,6,20
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+625,3.482,4.249,244727,40,330,740,55,11.7,14,9,0,67,0,10,24.4,38.9,2016,6,22
+626,3.417,4.348,219358,17,270,600,53.347,8.8,13,5,0,76,0,9.5,27.6,53.5,2016,6,23
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+628,3.729,3.873,259854,40,300,820,61.198,8,10,5,0,84,0,9.5,18.5,27.8,2016,6,27
+629,3.016,4.152,303367,39,350,780,61.405,10.8,16,7,0,79,0,10,22.2,27.8,2016,6,28
+630,3.842,4.141,303958,28,360,920,63.248,10.8,15,8.5,0,68,0,10,30,48.2,2016,6,29
+631,3.486,3.897,306053,34,370,880,63.248,8.3,10,7,0,82,0,9.5,28.7,55.4,2016,6,30
+632,3.964,3.652,300053,38,300,690,61.24,11.8,16,10,0,68,0,10,24.8,31.7,2016,7,3
+633,2.98,3.768,303266,46,370,845.96,63.091,9.3,12,7,0,81,0,9.8,15.4,24.1,2016,7,4
+634,3.095,4.219,225778,22,370,810,60.229,10.5,12,8,0,93,0,8.4,21.5,33.5,2016,7,5
+635,3.539,4.551,290915,20,310,570,53.394,10.6,12,9.8,0,92,0,6.6,20.6,33.5,2016,7,6
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+637,3.435,4.036,284401,40,340,750,60,11.2,13,11,0,50,0,10,37.2,63,2016,7,10
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+639,3.338,4.07,259123,49,330,710,61.483,6.7,12,3,0,65,0,10,34.8,48.2,2016,7,12
+640,3.334,4.127,248927,45,400,790,61.541,7.8,11,4.9,0,68,0,10,24.6,40.7,2016,7,13
+641,3.348,4.06,306436,40,480,760,62.397,9.7,12.2,7,0,69,0,10,18.7,31.7,2016,7,14
+642,3.221,3.676,233359,43,360,770,62.374,12.4,15,10.6,0,69,0,10,37.4,55.4,2016,7,17
+643,3.079,3.576,270172,44,320,740,61.69,13.8,18,11,0,77,0,10,21.7,38.9,2016,7,18
+644,2.352,5.543,258090,33,640,820,62.622,11.4,15,8,0,85,0,10,6.9,13,2016,7,19
+645,4.751,4.226,189084,34,420,800,60.835,9.9,15,6,0,83,0,9.7,9.8,27.8,2016,7,20
+646,3.804,3.847,239883,32,480,840,64.953,14.7,17.1,12.7,0,82,0,9.5,34.6,57.6,2016,7,21
+647,5.275,4.916,256952,38,320,600,58.331,7.9,11,5.9,0,74,0,10,26.9,40.7,2016,7,24
+648,4.302,4.503,277208,23,500,680,59.994,8.7,13,5,0,65,0,9.7,27.2,57.6,2016,7,25
+649,3.202,3.919,284140,38,310,690,49,8.4,10,7,0,72,0,9.8,26.9,38.9,2016,7,26
+650,3.019,4.544,293102,41,350,660,60.828,8.4,11,6,0,74,0,10,19.3,33.5,2016,7,27
+651,4.755,4.431,275785,34,560,970,64.953,10.8,14,8,0,73,0,10,22.4,31.7,2016,7,28
+652,3.854,4.551,227967,38,330,660,62.023,12.6,16,10.7,0,72,0,9.8,23.3,35.2,2016,7,31
+653,3.377,10.731,334240,20,350,660,58.769,9.2,13,4.8,0,90,0,9.8,18.3,35.2,2016,8,1
+654,6.385,8.471,288778,29,260,470,54.389,9.4,12,8,0,84,0,8.4,18.3,33.5,2016,8,2
+655,6.952,5.107,312292,36,290,620,59.415,7.9,12,3.9,0,87,0.51,92,14.3,31.7,2016,8,3
+656,5.872,5.408,321241,26,320,650,58.612,7.2,13.2,2.8,0,79,0,10,14.3,24.1,2016,8,4
+657,4.489,4.904,323158,31,330,770,60.601,9.2,15,4,0,56,0,10,14.3,31.7,2016,8,7
+658,4.64,4.789,296718,36,330,740,61.496,10.8,13,9,0,64,0,0,46.9,66.5,2016,8,8
+659,4.154,4.438,269276,49,370,870,63.84,12.4,17,8,0,65,0,10,33.3,59.4,2016,8,9
+660,4.627,5.34,294068,32,390,950,62.524,9.4,14,4,0,66,0,10,27.6,48.2,2016,8,10
+661,5.421,5.978,261432,46,260,650,57,9.8,14,5,0,66,0,10,20.2,33.5,2016,8,11
+662,5.365,5.732,271096,43,410,800,62.218,11.9,16,7.9,0,68,0,10,17.2,27.8,2016,8,14
+663,3.536,4.552,262585,38,320,760,62.023,12.2,17,9,0,70,0,10,25.6,40.7,2016,8,15
+664,2.85,3.889,277449,38,480,760,62.622,13.8,18,11,0,67,0,9.8,25.6,38.9,2016,8,16
+665,4.166,4.01,279644,49,400,890,62.942,10.7,15,6,0,81,0,10,16.7,40.7,2016,8,17
+666,4.515,4.008,297691,54,440,880,63.312,16.6,20,14.7,0,58,0,10,39.1,64.8,2016,8,18
+667,4.36,4.521,306766,34,380,660,61.24,10.7,14,8.9,0,78,0,9.8,18.5,27.8,2016,8,21
+668,5.902,13.713,310318,28,340,600,53.295,9.6,15,6,0,86,0,9.8,10.7,27.8,2016,8,22
+669,7.211,14.488,292775,27,350,870,54,7.2,13,2,0,74,0,10,9.8,22.2,2016,8,23
+670,7.322,6.587,235076,32,330,690,61.033,8.1,12,5,0,80,0,10,14.6,22.2,2016,8,24
+671,7.276,5.664,331344,34,440,770,60.563,8.2,13,5,0,76,0,10,17.6,33.5,2016,8,25
+672,7.307,4.992,295867,35,440,760,61.396,11.8,18.3,7,0,66,0,0,24.6,33.5,2016,8,28
+673,6.762,5.535,333187,33,320,800,61.591,13.4,18,9,0,58,0,10,22.2,35.2,2016,8,29
+674,5.175,5.716,342432,34,450,860,63.358,13.3,17,12,0,77,0,10,28,48.2,2016,8,30
+675,4.547,5.638,336331,34,400,860,63.091,14.1,19,9.9,0,70,0,9.8,14.4,31.7,2016,8,31
+676,4.337,5.25,351076,40,510,800,62.397,11.3,15,9,0,90,0,8.5,7.2,20.6,2016,9,1
+677,4.447,5.204,311190,40,450,770,61.591,13.2,16,10,0,67,0,10,16.9,25.9,2016,9,4
+678,4.873,5.404,258255,47,350,780,62.16,13.3,17.3,9,0,70,0,10,13.7,25.9,2016,9,5
+679,4.967,5.208,238691,43,350,800,56,13.2,20,7,0,76,0,10,12,20.6,2016,9,6
+680,4.765,5.846,303346,26,330,840,63.312,15.7,20,13,0,65,0,10,31.7,53.5,2016,9,7
+681,4.805,4.625,314318,30,490,820,62.046,18.1,22,14,0,62,0,9.7,36.1,46.5,2016,9,8
+682,5.799,7.657,311978,23,360,650,59.446,11.6,16,9,0,75,0,8.4,14.6,25.9,2016,9,11
+683,5.798,5.551,342733,40,350,690,61.533,10.3,13,9,0,89,0,7.7,9.3,20.6,2016,9,12
+684,5.285,4.537,267952,23,300,650,60.073,11.6,13,10,0,92,0,8.9,13.1,25.9,2016,9,13
+685,3.318,4.565,253441,18,270,550,53.152,10.2,15,7,0,78,0,9.8,25,40.7,2016,9,14
+686,5.327,5.328,273615,18,270,450,53.152,10.6,14,8,0,81,0,9.5,18.1,44.6,2016,9,15
+687,4.525,5.04,343753,43,330,650,60.7,8.7,11,5,0,85,0,9.8,14.6,24.1,2016,9,18
+688,3.84,4.044,365841,33,450,1000,63.358,10.8,15,7,0,65,0,10,16.1,37,2016,9,19
+689,3.476,4.338,339308,29,370,760,61.396,13.3,18,10,0,64,0,10,21.5,38.9,2016,9,20
+690,3.837,4.346,349075,38,360,720,61.24,9.7,11,9,0,87,0,10,23.2,27.8,2016,9,21
+691,3.948,5.407,358562,32,380,740,55,9.5,12,7,0,80,0,10,14.6,27.8,2016,9,22
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+693,4.303,4.744,327217,28,350,720,58.612,10.2,16,5,0,71,0,9.7,13.7,31.7,2016,9,26
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+700,2.526,7.046,195490,30,360,650,62.023,12.7,19,9,0,71,0,10,23,37,2016,10,5
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+702,7.432,5.804,389808,34,340,590,55.847,15.2,20,11,0,65,0,10,36.7,83.5,2016,10,9
+703,7.113,5.019,395208,26,310,660,58.769,9.1,16,5,0,69,0,9.8,26.1,53.5,2016,10,10
+704,5.651,4.973,322883,18,320,560,53.295,10.8,14,5,0,70,0,10,19.3,40.7,2016,10,11
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+706,4.577,5.492,343520,34,340,760,60.406,9,14.1,2,0,67,0,10,13.3,24.1,2016,10,13
+707,6.556,10.38,339821,29,290,620,48,12.9,21,7,0,74,0,9.5,19.4,37,2016,10,16
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+710,6.71,6.338,273169,29,360,730,62.218,11.1,15,7,0,53,0,0,19.3,53,2016,10,19
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+714,4.052,5.071,343844,26,340,780,59.797,18.9,23,14,0,44,0,0,29.1,50,2016,10,25
+715,4.53,4.725,350836,37,360,1100,66.797,11.3,19,5,0,84,0,9,13,31.7,2016,10,26
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+719,7.366,8.025,312313,34,400,700,51,12.8,18,7,0,66,0,10,14.6,25.9,2016,11,2
+720,6.641,5.822,311909,34,530,690,62.145,13.9,21,8,0,67,0,10,13.3,31.7,2016,11,3
+721,5.979,5.554,317380,42,350,780,61.885,17.3,21,14,0,52,0,10,23.9,51.9,2016,11,6
+722,4.905,4.709,308886,26,300,630,57.086,15.4,25,9,0,61,0,10,21.5,55.4,2016,11,7
+723,3.239,4.335,275366,26,350,720,59.545,13.2,18.3,8,0,62,0,9.8,15,25.9,2016,11,8
+724,2.984,3.993,302033,30,340,770,61.24,13,18,9,0,71,0,10,15.6,24.1,2016,11,9
+725,2.994,4.504,297927,40,350,840,62.257,11.8,18,5,0,72,0,10,12.2,20.6,2016,11,10
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+727,4.587,4.694,306020,37,320,720,61.396,12.6,18,9.8,0,84,0,8.7,28,37,2016,11,13
+728,3.433,3.965,151270,27,260,530,53.106,12.3,17,8.8,0,71,0,10,23.5,37,2016,11,14
+729,3.123,3.676,232501,30,340,720,61.668,13.3,18.1,8.7,0,76,0,10,15.4,25.9,2016,11,15
+730,2.963,3.602,350012,33,340,660,52,15.9,23,11,0,70,0,10,16.5,35.2,2016,11,16
+731,2.981,3.165,349776,37,370,770,61.591,21.9,30,14,0,46,0,8.4,21.3,38.9,2016,11,17
+732,3.01,3.407,272259,31,300,460,54.389,26.3,33.1,21,0,42,0,0,26.1,53.5,2016,11,20
+733,3.015,3.541,295352,37,360,880,64.321,22.4,34.1,13,0,57,0,8.7,20.4,57.6,2016,11,21
+734,2.849,3.572,351523,40,330,910,63.091,12.3,14,10.6,0,90,0,8.4,12,27.8,2016,11,22
+735,2.984,3.851,346530,36,410,820,61.396,10.7,14.1,8,0,75,0,9.7,22.4,38.9,2016,11,23
+736,3.772,4.147,279054,40,470,1100,68.183,12.6,17,9,0,68,0,10,20.4,29.4,2016,11,24
+737,2.949,3.479,265138,44,330,730,61.504,14.2,17,12,0,79,0,9.3,13,20.6,2016,11,27
+738,3.061,3.509,264954,43,440,850,67,14.9,21,10,0,69,0,10,12.2,22.2,2016,11,28
+739,4.01,4.204,261667,39,330,860,63.136,15.4,21,10,0,71,0,9.5,15.6,25.9,2016,11,29
+740,2.958,3.743,306998,40,320,870,63.091,15,19.2,9,0,76,0,10,13.3,24.1,2016,11,30
+741,3.597,4.103,360903,39,340,930,63.155,16.7,24,10.9,0,67,0,10,13,24.1,2016,12,1
+742,5.204,4.975,288576,43,310,750,63.521,23.3,31,15.7,0,50,0,10,28.9,48.2,2016,12,4
+743,5.82,10.091,203027,40,540,1300,68.183,16.2,22,12,0,63,0,10,14.8,27.8,2016,12,5
+744,7.274,13.368,318615,39,490,1200,68.183,14.2,21,8,0,64,0,10,12.2,27.8,2016,12,6
+745,7.373,5.818,321522,44,520,1000,64.477,22.1,28,16,0,31,0,9,25.7,57.6,2016,12,7
+746,5.518,4.608,361701,35,320,680,61.396,14.4,23,8,0,62,0,10,33.2,53.5,2016,12,8
+747,5.368,5.64,324125,46,640,1300,68.183,14.7,27,8,0,66,0,10,14.8,24.1,2016,12,11
+748,5.451,5.124,288885,36,340,950,70,25.7,33,17,0,24,0,0,23,46.5,2016,12,12
+749,3.443,3.998,297419,38,360,900,64.321,24.6,35.2,15,0,34,0,10,25.9,44.6,2016,12,13
+750,3.387,4.042,344684,39,310,940,63.312,14.2,19,9,0,55,0,10,22,33.5,2016,12,14
+751,3.874,4.638,343474,40,340,940,63.155,13.9,23,8,0,62,0,10,19.3,31.7,2016,12,15
+752,4.243,4.371,317555,42,340,760,61.051,13.3,21,5.6,0,50,0,10,20,40.7,2016,12,18
+753,3.538,4.019,289704,40,370,840,63.312,22.9,30,14,0,27,0,8.7,26.1,40.7,2016,12,19
+754,3.785,4.348,334202,40,420,840,63.155,16.4,23,10,0,54,0,10,17.6,29.4,2016,12,20
+755,4.185,4.718,325270,42,550,900,64.477,15.9,20,14,0,61,0,10,21.1,29.4,2016,12,21
+756,4.072,4.405,328625,41,320,950,63.091,16.6,27,12,0,69,0,10,16.5,29.4,2016,12,22
+757,4.073,4.073,296143,42,422.98,845.96,64.164,22.6,32,15,0,53,0,10,13.7,27.8,2016,12,23
+758,4.052,4.51,193270,58,422.98,845.96,63.664,19.4,27.2,17,0,79,0,9.7,12,24.1,2016,12,26
+759,3.256,3.949,198034,50,310,820,61.991,24.1,28,21,0,72,0,9.7,17,48.2,2016,12,27
+760,3.339,3.775,221962,41,540,910,62,30.2,38,26,0,44,0,0,30.9,68.3,2016,12,28
+761,3.727,4.063,249398,26,320,740,61.238,23.8,34,19,0,82,0,8,18,44.6,2016,12,29
+762,3.167,3.966,243256,30,422.98,845.96,63.683,21.2,30,16,0,63,0,10,16.5,27.8,2016,12,30
+763,3.775,4.088,248758,49,260,640,61.76,15.6,18,14,0,72,0,0,20.9,33.5,2017,1,2
+764,3.35,4.002,273805,50,320,790,62.16,17.4,26,15,0,70,0,0,15.4,27.8,2017,1,3
+765,6.518,13.246,315502,38,340,700,61.24,23.7,30,18,0,60,0,0,17.4,27.8,2017,1,4
+766,7.904,18.968,289960,42,330,820,63.169,23.1,33,16,0,60,0,0,15.7,31.7,2017,1,5
+767,7.92,13.169,234544,42,320,740,63.169,21.5,34,17,0,64,0,0,19.4,31.7,2017,1,8
+768,7.913,9.306,273650,39,330,770,62.16,19.5,24,17,0,71,0,0,11.7,18.3,2017,1,9
+769,7.895,6.691,289576,41,380,960,64.32,20.7,29,15,0,63,0,0,16.1,31.7,2017,1,10
+770,7.718,5.659,226540,39,340,830,54,17.9,26,11,0,63,0,0,16.7,37,2017,1,11
+771,7.582,6.369,221330,39,380,920,64.522,22.7,29,18,0,48,0,0,15.2,35.2,2017,1,12
+772,7.387,6.011,208333,49,400,780,62.019,16.7,22,12.7,0,64,0,0,10.7,25.9,2017,1,15
+773,7.477,6.474,210266,37,360,1000,65.374,26,34,19,0,34,0,0,14.3,29.4,2017,1,16
+774,4.182,5.151,257722,46,360,910,65.486,25.1,37.2,14,0,37,0,8.9,19.8,35.2,2017,1,17
+775,2.987,4.138,308029,50,420,1200,67.656,15.7,21,10,0,57,0,51.8,21.7,35.2,2017,1,18
+776,3.119,4.229,330675,37,520,1300,68.82,19.1,25,15,0,61,0,7.7,15.4,38.9,2017,1,19
+777,5.577,6.706,267534,51,270,720,63.393,23.6,31,19,0,58,0,0,13.3,37,2017,1,22
+778,6.693,5.424,258182,46,350,1000,62,26.1,36.4,18,0,45,0,0,21.5,37,2017,1,23
+779,5.975,5.579,307794,36,370,1100,67.656,17,23,10,0,56,0,0,20.9,35.2,2017,1,24
+780,7.04,6.513,290872,55,350,790,61.539,17.9,21.2,16,0,67,0,0,16.7,25.9,2017,1,26
+781,6.926,6.404,254138,55,480,1300,68.82,22.8,28,16,0,55,0,0,17.2,33.5,2017,1,29
+782,5.138,5.337,204002,47,350,820,62.384,21.7,30,15.6,0,55,0,51.8,21.9,51.9,2017,1,30
+783,3.724,4.601,278886,29,460,1000,63.838,17.5,22,12,0,54,0,0,16.1,27.8,2017,1,31
+784,3.624,4.609,285228,45,510,920,65.114,16.4,20.3,10,0,59,0,0,11.9,24.1,2017,2,1
+785,3.479,4.44,291341,47,510,910,65.114,18.2,25,13,0,60,0,0,13.3,31.7,2017,2,2
+786,4.518,5.269,255289,27,770,1300,68.82,25.3,30,19,0,66,0,8.2,20.6,31.7,2017,2,5
+787,5.945,5.635,283990,27,310,610,46,15.4,19,14.6,0,65,0,0,20.7,25.9,2017,2,6
+788,5.292,5.215,277078,38,360,930,64.412,20.3,28,15,0,68,0,0,12.8,42.4,2017,2,7
+789,3.021,4.03,295661,40,360,810,63.051,29.8,35,25,0,40,0,0,43.5,64.8,2017,2,8
+790,3.055,3.994,273697,39,350,670,63.326,22.7,37,16.9,0,71,0,0,19.1,57.6,2017,2,9
+791,5.635,6.172,237793,49,350,810,62.119,15,20,12.9,0,60,0,0,28.5,46.5,2017,2,12
+792,3.532,4.457,264397,45,370,800,62.374,16.2,21,13,0,70,0,0,20.9,35.2,2017,2,13
+793,3.558,4.448,325099,40,490,880,65.114,13.9,22,8,0,68,0,0,15.9,40.7,2017,2,14
+794,4.443,4.629,320327,36,360,920,64.958,22.5,32,16.8,0,46,0,0,21.1,44.6,2017,2,15
+795,4.283,4.488,288086,38,420,990,63.728,17.8,25,11,0,70,0,0,14.1,29.4,2017,2,16
+796,3.007,4.33,287587,42,460,1000,64.523,12.2,17,9,0,73,0,51.5,24.4,38.9,2017,2,19
+797,4.988,5.497,310907,35,330,750,61.396,14.3,21,8,0,62,0,0,19.6,40.7,2017,2,20
+798,4.326,5.284,366068,40,390,930,63.949,17.6,24,11,0,49,0,0,15.2,33.5,2017,2,21
+799,4.285,4.747,349201,41,370,840,66,23.7,33,13,0,34,0,0,23.7,48.2,2017,2,22
+800,5.032,5.844,323395,42,440,950,63.792,19.4,26,15,0,64,0,0,19.3,24.1,2017,2,23
+801,4.421,4.431,305186,46,300,760,61.757,21.6,29,14,0,53,0,0,14.8,44.6,2017,2,26
+802,4.615,5.428,304202,40,410,840,64.801,25.1,33,15,0,36,0,0,15.9,29.4,2017,2,28
+803,4.174,5.128,298728,39,390,1100,67.744,21.8,32.3,12,0,47,0,5.5,11.1,25.9,2017,3,1
+804,3.957,4.711,283244,36,520,940,65.59,20.7,26,17,0,73,0,9.7,18.5,27.8,2017,3,2
+805,3.923,4.222,258740,40,320,790,62.16,20.4,26,17,0,70,0,10,24.3,31.7,2017,3,5
+806,3.694,4.558,240628,38,440,910,64.477,19.1,27,11,0,60,0,10,20.4,37,2017,3,6
+807,4.533,4.342,329796,32,460,1100,67.544,19.3,27,11.8,0,54,0,0,13.7,27.8,2017,3,7
+808,3.36,4.816,256277,35,430,960,65.486,22.4,31,14,0,39,0,0,17,35.2,2017,3,8
+809,3.174,4.521,280493,38,160,1000,68,23.6,32,14,0,36,0,0,12,27.8,2017,3,9
+810,5.469,4.714,318664,29,422.98,845.96,63.728,20.6,27,15.8,0,68,0,10,10.9,22.2,2017,3,10
+811,3.166,3.348,242941,43,310,720,62.16,20.8,26,16,0,73,0,9.8,15.2,27.8,2017,3,13
+812,3.147,4.827,237300,40,550,960,66.354,25.9,32,20.8,0,43,0,0,18.5,40.7,2017,3,14
+813,5.436,6.533,262160,42,520,870,66.354,26.8,34,20,0,43,0,9.7,29.8,48.2,2017,3,15
+814,5.072,4.903,287993,50,600,910,65.59,17.9,23,13,0,66,0,10,20.7,31.7,2017,3,16
+815,4.711,4.894,292123,46,360,820,62.795,25.1,33,18.9,0,42,0,0,13.5,31.7,2017,3,19
+816,3.383,4.404,301248,42,330,850,69,21.9,28.3,18.7,0,83,0,8.4,11.9,29.4,2017,3,20
+817,3.949,4.245,305637,43,350,860,63.728,20.7,27,17,0,89,0,6.9,18.3,29.4,2017,3,21
+818,1.874,4.168,269781,44,440,960,64.412,17.3,21,14,0,83,0,10,23.9,37,2017,3,22
+819,4.805,4.036,271353,58,530,910,65.59,17.4,24,12,0,74,0,10,14.4,27.8,2017,3,23
+820,3.042,4.295,237360,50,520,1100,68.82,22.2,28,19,0,67,0,10,21.1,55.4,2017,3,26
+821,3.746,4.119,252600,41,370,780,62.628,17.1,31,10,0,67,0,9.8,21.9,61.1,2017,3,27
+822,3.172,4.191,250282,46,520,1100,68.82,18.4,24.1,12,0,53,0,10,14.6,27.8,2017,3,28
+823,3.853,4.08,261043,42,200,880,63.995,16.1,27,8,0,58,0,9.2,23.7,46.5,2017,3,29
+824,3.114,4.073,224420,41,420,830,63.995,12.3,18,9,0,67,0,10,17.2,33.5,2017,3,30
+825,3.071,4.069,250990,47,340,1100,71,12.6,0,6,0,62,0,10,22,33.5,2017,4,2
+826,4.878,4.137,263371,43,520,920,65.114,14.1,21,7,0,61,0,10,10.4,16.5,2017,4,3
+827,4.275,4.058,240560,48,530,880,65.114,16.8,25,10,0,48,0,0,14.4,29.4,2017,4,4
+828,4.446,4.091,242268,43,440,920,63.995,18,25,12,0,43,0,0,20.2,33,2017,4,5
+829,3.116,6.464,260517,48,370,980,63.995,19.1,26,11.9,0,36,0,0,19.8,35.2,2017,4,6
+830,5.465,4.703,258211,42,270,760,61.69,11.2,13,9,0,87,0,7.6,27,44.6,2017,4,9
+831,5.964,6.066,284125,39,230,680,61.885,12.2,14,10.9,0,55,0.25,9.8,23,40.7,2017,4,10
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+867,5.137,4.552,297041,42,330,820,60.7,9.4,15,5,0,73,0,10,11.5,22.2,2017,6,4
+868,4.107,4.847,279777,45,320,840,63.091,11.4,17,7.7,0,77,0,10,18.5,24.1,2017,6,5
+869,5.056,4.868,182092,44,310,780,61.285,9.2,12,5.8,0,77,0,10,15,37,2017,6,6
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+888,5.134,5.889,315481,49,300,830,63.248,10.1,12,8,0,79,0,9.8,24.8,37,2017,7,3
+889,4.324,5.898,195683,37,240,860,63.664,12,16,9,0,75,0,1,18.5,25.9,2017,7,4
+890,4.756,4.74,313468,30,320,910,62.257,8.7,14,3,0,74,0,1,17.4,24.1,2017,7,5
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+899,3.523,4.592,314661,50,340,1100,66.954,9.8,14,7,0,77,0,1,21.1,33.5,2017,7,18
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+904,3.828,4.511,312083,43,350,1000,56,12.1,17,9,0,65,0,10,25.7,46.5,2017,7,25
+905,3.376,4.287,315783,36,290,920,62.414,8.3,15,4,0,79,0,10,20.6,37,2017,7,26
+906,5.025,4.619,324973,37,370,920,62.414,9.9,12,6,0,76,0,10,28.2,50,2017,7,27
+907,3.407,3.668,239882,40,220,830,63.052,9.6,17,3,0,62,0,1,16.3,35.2,2017,7,30
+908,4.242,4.646,288137,37,300,800,60.406,7.7,15,3,0,72,0,10,12,20.6,2017,7,31
+909,2.986,3.847,298435,37,270,870,62.257,7.4,14,2,0,78,0,6.8,8.3,14.8,2017,8,1
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+912,3.732,3.903,282028,40,330,920,62.414,8.4,12,6,0,74,0,0,24.3,37,2017,8,6
+913,3.663,4.162,285242,37,320,820,60.563,7.7,12,5,0,82,0,0,21.7,35.2,2017,8,7
+914,3.712,4.098,284836,36,330,820,60.406,10.6,14.1,6,0,73,0,0,18.1,21.8,2017,8,8
+915,4.215,4.109,212253,38,360,800,62.023,12.3,16,10,0,69,0,0,45.9,74.1,2017,8,9
+916,5.005,3.566,312287,40,330,830,68,12.9,18,7.7,0,54,0,0,27.6,66.5,2017,8,10
+917,4.044,5.16,292451,34,300,750,61.591,13.9,18,11.6,0,52,0,0,39.4,53.5,2017,8,13
+918,4.164,5.036,264278,41,320,850,63.358,13.7,19,9,0,59,0,0,29.6,51.9,2017,8,14
+919,3.815,4.256,338322,41,350,900,63.248,13.9,17,9.7,0,70,0,0,27.6,55.4,2017,8,15
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+921,3.901,4.306,352555,31,340,870,62.479,9.3,15,5,0,67,0,0,26.5,46.5,2017,8,17
+922,3.783,4.241,320506,30,260,740,60.563,8.5,13,6,0,61,0,0,13.5,33.5,2017,8,20
+923,4.445,4.086,297794,93,320,800,60.735,8.3,12,4,0,71,0,0,20.6,21.8,2017,8,21
+924,4.013,4.607,325069,40,340,850,60,11.9,17,7,0,63,0,0,11,24.1,2017,8,22
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+926,4.582,4.219,315745,32,300,780,60.406,7.8,13.1,3,0,77,0,0,14.8,31.1,2017,8,24
+927,5.545,4.341,314119,27,250,660,58.769,5.8,9.2,3,0,80,0,0,18.3,46.5,2017,8,27
+928,4.123,5.25,288283,42,310,740,60.765,7.1,11,3,0,79,0,0,10.2,18.3,2017,8,28
+929,4.403,5.395,289394,42,330,820,60.572,8.8,12,4,0,70,0,0,11.9,24.1,2017,8,29
+930,4.579,4.552,306590,45,370,970,62.257,7,12,1,0,77,0,9.8,13.5,27.8,2017,8,30
+931,4.232,4.563,282173,30,360,950,62.849,7.7,14,2,0,66,0,0,14.1,29.4,2017,8,31
+932,4.54,4.604,281519,36,360,980,63.84,11.2,15,7,0,59,0,10,24.3,40.7,2017,9,3
+933,4.667,4.57,293503,40,460,1000,62.524,7.5,13,4.9,0,56,0,10,30.9,57.6,2017,9,4
+934,5.432,4.641,319247,36,380,930,70,7.8,13,4.8,0,65,0,9.7,29.8,50,2017,9,5
+935,4.573,5.237,254582,30,370,920,62.942,9.6,15,5,0,73,0,10,21.3,38.9,2017,9,6
+936,5.162,5.288,337212,42,420,1000,62.414,10.1,15,6.8,0,75,0,9.8,23.5,37,2017,9,7
+937,4.531,5.459,313190,38,330,830,63.312,11.4,16,8,0,63,0,10,21.5,53.5,2017,9,10
+938,4.261,4.805,326101,43,340,880,63.312,14.3,17,11,0,62,0,10,30.2,50,2017,9,11
+939,4.193,4.646,370055,48,340,940,63.248,14.7,20,9,0,72,0,10,19.1,33.5,2017,9,12
+940,4.188,4.488,304270,27,350,890,62.414,8.5,15,4,0,70,0,10,27.8,44.6,2017,9,13
+941,4.338,4.591,304934,31,480,910,64.477,11.3,14,9,0,67,0,10,22.6,37,2017,9,14
+942,3.815,4.661,321835,24,320,730,59.797,12.7,18,9,0,44,0,0,37,64.8,2017,9,17
+943,4.103,4.4,346073,32,360,920,63.312,13.4,21.2,7,0,49,0,10,31.9,61.1,2017,9,18
+944,3.282,4.161,371725,29,380,1300,67.019,9.3,14,4.9,0,64,0,10,20,35.2,2017,9,19
+945,4.46,4.562,236862,31,480,1100,68.183,14.1,19,11,0,53,0,0,32.8,55.4,2017,9,20
+946,4.314,4.16,301200,35,422.98,845.96,63.312,15.4,23,10,0,60,0,10,20.9,51.9,2017,9,21
+947,4.512,4.208,326495,41,380,860,63.312,14.3,19,9,0,53,0.25,9.2,29.1,57.6,2017,9,24
+948,4.11,5.036,262565,38,422.98,845.96,62.942,8.2,13.4,2,0,78,0,10,17,35.2,2017,9,25
+949,3.587,4.608,320429,40,422.98,845.96,63.312,11.5,16,8,0,56,0,10,10.6,37,2017,9,26
+950,4.898,4.362,339197,38,520,860,64.477,15.7,24,7.5,0,47,0,10,20.2,51.9,2017,9,27
+951,4.525,4.288,233792,46,422.98,845.96,63.84,13.2,17,9,0,52,0,10,25,40.7,2017,9,29
+952,4.324,5.333,283684,50,400,970,62.785,11.9,17,6,0,75,0,9.5,13.3,24.1,2017,10,1
+953,3.803,4.696,274785,45,450,1000,62.895,10.5,19,4,0,73,0,10,11.3,20.6,2017,10,2
+954,4.415,4.341,259801,44,330,900,66,13.3,23,5.5,0,60,0,10,13,24.1,2017,10,3
+955,3.418,4.512,303702,41,380,1000,63.155,20.6,26,17,0,38,0,0,19.5,29.4,2017,10,4
+956,4.603,4.335,343694,44,420,900,63.312,13.1,20,8.6,0,65,0,10,29.3,50,2017,10,5
+957,5.155,4.269,342413,44,320,840,63.312,18.3,25,13,0,66,0,9.8,35,64.5,2017,10,8
+958,4.931,4.901,341127,44,480,845.96,63.643,12.4,19.2,5,0,60,0,10,18.1,40.7,2017,10,9
+959,4.021,5.469,256975,41,480,920,64.953,14.2,20,7,0,49,0,10,15.4,55.4,2017,10,10
+960,4.792,4.816,375692,41,410,880,63.312,14.5,24,7.8,0,61,0,9.7,29.3,63,2017,10,11
+961,4.057,4.551,339797,38,320,790,60.758,13.9,18,5,0,56,0,10,18.1,35.2,2017,10,12
+962,3.729,4.736,298750,44,320,690,55,13.9,23,9,0,73,0,9,11.3,27.5,2017,10,15
+963,4.303,4.426,303516,41,330,900,63.312,20.3,28.1,12.5,0,51,0,0,18.7,38.9,2017,10,16
+964,4.036,4.349,334167,41,370,1000,63.312,21.5,30,12,0,37,0,0,24.6,51.9,2017,10,17
+965,4.179,4.285,279218,40,440,900,63.84,24.7,30,19,0,41,0,10,31.1,46.5,2017,10,18
+966,4.129,4.487,285873,48,350,930,62.942,14.9,25,5,0,73,0,9.7,19.1,38.9,2017,10,19
+967,4.144,4.352,314317,39,400,850,63.091,13.2,16,10,0,75,0,10,15.9,24.1,2017,10,22
+968,4.491,4.167,331802,34,420,850,63.091,14.5,20,9,0,70,0,10,10.2,27.5,2017,10,23
+969,3.267,4.355,293425,37,350,880,63.091,15.5,22,12.7,0,77,0,7.9,10.7,25.9,2017,10,24
+970,3.003,4.241,180460,35,360,770,61.668,13.9,17,11,0,82,0,92,15.4,25.9,2017,10,25
+971,4.127,4.407,304905,45,410,830,63.155,13.5,20,12,0,50,0,10,17.5,29.4,2017,10,26
+972,3.897,4.277,276256,47,340,860,63.84,17.6,28.3,7,0,42,0,9.3,32,57.6,2017,10,29
+973,4.046,4.245,277247,33,340,910,62.942,9.6,15.2,5,0,71,0,10,18.5,42.4,2017,10,30
+974,3.968,4.193,275270,50,320,780,62.032,13,16,11.6,0,66,0,10,16.7,25.9,2017,10,31
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+976,3.929,4.386,284899,50,470,1000,64.477,11.3,15,8,0,72,0,0,14.1,33.5,2017,11,2
+977,3.049,4.039,237365,52,330,850,63.729,12.1,18,8,0,59,0,0,18.3,29.4,2017,11,5
+978,4.55,3.963,224424,78,330,810,62.547,12.3,15,8.7,0,54,0,0,21.5,33.5,2017,11,7
+979,3.678,3.925,212952,53,460,960,63.774,12.8,18,8,0,71,0,0,11.9,24.1,2017,11,8
+980,5.485,4.036,230159,52,400,940,63.729,15.3,22,10,0,67,0,9.8,13.5,25.9,2017,11,9
+981,4.606,4.211,265386,36,330,950,63.683,19.1,27,11,0,61,0,8.7,13.1,27.8,2017,11,12
+982,4.37,5.706,270370,46,550,1100,68.183,25.4,33,17,0,34,0,0,22,51.9,2017,11,13
+983,4.212,4.506,263309,41,480,1000,65.717,27.6,34,22,0,27,0,0,30.6,51.9,2017,11,14
+984,3.82,5.062,302874,42,440,890,58,21.2,31,16.5,0,62,0,6.8,18.3,51.9,2017,11,15
+985,4.704,4.314,320313,38,350,860,63.091,18.3,23,15,0,83,0,0,14.4,25.9,2017,11,16
+986,3.238,4.197,262783,41,340,900,63.84,21.7,28.1,14.6,0,57,0,0,19.3,37,2017,11,19
+987,3.87,4.198,280668,40,290,900,64.849,23.8,31,14.6,0,47,0,0,19.6,33.5,2017,11,20
+988,3.926,4.258,283348,45,360,1100,67.315,25.1,32,16,0,38,0,0,17,35.2,2017,11,21
+989,3.001,4.231,275802,38,430,940,64.849,23.6,32.4,12,0,33,0,0,16.9,38.9,2017,11,22
+990,4.186,4.444,292177,43,380,890,64.321,24.8,33.1,16,0,39,0,0,19.1,40.7,2017,11,23
+991,2.759,4.161,285816,49,300,870,63.619,19.8,27.5,15,0,78,0.25,8.4,14.8,31.7,2017,11,26
+992,5.087,4.317,284670,50,430,840,53,16.3,22,11,0,73,0,0,14.6,29.4,2017,11,27
+993,4.351,4.398,293724,42,350,890,63.312,24.7,30,18,0,53,0,0,18,44.6,2017,11,28
+994,3.883,4.154,323670,42,360,950,64.321,28.7,35,21,0,37,0,0,23.5,48.2,2017,11,29
+995,3.761,4.253,357342,45,470,1100,68.183,25.7,35.1,20,0,53,0,0,23.2,40.7,2017,11,30
+996,3.935,4.081,328661,13,140,360,53.053,13,15.2,11,0,77,0,9,22.2,37,2017,12,3
+997,3.499,4.366,303007,29,280,590,54.531,13.3,17,10,0,76,0,10,16.5,31.7,2017,12,4
+998,3.921,4.201,352520,29,340,840,63.091,16.5,22,12,0,72,0,10,15.6,31.7,2017,12,5
+999,5.019,4.169,367629,39,350,740,61.533,15.3,22,9.7,0,72,0,10,12.8,25.9,2017,12,6
+1000,5.735,3.977,364181,30,290,650,61.24,15.3,23,9,0,71,0,9.3,17,27.8,2017,12,7
+1001,6.099,9.41,393338,38,360,770,61.24,17.6,23,13,0,67,0,10,14.6,25.9,2017,12,10
+1002,6.015,11.354,331550,33,270,710,54,17.5,21,15,0,64,0,10,15.7,25.9,2017,12,11
+1003,6.007,9.082,350111,35,610,900,65.241,20.8,31,13,0,53,0,10,16.9,38.9,2017,12,12
+1004,5.941,8.745,344578,46,350,820,62.894,28.8,37,20.5,0,23,0,0,24.3,44.6,2017,12,13
+1005,5.059,7.54,341039,36,300,780,61.24,18,24,13,0,65,0,10,17,29.4,2017,12,14
+1006,4.767,6.202,330513,36,340,820,61.24,19.8,25,15,0,72,0,10,14.8,22.2,2017,12,17
+1007,4.758,5.225,319609,32,420,890,64.321,28.7,33,25,0,31,0,0,17,37,2017,12,18
+1008,4.757,5.219,316913,27,360,860,64.321,22.6,38,15,0,56,0,10,22.4,55.4,2017,12,19
+1009,4.67,5.184,322943,27,330,800,59.702,16.2,24,10,0,64,0,10,17.8,33.5,2017,12,20
+1010,4.521,4.697,315431,36,300,860,63.683,18.1,24.1,12,0,63,0,10,12.8,27.8,2017,12,21
+1011,5.411,4.881,269519,37,422.98,845.96,64.849,21.3,31,14,0,47,0,9.3,17.4,33.5,2017,12,23
+1012,4.099,5.369,269727,46,490,810,63.04,23.9,30,17,0,45,0,0,23.2,51.9,2017,12,26
+1013,3.863,4.927,295216,27,290,570,47,28.6,34,23,0,35,0,10,22.2,40.7,2017,12,27
+1014,4.348,4.393,272602,28,290,680,61.192,21.8,32,18,0,70,0,9.8,14.4,38.9,2017,12,28
+1015,4.77,4.176,261361,29,422.98,845.96,63.775,18.2,24,13,0,83,0,9.5,12.6,35.2,2017,12,29
+1016,3.952,4.995,294830,33,280,770,61.866,19.3,26,16,0,59,0,10,17.2,31.7,2018,1,1
+1017,3.683,4.721,264043,35,320,750,61.866,17.2,23,11,0,62,0,10,20.9,31.7,2018,1,2
+1018,3.666,4.322,228976,45,500,880,65.59,17.2,22,12,0,58,0,10,16.3,27.8,2018,1,3
+1019,4.748,3.857,240676,46,670,940,65.59,18.4,24,12,0,65,0,10,12.2,25.9,2018,1,4
+1020,4.083,4.434,281666,39,410,1100,67.486,18.2,21,16,0,74,0,10,13.7,22.2,2018,1,7
+1021,3.66,4.897,263358,47,340,900,64.32,18.7,23,14,0,66,0,10,16.3,24.1,2018,1,8
+1022,3.597,4.263,247567,44,540,970,65.59,17,22,12,0,61,0,10,23.5,35.2,2018,1,9
+1023,5.034,4.023,200216,29,530,890,56,19.7,28,13.9,0,58,0,0,11.9,20.6,2018,1,10
+1024,4.405,4.066,266754,37,360,920,65.486,29.6,35,25,0,26,0,10,22.4,46.5,2018,1,11
+1025,4.091,5.283,219748,32,270,650,61.668,15.9,19,13,0,62,0,9.8,21.1,31.7,2018,1,14
+1026,4.701,4.745,291562,40,330,1100,67.591,16.4,21,11,0,72,0,10,19.1,33.5,2018,1,15
+1027,3.927,4.764,232473,47,340,950,64.32,18.5,26,11,0,59,0,10,16.5,31.7,2018,1,16
+1028,3.747,4.695,243517,38,580,930,66.354,23.6,32,15.5,0,36,0,0,18,42.4,2018,1,17
+1029,4.77,4.3,255588,50,490,990,66.354,32,39,22,0,16,0,0,25.2,46.5,2018,1,18
+1030,6.02,4.029,241014,56,300,780,62.195,23.9,29,18.8,0,68,0,6.9,10.7,20.6,2018,1,21
+1031,5.325,6.195,227807,36,300,790,56,20.6,26,17,0,66,0,10,17.2,29.4,2018,1,22
+1032,4.198,5.502,251943,37,370,910,64.32,19.1,25,13,0,65,0,10,15,29.4,2018,1,23
+1033,4.092,5.355,262035,45,420,920,64.32,20,25,16,0,67,0,10,15.4,27.8,2018,1,24
+1034,4.118,4.419,255015,30,422.98,845.96,65.265,22.9,31,20,0,82,0,5.6,12.8,31.7,2018,1,26
+1035,3.937,4.301,246633,35,350,750,63.227,32.1,38,26.9,0,39,0,0,35.7,57.6,2018,1,28
+1036,4.07,4.142,311694,33,290,810,62.405,21.3,33,14,0,76,0,6.9,23.3,53.5,2018,1,29
+1037,4.132,4.196,315479,20,230,550,53.053,15.3,19,12,0,60,0,10,26.5,38.9,2018,1,30
+1038,3.657,4.174,300483,30,330,810,61.591,14.6,19,9,0,52,0,9.8,26.1,38.9,2018,1,31
+1039,3.006,4.702,307393,49,370,820,61.748,17.3,22,13,0,60,0,10,19.6,37,2018,2,1
+1040,5.868,4.204,281575,44,360,820,62.218,20.8,27,15,0,61,0,10,13.1,24.1,2018,2,4
+1041,4.663,4.444,254419,37,400,800,65,21.1,27,16,0,65,0,10,14.4,25.9,2018,2,5
+1042,6.044,5.409,256599,34,490,920,66.354,23.3,31,15.6,0,56,0,0,13.5,35.2,2018,2,6
+1043,5.547,9.911,198060,31,360,850,65.531,28.1,37,20,0,37,0,0,18.1,33.5,2018,2,7
+1044,5.054,8.081,283600,51,340,890,63.728,22.8,29,19,0,68,0,10,15.2,29.4,2018,2,8
+1045,5.311,6.128,267864,45,610,880,65.59,17.4,22,14.7,0,54,0,10,21.1,33.5,2018,2,11
+1046,4.067,5.761,248735,47,640,1700,68.82,17.6,23,11,0,59,0,10,13.3,24.1,2018,2,12
+1047,4.188,5.629,229126,40,400,1000,64.477,23.8,29.4,17,0,33,0,10,19.8,57.6,2018,2,13
+1048,4.381,5.039,314438,41,550,1000,65.114,16.8,24,9.7,0,40,0,0,23.5,51.9,2018,2,14
+1049,5.264,5.003,300011,39,600,990,65.114,18.7,23.3,13,0,54,0,10,18.7,29.4,2018,2,15
+1050,4.438,4.591,264966,48,340,910,64.256,19.7,26,17,0,72,0,10,19.4,27.8,2018,2,18
+1051,5.71,4.729,272804,50,640,1200,68.82,18.3,26,11.7,0,68,0,10,23.7,44.6,2018,2,19
+1052,5.895,4.658,319073,43,490,920,65.114,21.3,29,14,0,48,0,10,18.5,55.4,2018,2,20
+1053,4.339,7.958,314252,39,350,1100,65,23.1,29,18.7,0,46,0,0,16.7,53.5,2018,2,21
+1054,3.891,5.295,299886,41,330,1100,67.499,23.8,28,19.8,0,60,0,10,11.9,27.8,2018,2,22
+1055,4.05,4.402,301713,50,350,910,63.949,15.4,19,10.7,0,66,0,10,26.1,38.9,2018,2,25
+1056,4.961,4.474,310462,43,310,950,63.949,19.6,26,12.7,0,57,0,0,17,44.6,2018,2,26
+1057,3.551,4.63,288529,38,340,780,62.6,25.2,31,19,0,33,0,0,28.3,55.4,2018,2,27
+1058,5.497,4.406,279514,38,340,900,64.958,20.3,31,15,0,50,0,10,28.5,46.5,2018,2,28
+1059,7.384,3.997,346468,38,340,800,61.24,17.2,21,14.6,0,73,0,10,17,29.4,2018,3,1
+1060,6.032,14.551,318847,46,360,1000,63.792,16.6,21,13,0,55,0,10,19.8,29.4,2018,3,4
+1061,6.625,12.652,294423,38,260,740,60,16.1,20,10.5,0,60,0,10,25.4,35.2,2018,3,5
+1062,6.399,8.021,340930,45,370,980,63.792,18.3,26,11,0,56,0,0,14.1,29.4,2018,3,6
+1063,0.143,6.693,253080,40,360,860,63.995,21.7,30,13.7,0,46,0,0,18.1,33.5,2018,3,7
+1064,0.028,5.869,339219,38,380,940,64.801,21.6,31,12,0,46,0,0,14.3,27.8,2018,3,8
+1065,2.331,4.522,332643,48,422.98,845.96,64.801,21.9,31,13,0,42,0,0,14.3,25.9,2018,3,9
+1066,2.013,4.192,320902,43,340,860,63.949,16.6,20,13,0,64,0,10,21.1,33.5,2018,3,12
+1067,2.056,4.181,297998,38,330,810,61.24,16.7,21.3,13,0,64,0,10,15.7,29.4,2018,3,13
+1068,4.443,4.146,312583,39,360,800,61.591,16.9,22,13,0,65,0,10,11.7,22.2,2018,3,14
+1069,7.102,4.751,284939,68,350,840,63.728,15.8,21,11,0,69,0,10,13.9,25.9,2018,3,15
+1070,6.607,4.805,303374,49,360,890,63.949,16.8,22,11,0,34,0,10,26.7,53.5,2018,3,18
+1071,6.809,5.435,280064,43,310,760,61.728,19.4,28,14.7,0,52,0,10,18.9,31.7,2018,3,19
+1072,5.589,5.339,323207,52,540,1500,68.82,14.1,18,9,0,55,0,10,26.3,40.7,2018,3,20
+1073,7.695,5.607,256047,45,400,1200,78,16.8,26,10,0,56,0,0,12.6,27.8,2018,3,21
+1074,5.749,7.645,299212,47,510,1300,68.82,21.1,28,15,0,42,0,0,17.8,42.4,2018,3,22
+1075,5.438,6.917,326326,38,600,960,65.114,16,25,9,0,50,0,9.3,32,44.6,2018,3,25
+1076,5,5.122,386087,43,350,940,63.949,12.7,19,7.9,0,65,0,10,23.7,40.7,2018,3,26
+1077,5.05,5.755,383882,40,340,960,63.949,19.1,23,15.6,0,38,0,0,30.4,53.5,2018,3,27
+1078,4.303,5.38,385023,46,340,920,63.949,20.2,30,15,0,54,0,10,16.9,35.2,2018,3,28
+1079,4.026,4.686,304303,41,422.98,845.96,63.792,16.9,24,11,0,64,0,10,14.3,27.8,2018,3,30
+1080,4.742,4.535,316841,49,340,890,63,16.2,21,11,0,66,0,10,14.3,24.1,2018,4,2
+1081,4.662,4.602,345170,51,330,930,63.792,15.8,20,12,0,66,0,10,10.4,18.3,2018,4,3
+1082,3.057,4.841,361080,43,360,1100,67.434,16.2,23,12,0,72,0,10,10.6,22.2,2018,4,4
+1083,4.95,4.885,373131,46,360,1000,63.728,15.6,20,12,0,73,0,10,9.8,22.2,2018,4,5
+1084,4.661,4.14,343579,50,330,880,63.949,21.9,30.1,12.7,0,38,0,0,17.8,46.5,2018,4,8
+1085,3.026,5.372,335682,38,370,1100,67.656,19.3,26,13,0,56,0,10,15,53.5,2018,4,9
+1086,4.406,4.266,329495,39,422.98,845.96,63.949,22.7,28,17,0,44,0,10,22.8,38.9,2018,4,10
+1087,4.034,4.125,224909,49,370,920,64.522,21.4,30,15.4,1010.5,53,0.25,11.6,16.7,35,2018,4,11
+1088,5.863,4.225,302386,35,460,1100,67.544,17.6,28,10,0,54,0,10,16.7,27.8,2018,4,12
+1089,4.848,8.777,269376,39,310,840,64.412,16.5,20,14.8,0,70,0,10,23.2,44.6,2018,4,15
+1090,4.499,6.299,218684,41,300,980,63.995,14.8,22,11,0,62,0,10,24.3,40.7,2018,4,16
+1091,3.961,5.247,168264,50,350,940,62.94,10.1,16,3.7,0,68,0,10,13.7,25.9,2018,4,17
+1092,3.035,4.69,173441,34,710,1500,77,14.3,23.2,9,0,63,0,0,13.5,29.4,2018,4,18
+1093,4.166,4.217,179307,43,410,990,63.838,14,24,7,0,60,0,9.8,11.3,22.2,2018,4,19
+1094,3.032,3.982,180832,46,320,810,61.504,14.7,23,7.8,0,80,0,6,8.5,16.5,2018,4,22
+1095,3.049,3.78,303770,43,360,880,63.949,21.6,28,14,0,35,0,0,28.2,46.5,2018,4,23
+1096,4.402,3.494,302053,52,370,870,63.728,14.9,21,9,0,71,0,10,13,22.2,2018,4,25
+1097,3.039,4.384,319048,39,460,940,63.838,12.8,18,8,0,71,0,10,13.1,27.8,2018,4,26
+1098,3.398,4.035,263403,44,340,710,62.032,12.2,18,8,0,81,0,10,12,24.1,2018,4,29
+1099,3.065,3.979,306663,40,340,820,60.766,12.6,20,6,0,57,0,10,13,24.1,2018,4,30
+1100,3.709,3.74,319098,40,310,850,54,17.9,23,13,0,32,0,0,22.6,35.2,2018,5,1
+1101,4.915,3.684,313327,40,350,670,61.885,15.1,23,14.6,0,40,0,0,27.4,48.2,2018,5,2
+1102,3.73,4.255,288646,45,490,880,65.114,17.2,25,10,0,48,2.03,9.7,25.9,50,2018,5,3
+1103,3.821,4.899,302958,50,350,1100,67.656,14.9,20.1,10,0,60,0,10,18.5,46.5,2018,5,6
+1104,4.228,4.14,296588,46,350,1000,63.949,15.6,19,11,0,53,0,10,22,37,2018,5,7
+1105,4.043,3.954,291266,50,490,1200,68.82,11.5,15,7,0,70,0,10,13.9,24.1,2018,5,8
+1106,3.082,4.653,330347,39,500,1300,68.82,12.9,15,6.5,0,60,0,9.2,21.5,35.2,2018,5,9
+1107,3.087,3.927,370243,43,340,950,61.118,5.5,12,6,0,77,0,5.5,24.5,46.2,2018,5,10
+1108,4.354,3.758,236521,50,300,790,60.994,11.1,16,6,0,54,0,9,15,27.8,2018,5,13
+1109,3.058,3.816,260440,18,350,850,62.94,11.3,15,5,0,79,0,10,10.7,18.3,2018,5,14
+1110,4.155,4.301,269052,29,340,920,68,10.1,14,7,0,50,1.02,9.5,15.9,35.2,2018,5,15
+1111,3.062,4.19,262713,41,360,900,64.32,10.7,13,9,0,67,0,10,14.3,20.6,2018,5,16
+1112,3.074,3.741,268245,50,360,960,64.256,12.7,14,11,0,79,0,10,14.4,27.5,2018,5,17
+1113,4.045,3.675,309405,40,340,770,61.533,13.5,16,10,0,77,0,9.7,21.5,31.7,2018,5,20
+1114,3.028,3.745,293593,42,380,790,61.69,13.3,15,11.8,0,76,0,10,22,31.7,2018,5,21
+1115,3.68,3.884,311403,36,350,1000,63.792,12.9,16,10,0,56,0,9.7,18.1,31.7,2018,5,22
+1116,3.841,3.679,232384,35,340,930,64.301,12.7,14,11.7,0,74,0,10,16.3,27.5,2018,5,23
+1117,2.961,3.966,342567,41,350,1100,67.434,12.4,15.1,10,0,73,0,10,12.2,25.9,2018,5,24
+1118,2.972,3.864,296912,50,260,720,49,15.8,20,13.6,0,57,0,10,31.7,44.6,2018,5,27
+1119,3.658,3.709,304357,48,310,810,61.757,15.9,21,12,0,54,0,10,34.5,46.5,2018,5,28
+1120,2.953,3.639,270284,45,320,920,63.643,10.7,16,5,0,66,0,10,16.1,37,2018,5,29
+1121,3.968,3.675,255398,40,370,970,63.532,11.1,15,5,0,66,0,10,22.5,29.4,2018,5,30
+1122,2.963,3.609,271012,27,340,900,62.94,7.8,14,3,0,75,0,10,13.7,31.7,2018,5,31
+1123,4.112,4.046,252658,38,320,400,58.089,9.1,13,5,0,87,0,9.8,10.9,14.8,2018,6,3
+1124,3.688,3.925,259956,31,430,1100,66.849,10.8,14.1,8.8,0,85,0,9.7,10.4,16.5,2018,6,4
+1125,3.513,4.175,276357,27,430,980,63.091,11.3,15,7,0,81,0,10,10,16.5,2018,6,5
+1126,4.182,3.957,293012,34,390,1000,63.312,12.8,18,7,0,61,0,10,21.3,46.5,2018,6,6
+1127,2.974,3.857,255255,35,430,1200,67.07,14.2,16,12,0,61,0,10,36.3,57.6,2018,6,7
+1128,3.485,3.788,238215,38,422.98,845.96,63.775,11.4,13,9,0,86,0,10,19.1,37,2018,6,8
+1129,3.539,3.677,227780,41,330,910,63.821,12.6,16,10,0,70,0,10,36.3,48.2,2018,6,11
+1130,2.987,3.838,176208,34,330,930,63.821,11.3,15,7,0,73,0,10,21.7,38.9,2018,6,12
+1131,3.053,4.057,328442,31,300,1100,66.954,9.6,13,7,0,77,0,10,22.6,35.2,2018,6,13
+1132,4.417,3.852,360953,29,410,800,52,11,13,9,0,68,0,10,31.9,55.4,2018,6,14
+1133,2.985,3.162,312384,23,240,560,53.295,9.3,12,8,0,93,0,8.7,26.1,44.6,2018,6,17
+1134,3.522,4.009,337634,29,300,720,60.406,6.3,11,1.9,0,89,0,9.5,10.2,20.6,2018,6,18
+1135,3.691,3.94,295037,42,340,790,60.7,7.4,13,3,0,76,0,10,13,29.4,2018,6,19
+1136,3.555,3.663,334475,38,320,780,60.406,8,14,3,0,75,0,10,18.9,29.4,2018,6,20
+1137,3.017,3.801,280133,33,320,970,62.257,8,15,3,0,71,0,10,13.9,22.2,2018,6,21
+1138,3.674,3.864,267323,35,320,790,61.033,9.1,12,6,0,67,0,10,12.2,24.1,2018,6,24
+1139,3.038,3.727,241117,30,340,1000,63.136,9.6,12,8,0,80,0,10,4.3,13,2018,6,25
+1140,3.798,3.698,241714,45,450,790,56,7.8,14,3,0,86,0,7.4,8,14.8,2018,6,26
+1141,3.889,3.726,274864,46,560,1000,63.643,6.8,13,2.5,0,88,0,4.2,7,13,2018,6,27
+1142,3.048,4.255,258832,38,550,890,64.12,8.2,10,5,0,88,0,9.2,14.3,35.2,2018,6,28
+1143,3.076,3.738,197054,36,340,870,62.83,7.1,14,2,0,74,0,10,15.4,24.1,2018,7,1
+1144,4.54,4.004,196853,41,360,1100,67.115,9.1,14,6,0,67,0,10,29.1,57.6,2018,7,2
+1145,1.743,3.106,222667,38,420,1000,62.987,10.8,14,5.4,0,68,0,10,38.7,53.5,2018,7,3
+1146,5.076,4.353,219809,32,500,1100,68.183,12.9,16,9.1,0,62,0,10,49.1,63,2018,7,4
+1147,2.989,3.657,225159,47,590,1200,68.183,14.4,18,9,0,57,0,10,30,53.5,2018,7,5
+1148,3.725,3.851,259038,53,320,820,65,10.5,13,8,0,77,0,9.5,27,44.6,2018,7,8
+1149,2.981,3.788,257045,54,290,930,62.303,9.6,13,6,0,73,0,10,15.4,27.8,2018,7,9
+1150,3.863,3.785,263663,54,270,920,62.524,8.1,11,4.9,0,66,0,10,15.9,40.7,2018,7,10
+1151,6.021,3.87,249311,52,350,960,62.987,6.7,10,2.7,0,76,0,10,14.6,38.9,2018,7,11
+1152,5.055,3.977,261481,52,330,930,62.849,7.9,12,6,0,55,0,10,9.6,13,2018,7,12
+1153,3.558,6.92,210059,53,320,850,63.052,8.5,12,6,0,60,0,10,40.2,53.5,2018,7,15
+1154,5.485,4.721,239570,46,330,830,63.052,9,13,6,0,61,0,10,37.2,51.9,2018,7,16
+1155,3.1,4.287,241046,49,330,850,62.524,9.1,16,5,0,66,0,9.5,35.7,63,2018,7,17
+1156,6.215,5.224,243416,49,310,1000,63.006,10.2,14,6.7,0,57,0,10,33.2,51.9,2018,7,18
+1157,5.844,4.032,267608,44,350,1100,67.07,9.3,17,5,0,66,0,10,20.7,40.7,2018,7,19
+1158,3.622,6.751,227613,49,280,850,63.052,9,13,6,0,55,0,10,36.5,63,2018,7,22
+1159,4.117,5.459,286788,47,320,940,63.84,9.3,13,7,0,65,0,10,41.1,66.5,2018,7,23
+1160,3.513,4.107,362730,26,320,1000,63,10.1,16,6,0,74,0,10,27.5,53.5,2018,7,24
+1161,3.391,4.077,309158,40,330,820,60.728,10.2,14,5,0,78,0,10,24.6,37,2018,7,26
+1162,3.954,4.09,309731,35,290,770,60.563,9,14,6.5,0,69,0,10,25.7,50,2018,7,29
+1163,3.019,3.896,289943,35,320,820,60.563,9.4,12,6,0,65,0,10,30.4,51.9,2018,7,30
+1164,3.65,3.777,260510,35,330,1000,63.885,10.7,15,7,0,66,0,9.7,22.6,38.9,2018,7,31
+1165,3.61,3.873,285437,36,340,890,62.942,9.2,15,4,0,70,0,10,15.4,35.2,2018,8,1
+1166,3.385,3.691,297410,40,360,930,63.312,11.4,15,8,0,56,0,10,35.9,66.5,2018,8,2
+1167,3.917,4.087,251865,42,330,820,62.512,12.3,16,7.6,0,50,0,10,34.8,51.9,2018,8,5
+1168,4.433,3.827,331653,50,360,1100,67.019,8.5,13,5,0,65,0,10,23.5,35.2,2018,8,6
+1169,3.654,3.921,325329,44,360,900,63.312,10.9,13,9,0,61,0,10,32.4,48.2,2018,8,7
+1170,3.871,4.452,202616,40,422.98,845.96,62.83,8.7,16,3,0,74,0,10,20.7,31.7,2018,8,8
+1171,3.617,4.151,263932,47,340,890,61,10.4,13,8.5,0,62,0,10,38.2,63,2018,8,9
+1172,3.046,4.136,343442,37,310,790,61.396,11.3,14,9.9,0,63,0,10,22.2,35.2,2018,8,12
+1173,4.157,4.079,351710,37,300,1000,63.248,10.8,15,6.9,0,71,0,10,22.2,35.2,2018,8,13
+1174,4.318,3.989,344121,45,330,950,63.312,13.5,16,11,0,51,0,10,40.4,53.5,2018,8,14
+1175,3.442,3.585,325419,40,360,1100,67.019,11.1,18,5,0,56,0,10,24.3,46.5,2018,8,15
+1176,3.521,4.765,299944,37,430,990,62.322,9.3,14,6,0,61,0,10,19.1,29.4,2018,8,16
+1177,3.602,3.946,272606,29,290,670,60.662,6.8,12,4,0,76,0,10,24.1,46.5,2018,8,19
+1178,3.582,3.837,251888,29,280,760,60.406,8.9,11,6,0,73,0,9.8,20.6,31.7,2018,8,20
+1179,4.401,3.962,252906,41,350,810,55,8.8,12,6,0,79,0,9.8,15,24.1,2018,8,21
+1180,3.025,3.972,349091,41,380,970,62.257,9.1,13,4,0,69,0,10,14.1,24.1,2018,8,22
+1181,3.041,3.952,343612,36,390,1100,66.862,9.7,16,2,0,64,0,10,13.1,20.6,2018,8,23
+1182,4.204,3.889,288798,47,290,850,62.414,8.7,14,3,0,77,0,9.8,13.7,33.5,2018,8,26
+1183,2.959,3.867,256927,41,340,940,60.897,6.2,12,0,0,71,0,10,14.6,31.7,2018,8,27
+1184,3.719,3.864,308827,50,410,1100,64.864,4.7,11,-2,0,68,0,10,10.2,18.3,2018,8,28
+1185,3.538,3.893,321713,48,350,1000,62.479,8.5,14,3,0,50,0,10,17.6,42.4,2018,8,29
+1186,3.03,3.968,322896,38,330,990,63.312,11.1,14,7,0,41,0,10,29.4,51.9,2018,8,30
+1187,3.023,3.837,283637,42,360,950,62.257,7.3,12,3,0,77,0,10,12.8,27.8,2018,9,2
+1188,3.046,3.968,279421,43,360,1200,66.797,7.3,13,2,0,73,0,10,13,22.2,2018,9,3
+1189,4.503,3.809,308352,40,370,1100,68,11.7,18,5,0,57,0,10,16.5,38.9,2018,9,4
+1190,3.001,3.177,306308,39,350,990,63.312,14.4,18.3,9,0,54,0,10,28.3,46.5,2018,9,5
+1191,3.018,4.566,312529,36,390,980,62.414,12.4,19,5.8,0,71,0,10,23.2,50,2018,9,6
+1192,3.032,3.837,282721,45,370,860,63.84,13.9,18,10,0,66,0,10,18.5,40.7,2018,9,9
+1193,3.034,3.433,266473,37,320,1100,67.005,13.7,18,10,0,71,0,10,16.5,55.4,2018,9,10
+1194,4.068,3.334,286478,39,350,990,63.84,17.1,23.1,7.9,0,43,0,10,30.2,55.4,2018,9,11
+1195,3.549,3.944,180103,36,300,890,62.895,11.5,18,6,0,50,0,0,17.8,27.8,2018,9,12
+1196,3.037,3.906,329608,28,320,880,63.312,13.3,19,8,0,50,0,0,23.3,40.7,2018,9,13
+1197,3.914,3.849,194980,36,360,740,61.033,8.7,14,3,0,60,0,13.7,19.1,29.4,2018,9,16
+1198,3.011,3.996,286556,32,340,970,63.312,13.6,16,12,0,40,0,0,33.3,42.4,2018,9,17
+1199,3.873,3.894,314730,37,380,1100,66.797,8.4,12,5,0,79,0,10,12.4,25.9,2018,9,18
+1200,3.38,3.943,299107,35,422.98,845.96,62.414,8.4,15,3,0,68,3.3,11.6,15.7,42.4,2018,9,19
+1201,3.514,3.916,289956,36,350,990,62,10.7,16.7,2.3,1022,61,0,15.8,12.8,18.3,2018,9,20
+1202,3.549,3.79,309039,39,380,980,62.479,8.6,12,4,0,65,0,10,20.4,33.5,2018,9,23
+1203,3,3.822,315225,48,340,920,63.091,9.7,11,9,0,77,0,10,18.9,22.2,2018,9,24
+1204,3.568,3.859,296995,35,360,980,62.257,7.8,14,3,0,71,0,10,15.2,27.8,2018,9,25
+1205,3.684,3.673,306442,41,360,910,63.312,12.9,19,7,0,45,0,0,18.3,55.4,2018,9,26
+1206,4.49,3.972,270158,39,422.98,845.96,62.942,8.3,15,3,0,71,0.51,10,20.4,35.2,2018,9,28
+1207,3.728,4.112,270662,44,300,790,60.671,9.6,16.4,3,0,66,0,10,12.4,25.9,2018,9,30
+1208,1.516,4.315,262951,35,300,830,62.849,15.5,23,3.1,0,41,0,0,12.6,25.9,2018,10,1
+1209,4.69,4.451,267439,44,410,1000,63,20.3,25.9,10.3,0,35,0,10,22.2,38.9,2018,10,2
+1210,6.069,8.48,202227,41,310,1100,66.958,12.7,17,10,0,63,0,10,20.9,29.4,2018,10,3
+1211,5.596,8.186,285451,40,260,900,62.257,10.9,15.2,5.8,0,70,0,10,17.2,29.4,2018,10,4
+1212,4.194,5.859,294926,36,360,900,63.155,17.6,25,11,0,49,0,0,10.6,25.9,2018,10,7
+1213,4.422,4.741,301067,35,340,845.96,63.155,19.7,27,14,0,47,0,10,8,24.1,2018,10,8
+1214,4.321,4.909,283531,44,370,960,63.248,12.2,16,9,0,81,0,10,23.3,38.9,2018,10,9
+1215,3.161,5.003,158404,46,340,920,63.052,9.9,16.1,3.6,0,63,0,10,25,42.4,2018,10,10
+1216,6.998,4.442,245403,38,330,870,62.895,12.5,19.5,6,0,63,0,0,13.9,27.8,2018,10,11
+1217,7.119,3.81,283352,43,320,780,70,21.4,27,10.2,0,43,0,10,29.6,46.5,2018,10,14
+1218,6.041,7.749,261013,49,340,1200,67.07,23.4,27,18,0,40,0,10,34.6,48.2,2018,10,15
+1219,5.093,9.105,323494,47,350,960,63.248,17.3,22.2,14.7,0,79,0,10,25,42.4,2018,10,16
+1220,5.044,5.83,222837,45,340,850,63.885,17,21,13.8,0,67,2.29,10,19.8,33.5,2018,10,17
+1221,3.88,5.686,303182,41,340,880,63.248,15.9,21.3,10,0,68,0.25,10,19.4,42.4,2018,10,18
+1222,4.044,5.362,333262,45,340,820,60.856,13.7,21,6.4,0,60,0,10,16.3,46.5,2018,10,21
+1223,3.031,4.915,322831,31,370,940,63.312,18.2,27,7.7,0,47,0,10,25,46.5,2018,10,22
+1224,3.881,4.774,293890,43,350,1100,67.019,11.4,21.1,5,0,67,0,10.8,18.7,33.5,2018,10,23
+1225,4.19,4.624,219686,42,310,1200,66.958,10.7,16.6,4.7,0,63,0,10,18.1,29.4,2018,10,24
+1226,4.443,4.311,341987,42,350,1000,62.479,12.7,22.3,4.8,0,59,0,10,14.3,33.5,2018,10,25
+1227,5.387,4.783,309304,50,330,810,61.6,12.1,17.2,8.3,0,54,0,10,18.9,27.8,2018,10,28
+1228,4.055,4.848,304860,37,330,930,62.322,12.6,21,6,0,62,0,0,13.5,22.2,2018,10,29
+1229,3.614,5.922,300185,40,350,1100,66,17.7,26.9,5.9,0,53,0,10,11.5,25.9,2018,10,30
+1230,5.008,5.065,278652,25,422.98,845.96,63.619,15.3,21,11,0,77,0,10,12.2,20.6,2018,10,31
+1231,4.125,4.136,234241,27,422.98,845.96,64.849,27.4,34,20,0,28,0,0,25.4,50,2018,11,1
+1232,3.053,4.955,270214,39,422.98,845.96,63.683,17.7,24,14,0,55,0,0,12.4,27.8,2018,11,4
+1233,4.118,4.384,240673,21,422.98,845.96,62.785,14.7,21,5,0,75,0,51.5,13,27.8,2018,11,6
+1234,3.973,4.272,330795,35,422.98,845.96,62.479,10.3,16,6,0,62,0,0,21.5,45.2,2018,11,7
+1235,3.798,4.744,300619,33,320,760,61.24,12,17.1,6.9,0,59,0,0,16.7,27.8,2018,11,8
+1236,3.85,4.489,275148,35,340,830,63.155,24.4,29,20,0,25,0,0,22,31.7,2018,11,12
+1237,4.109,4.388,316940,41,310,920,62.322,12.3,17.1,6,0,64,0,0,19.5,31.7,2018,11,15
+1238,3.077,4.219,279823,39,350,910,60.388,0,0,0,0,0,0,0,0,0,2018,11,18
+1239,6.624,4.734,282413,31,320,1100,64.928,0,0,0,0,0,0,0,0,0,2018,11,19
+1240,7.579,4.738,305587,34,310,1000,60.388,0,0,0,0,0,0,0,0,0,2018,11,20
+1241,6.239,10.888,315000,28,280,680,59.603,12.5,14,11,0,67,0,0,28.9,42.4,2018,11,22
+1242,4.389,6.805,303537,30,330,720,61.24,14.4,19,11,0,78,0,0,16.3,31.7,2018,11,25
+1243,3.385,5.644,291143,35,340,930,63,15.5,19,13,0,71,0,0,15,25.9,2018,11,26
+1244,3.431,5.341,296543,31,300,900,63.248,16.6,20.1,14,0,75,0,0,22,35.2,2018,11,27
+1245,4.827,4.518,335973,43,340,960,63.312,15.6,20.3,13,0,50,0,51.3,25,35.9,2018,11,28
+1246,3.963,5.076,349363,44,340,940,63.091,15.9,20,14,0,74,0,0,17.6,25.9,2018,11,29
+1247,5.489,4.907,291902,25,290,1200,67.019,14.7,19,11,0,52,0,10,24.4,38.9,2018,12,2
+1248,4.559,4.637,313630,46,320,820,61.69,16.4,23,12,0,64,0,10,25.6,40.7,2018,12,3
+1249,4.57,5.068,324791,45,330,920,63.091,16.1,20,12,0,68,0,10,15.6,24.1,2018,12,4
+1250,5.056,5.941,292929,38,330,870,63.312,19.1,28,12.6,0,63,0,0,15.7,42.4,2018,12,5
+1251,5.095,9.77,277937,27,360,870,64.321,29.4,35,25,0,29,0,0,30.4,51.9,2018,12,6
+1252,3.846,6.157,292278,56,330,920,63.136,16.8,21,14,0,79,0,10,11.9,27.8,2018,12,9
+1253,5.372,5.004,292526,47,390,930,69,16.3,21,11.5,0,68,0,10,15.9,29.4,2018,12,10
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+1255,6.028,6.037,326261,34,320,990,64.321,24.6,33,15.6,0,51,0,9.2,20.9,40.7,2018,12,12
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+1259,3.021,5.159,259978,35,330,970,63.136,17.9,22,16,0,77,0,10,15,24.1,2018,12,18
+1260,3.024,4.703,332033,32,330,890,63.091,20.1,26,14.8,0,73,0,9.5,8.5,18.3,2018,12,19
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+1264,3.03,4.496,263962,32,310,810,62.023,19,26,14,0,65,0,10,19.4,33.5,2019,1,8
+1265,5.063,4.447,253436,33,340,810,60,15.4,20,9,0,56,0,10,16.7,31.7,2019,1,9
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+1280,6.517,7.265,266159,41,320,870,64.477,16.3,21,11,0,48,0,10,26.9,40.7,2019,1,31
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+1300,4.35E-06,5.291,286661,49,440,930,64.958,30.9,38,26,0,24,0,0,30,51.9,2019,2,28
+1301,5.133,4.781,283081,46,350,870,65.486,25.4,38,16,0,42,0,10,17.8,40.7,2019,3,3
+1302,5.951,4.42,300576,50,360,840,70,20.9,29,16,0,59,0,0,11.9,24.1,2019,3,4
+1303,5.956,5.531,275199,38,330,820,61.396,18.4,26,11,0,69,0,10,18,38.9,2019,3,5
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+1309,4.35E-06,5.264,351227,27,350,850,63.792,14.3,18,9.7,1017.5,59,0,11.3,14.4,25.9,2019,3,13
+1310,4.35E-06,4.968,326009,31,290,780,61.24,15.9,22,11,0,62,0,10,14.1,25.9,2019,3,14
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+1318,4.35E-06,7.31,274798,37,420,890,64.32,14.4,21,8,0,52,0,10,17.4,31.7,2019,3,26
+1319,4.35E-06,6.256,223711,35,420,910,64.366,16.3,23,11,0,50,0,0,15,29.4,2019,3,27
+1320,4.35E-06,5.556,232271,35,410,1000,64.477,22.1,28,17,0,23,0,0,24.3,48.2,2019,3,28
+1321,4.35E-06,5.299,263513,35,280,720,61.866,14.1,19,12,0,74,0,9.7,13.7,31.7,2019,3,31
+1322,4.656,5.951,289189,35,350,770,58,11.7,17,6,0,68,0,10,11.7,20.6,2019,4,1
+1323,5.902,5.313,303918,50,400,940,63.792,19.4,26,13,0,38,0,0,21.1,29.4,2019,4,2
+1324,6.182,5.297,267033,27,360,1000,64.477,17.1,26,12.9,0,61,0,10,19.4,35.2,2019,4,3
+1325,6.432,6.005,339369,37,350,770,61.396,17.7,23,13,0,61,0,0,14.1,50,2019,4,4
+1326,6.248,7.915,276679,45,260,680,62.512,18.7,26,10,0,41,0,10,20,38.9,2019,4,7
+1327,6.112,5.953,266240,37,350,1000,64.477,16.3,23,9,0,57,0,10,22.6,42.4,2019,4,8
+1328,4.054,5.066,232435,48,340,845.96,64.477,11.1,16,8,0,67,0,10,17.2,35.2,2019,4,9
+1329,3.686,5.477,207915,42,380,840,64.366,13.1,15,9,0,59,0,10,11.9,20.6,2019,4,10
+1330,5.51,4.483,319623,38,320,650,60.406,11.4,18,5.6,0,64,0,10,13.3,20.6,2019,4,11
+1331,5.115,5.066,271916,45,260,660,60,17.1,23,12,0,58,0,0,9.6,25.9,2019,4,14
+1332,5.24,4.69,282147,40,300,670,62.512,22.4,27,20,0,36,0,0,25,42.4,2019,4,15
+1333,4.463,5.367,295988,36,340,680,62.218,24.8,30,21,0,28,0,0,41.3,61.1,2019,4,16
+1334,5.542,5.069,290667,38,300,930,65.486,20.9,31,8.9,0,39,0,10,26.9,59.4,2019,4,17
+1335,4.613,4.701,233217,33,422.98,845.96,64.32,15.1,23,9,0,56,0,0,11.3,27.8,2019,4,19
+1336,4.332,5.14,172867,42,270,780,61.601,13,16.1,9,0,73,0,10,12.4,18.3,2019,4,22
+1337,6.161,4.348,248114,46,300,890,64.32,16.1,22,11,0,54,0,10,18,31.7,2019,4,25
+1338,7.528,5.253,223064,50,260,730,62.032,12.2,16.2,8,0,77,0,10,14.6,27.8,2019,4,28
+1339,6.984,5.988,224891,40,250,770,61.991,12.3,18,7,0,63,0,10,12.8,38.9,2019,4,29
+1340,3.572,6.175,264894,41,270,750,62.384,18.7,22,15,0,37,0,10,28.3,50,2019,4,30
+1341,4.35E-06,6.372,269271,43,320,880,61,18.9,22,15,0,72,0,51.8,30,38.9,2019,5,1
+1342,0.002,5.208,257362,49,330,780,62.16,15.4,20,10,0,76,0,0,20.6,31.7,2019,5,2
+1343,5.689,4.165,261684,48,220,780,62.16,11.8,16,8,0,81,0,0,14.1,24.1,2019,5,5
+1344,6.567,4.093,223546,48,280,840,63.422,11,16,6,0,76,0,0,14.3,25.9,2019,5,6
+1345,6.589,6.135,236331,34,310,950,64.477,13.4,19,9,0,62,0,0,25.9,48.2,2019,5,7
+1346,5.481,5.445,260337,46,360,920,64.477,12,16,8,0,67,0,0,22.6,42.4,2019,5,8
+1347,3.994,5.608,262600,40,290,990,64.477,12.2,16,8.8,0,65,0,51.8,25.2,55.4,2019,5,9
+1348,4.525,4.664,243279,43,330,830,64.256,13.9,17,11,0,69,0,0,15.7,22.2,2019,5,12
+1349,5.326,4.59,248342,39,250,750,62.317,12.9,17,9,0,65,0,0,22.8,33.5,2019,5,13
+1350,5.64,4.37,230971,44,340,930,66,14.3,19.1,10,0,69,0,0,10.4,25.9,2019,5,14
+1351,3.788,5.544,232223,50,310,880,63.422,11.4,16,6,0,71,0,0,8.9,20.6,2019,5,15
+1352,4.844,5.078,297914,38,330,910,61.025,0,0,0,0,0,0,0,0,0,2019,5,16
+1353,5.045,4.628,269476,40,270,700,61.521,0,0,0,0,0,0,0,0,0,2019,5,19
+1354,4.187,4.895,275305,41,330,800,62.317,13.6,17,10,0,79,0,0,28.7,53.5,2019,5,20
+1355,4.467,4.705,270048,34,280,880,64.256,14.4,20,10.8,0,70,0,0,20.7,27.8,2019,5,21
+1356,2.815,4.644,188232,35,300,720,61.668,15.3,22,11,0,61,0,0,19.1,29.4,2019,5,22
+1357,5.332,4.488,306155,32,310,740,61.69,16.6,21,14,0,49,0,0,41.9,53.5,2019,5,23
+1358,5.502,4.453,285131,26,190,610,48,10.3,14,6,0,66,0,51.8,27.2,46.5,2019,5,26
+1359,5.392,4.93,328307,24,200,560,53.295,9.1,13,7,0,70,0,0,30.7,51.9,2019,5,27
+1360,4.582,4.802,339074,24,260,620,57.086,10.9,15,7,0,67,0,0,28,42.4,2019,5,28
+1361,4.875,5.346,353157,28,280,680,58.769,6.6,10,5,0,76,0,0,28.5,46.5,2019,5,29
+1362,4.846,4.219,343734,19,170,640,59.797,10.6,12,8.8,0,50,0,51.7,22.8,35.2,2019,5,30
+1363,3.593,4.357,321106,29,230,800,61.591,9.5,14,7,0,51,0,9.5,17.5,42.4,2019,6,2
+1364,3.954,4.907,259208,33,180,720,61.19,8.1,10,6,0,59,0,9,18.1,35.2,2019,6,3
+1365,5.686,5.083,286142,38,260,750,61.033,9.1,12,6,0,77,0,10,15,25.9,2019,6,4
+1366,6.171,4.615,295447,35,300,980,63.619,10.5,12,9.6,0,72,0,10,18.9,25.9,2019,6,5
+1367,3.797,5.971,303571,39,320,920,63.155,11.8,14,10,0,52,0,10,10.7,25.9,2019,6,6
+1368,4.545,4.932,294265,39,422.98,845.96,62.942,10.1,17,5,0,74,0,10,13.9,35.2,2019,6,7
+1369,4.738,4.777,304417,39,320,790,61.69,12.6,15,8.9,0,67,0,10,23,37,2019,6,10
+1370,2.813,5.216,255359,44,260,870,63.84,14.3,17,12,0,67,0,9.7,35.6,59.4,2019,6,11
+1371,4.398,4.513,304526,43,230,780,61.885,12,16,7,0,55,0,9.8,23.2,42.4,2019,6,12
+1372,3.805,4.558,329105,43,300,810,65,12.1,16,5,0,75,0,9.8,19.1,29.4,2019,6,13
+1373,5.327,4.795,303728,45,330,770,61.632,10.4,15,7,0,79,0,10,17.6,24.1,2019,6,16
+1374,4.394,4.656,277748,47,270,760,61.789,11.6,17,8.8,0,74,0,10,23.3,35.2,2019,6,17
+1375,3.838,4.95,289854,44,270,870,62.942,7.2,12,4.7,0,82,0,10,18.9,40.7,2019,6,18
+1376,4.934,4.834,289607,46,360,1000,62.849,7.7,11,5.6,0,55,0,10,11.1,18.3,2019,6,19
+1377,5.068,4.716,305938,28,310,660,58.807,6.8,10,4,0,56,0,10,14.4,22.2,2019,6,20
+1378,5.882,5.51,293446,40,250,700,60.671,7.6,16,3,0,71,0,0,13.5,25.9,2019,6,24
+1379,4.638,4.811,307968,47,260,860,64,9.7,16,3,0,65,0,10,18.1,25.9,2019,6,25
+1380,5.373,4.929,316675,46,300,900,62.479,10.9,17,5,0,65,0,10,21.9,35.2,2019,6,26
+1381,4.072,5.194,318268,31,270,910,63.312,12.4,16,10,0,63,0,10,28,44.6,2019,6,27
diff --git a/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Sukaran IIT BHU assignment 3.ipynb b/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Sukaran IIT BHU assignment 3.ipynb
new file mode 100644
index 00000000..02438816
--- /dev/null
+++ b/NON IITK/Assignments/Assignment 3/SukaranIIT BHU/Sukaran IIT BHU assignment 3.ipynb	
@@ -0,0 +1,907 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "73678b5e-f0ff-4dc1-8107-e17d7030c9c2",
+   "metadata": {},
+   "source": [
+    "Dataset: Wastewater Treatment Plant Dataset \n",
+    "\n",
+    "\n",
+    "The dataset contains daily measurements from a full-scale wastewater treatment plant, including various physicochemical properties that help assess plant performance. The dataset can be used to analyse the plant's operational effectiveness and predict potential faults.\r\n",
+    "Dataset Link : https://www.kaggle.com/datasets/d4rklucif3r/full-scale-waste-water-treatment-plant-dat\n",
+    "a\r\n",
+    "The objective is to build a machine learning model that predicts whether the wastewater treatment process is operating optimally based on daily measurements of the plant's operational data\r\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 448,
+   "id": "e8b01d4c-058f-4fee-b3f6-07037b866e03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.svm import SVC\n",
+    "from sklearn.model_selection import GridSearchCV\n",
+    "from sklearn.metrics import accuracy_score, f1_score, confusion_matrix, classification_report"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 449,
+   "id": "fa7dff98-48eb-4417-ba98-d70acccbc14b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Serial number</th>\n",
+       "      <th>Average Outflow</th>\n",
+       "      <th>Average Inflow</th>\n",
+       "      <th>Energy Consumption</th>\n",
+       "      <th>Ammonia</th>\n",
+       "      <th>Biological Oxygen Demand</th>\n",
+       "      <th>Chemical Oxygen Demand</th>\n",
+       "      <th>Total Nitrogen</th>\n",
+       "      <th>Average Temperature</th>\n",
+       "      <th>Maximum temperature</th>\n",
+       "      <th>Minimum temperature</th>\n",
+       "      <th>Atmospheric pressure</th>\n",
+       "      <th>Average humidity</th>\n",
+       "      <th>Total rainfall</th>\n",
+       "      <th>Average visibility</th>\n",
+       "      <th>Average wind speed</th>\n",
+       "      <th>Maximum wind speed</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Day</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2.941</td>\n",
+       "      <td>2.589</td>\n",
+       "      <td>175856</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>730.0</td>\n",
+       "      <td>60.378</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>25.1</td>\n",
+       "      <td>12.6</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>56</td>\n",
+       "      <td>1.52</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>26.9</td>\n",
+       "      <td>53.5</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2.936</td>\n",
+       "      <td>2.961</td>\n",
+       "      <td>181624</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>370.0</td>\n",
+       "      <td>740.0</td>\n",
+       "      <td>60.026</td>\n",
+       "      <td>17.1</td>\n",
+       "      <td>23.6</td>\n",
+       "      <td>12.3</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>63</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>14.4</td>\n",
+       "      <td>27.8</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2.928</td>\n",
+       "      <td>3.225</td>\n",
+       "      <td>202016</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>418.0</td>\n",
+       "      <td>836.0</td>\n",
+       "      <td>64.522</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>27.2</td>\n",
+       "      <td>8.8</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>31.9</td>\n",
+       "      <td>61.1</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2.928</td>\n",
+       "      <td>3.354</td>\n",
+       "      <td>207547</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>430.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>63.000</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>19.9</td>\n",
+       "      <td>11.1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>49</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>38.9</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2.917</td>\n",
+       "      <td>3.794</td>\n",
+       "      <td>202824</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>508.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>65.590</td>\n",
+       "      <td>13.4</td>\n",
+       "      <td>19.1</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.6</td>\n",
+       "      <td>35.2</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Serial number  Average Outflow  Average Inflow  Energy Consumption  \\\n",
+       "0              0            2.941           2.589              175856   \n",
+       "1              1            2.936           2.961              181624   \n",
+       "2              2            2.928           3.225              202016   \n",
+       "3              3            2.928           3.354              207547   \n",
+       "4              4            2.917           3.794              202824   \n",
+       "\n",
+       "   Ammonia  Biological Oxygen Demand  Chemical Oxygen Demand  Total Nitrogen  \\\n",
+       "0     27.0                     365.0                   730.0          60.378   \n",
+       "1     25.0                     370.0                   740.0          60.026   \n",
+       "2     42.0                     418.0                   836.0          64.522   \n",
+       "3     36.0                     430.0                   850.0          63.000   \n",
+       "4     46.0                     508.0                  1016.0          65.590   \n",
+       "\n",
+       "   Average Temperature  Maximum temperature  Minimum temperature  \\\n",
+       "0                 19.3                 25.1                 12.6   \n",
+       "1                 17.1                 23.6                 12.3   \n",
+       "2                 16.8                 27.2                  8.8   \n",
+       "3                 14.6                 19.9                 11.1   \n",
+       "4                 13.4                 19.1                  8.0   \n",
+       "\n",
+       "   Atmospheric pressure  Average humidity  Total rainfall  Average visibility  \\\n",
+       "0                   0.0                56            1.52                10.0   \n",
+       "1                   0.0                63            0.00                10.0   \n",
+       "2                   0.0                47            0.25                10.0   \n",
+       "3                   0.0                49            0.00                10.0   \n",
+       "4                   0.0                65            0.00                10.0   \n",
+       "\n",
+       "   Average wind speed  Maximum wind speed  Year  Month  Day  \n",
+       "0                26.9                53.5  2014      1    1  \n",
+       "1                14.4                27.8  2014      1    2  \n",
+       "2                31.9                61.1  2014      1    5  \n",
+       "3                27.0                38.9  2014      1    6  \n",
+       "4                20.6                35.2  2014      1    7  "
+      ]
+     },
+     "execution_count": 449,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv('Data-Melbourne_F_fixed.csv')\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6e2ac5c4-6544-4f35-8291-81f16d0d26c7",
+   "metadata": {},
+   "source": [
+    "1.\tData Preprocessing: \n",
+    "Perform comprehensive data preprocessing, including handling missing values, scaling, and feature selection, while visualizing key trends and correlations to enhance data insights and model performance.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 451,
+   "id": "9aca9ac7-324c-4a57-ac3e-574d28d505a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Serial number               0\n",
+       "Average Outflow             0\n",
+       "Average Inflow              0\n",
+       "Energy Consumption          0\n",
+       "Ammonia                     0\n",
+       "Biological Oxygen Demand    0\n",
+       "Chemical Oxygen Demand      0\n",
+       "Total Nitrogen              0\n",
+       "Average Temperature         0\n",
+       "Maximum temperature         0\n",
+       "Minimum temperature         0\n",
+       "Atmospheric pressure        0\n",
+       "Average humidity            0\n",
+       "Total rainfall              0\n",
+       "Average visibility          0\n",
+       "Average wind speed          0\n",
+       "Maximum wind speed          0\n",
+       "Year                        0\n",
+       "Month                       0\n",
+       "Day                         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 451,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 452,
+   "id": "eb08ddd0-b67a-4935-86fa-fc63759498b3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Serial number</th>\n",
+       "      <th>Average Outflow</th>\n",
+       "      <th>Average Inflow</th>\n",
+       "      <th>Energy Consumption</th>\n",
+       "      <th>Ammonia</th>\n",
+       "      <th>Biological Oxygen Demand</th>\n",
+       "      <th>Chemical Oxygen Demand</th>\n",
+       "      <th>Total Nitrogen</th>\n",
+       "      <th>Average Temperature</th>\n",
+       "      <th>Maximum temperature</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Atmospheric pressure</th>\n",
+       "      <th>Average humidity</th>\n",
+       "      <th>Total rainfall</th>\n",
+       "      <th>Average visibility</th>\n",
+       "      <th>Average wind speed</th>\n",
+       "      <th>Maximum wind speed</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Month</th>\n",
+       "      <th>Day</th>\n",
+       "      <th>temperature_difference</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2.941</td>\n",
+       "      <td>2.589</td>\n",
+       "      <td>175856</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>365.0</td>\n",
+       "      <td>730.0</td>\n",
+       "      <td>60.378</td>\n",
+       "      <td>19.3</td>\n",
+       "      <td>25.1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>56</td>\n",
+       "      <td>1.52</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>26.9</td>\n",
+       "      <td>53.5</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>12.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2.936</td>\n",
+       "      <td>2.961</td>\n",
+       "      <td>181624</td>\n",
+       "      <td>25.0</td>\n",
+       "      <td>370.0</td>\n",
+       "      <td>740.0</td>\n",
+       "      <td>60.026</td>\n",
+       "      <td>17.1</td>\n",
+       "      <td>23.6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>63</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>14.4</td>\n",
+       "      <td>27.8</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>11.3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2.928</td>\n",
+       "      <td>3.225</td>\n",
+       "      <td>202016</td>\n",
+       "      <td>42.0</td>\n",
+       "      <td>418.0</td>\n",
+       "      <td>836.0</td>\n",
+       "      <td>64.522</td>\n",
+       "      <td>16.8</td>\n",
+       "      <td>27.2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>47</td>\n",
+       "      <td>0.25</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>31.9</td>\n",
+       "      <td>61.1</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "      <td>18.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>2.928</td>\n",
+       "      <td>3.354</td>\n",
+       "      <td>207547</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>430.0</td>\n",
+       "      <td>850.0</td>\n",
+       "      <td>63.000</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>19.9</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>49</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>27.0</td>\n",
+       "      <td>38.9</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6</td>\n",
+       "      <td>8.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>2.917</td>\n",
+       "      <td>3.794</td>\n",
+       "      <td>202824</td>\n",
+       "      <td>46.0</td>\n",
+       "      <td>508.0</td>\n",
+       "      <td>1016.0</td>\n",
+       "      <td>65.590</td>\n",
+       "      <td>13.4</td>\n",
+       "      <td>19.1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>65</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>20.6</td>\n",
+       "      <td>35.2</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1</td>\n",
+       "      <td>7</td>\n",
+       "      <td>11.1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Serial number  Average Outflow  Average Inflow  Energy Consumption  \\\n",
+       "0              0            2.941           2.589              175856   \n",
+       "1              1            2.936           2.961              181624   \n",
+       "2              2            2.928           3.225              202016   \n",
+       "3              3            2.928           3.354              207547   \n",
+       "4              4            2.917           3.794              202824   \n",
+       "\n",
+       "   Ammonia  Biological Oxygen Demand  Chemical Oxygen Demand  Total Nitrogen  \\\n",
+       "0     27.0                     365.0                   730.0          60.378   \n",
+       "1     25.0                     370.0                   740.0          60.026   \n",
+       "2     42.0                     418.0                   836.0          64.522   \n",
+       "3     36.0                     430.0                   850.0          63.000   \n",
+       "4     46.0                     508.0                  1016.0          65.590   \n",
+       "\n",
+       "   Average Temperature  Maximum temperature  ...  Atmospheric pressure  \\\n",
+       "0                 19.3                 25.1  ...                   0.0   \n",
+       "1                 17.1                 23.6  ...                   0.0   \n",
+       "2                 16.8                 27.2  ...                   0.0   \n",
+       "3                 14.6                 19.9  ...                   0.0   \n",
+       "4                 13.4                 19.1  ...                   0.0   \n",
+       "\n",
+       "   Average humidity  Total rainfall  Average visibility  Average wind speed  \\\n",
+       "0                56            1.52                10.0                26.9   \n",
+       "1                63            0.00                10.0                14.4   \n",
+       "2                47            0.25                10.0                31.9   \n",
+       "3                49            0.00                10.0                27.0   \n",
+       "4                65            0.00                10.0                20.6   \n",
+       "\n",
+       "   Maximum wind speed  Year  Month  Day  temperature_difference  \n",
+       "0                53.5  2014      1    1                    12.5  \n",
+       "1                27.8  2014      1    2                    11.3  \n",
+       "2                61.1  2014      1    5                    18.4  \n",
+       "3                38.9  2014      1    6                     8.8  \n",
+       "4                35.2  2014      1    7                    11.1  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 452,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['temperature_difference']=df['Maximum temperature']-df['Minimum temperature']\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 453,
+   "id": "45e5fdff-70bc-42f9-a4ea-7417981e57e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 2000x1000 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "correlation_matrix = df.corr()\n",
+    "plt.figure(figsize=(20, 10))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm')\n",
+    "plt.title('Correlation Matrix')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3957b0bb-4d17-4c25-b927-91d1fb8f3224",
+   "metadata": {},
+   "source": [
+    "2.\tModeling with Machine Learning Algorithms:\r\n",
+    "Apply various machine learning algorithms to classify the operational state of the wastewater treatment process. Use the following algorithms:\r\n",
+    "o\tLogistic Regression from scratch as well as from sklearn\r\n",
+    "o\tK-Nearest Neighbours (KNN)\r\n",
+    "o\tDecision Tree Classifier\r\n",
+    "o\tRandom Forest Classifier\r\n",
+    "o\tSupport Vector Machine (SVM)\r\n",
+    "o\tAny other relevant algorithms you feel might improve performance.\r\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 455,
+   "id": "434acd28-4b8d-422a-93ec-c5855e81fa0b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "determining_value=df['Chemical Oxygen Demand'].mean()\n",
+    "df['cod']=df['Chemical Oxygen Demand'].apply(lambda x:1 if x>determining_value else 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 456,
+   "id": "17ced6e0-6be6-4931-b502-a8d20b9f98f7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = df.drop(['cod' , 'Chemical Oxygen Demand'] , axis = 1)\n",
+    "y = df['cod']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 457,
+   "id": "890c5ca8-d8b8-41ec-a56f-e1d8474dd3fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train , x_test , y_train , y_test = train_test_split(x, y, random_state = 20 , test_size = 0.2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 458,
+   "id": "15afb544-555b-4295-8ef0-852daa00fc35",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st = StandardScaler()\n",
+    "x_train_sc = st.fit_transform(x_train)\n",
+    "x_test_sc = st.transform(x_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 459,
+   "id": "5e3e39f1-765a-411c-8641-f3129195bc47",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m1 = LogisticRegression()\n",
+    "\n",
+    "m1.fit(x_train_sc, y_train)\n",
+    "\n",
+    "\n",
+    "y_pred_m1 = m1.predict(x_test_sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 460,
+   "id": "7cca33c9-0aa3-4026-aacd-c192dcc4ea20",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m2 = KNeighborsClassifier()\n",
+    "\n",
+    "m2.fit(x_train_sc, y_train)\n",
+    "\n",
+    "\n",
+    "y_pred_m2 = m2.predict(x_test_sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 461,
+   "id": "e3f8a4cc-8f68-483d-b46c-529a59256b45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m3 = DecisionTreeClassifier()\n",
+    "\n",
+    "m3.fit(x_train_sc, y_train)\n",
+    "\n",
+    "\n",
+    "y_pred_m3 = m3.predict(x_test_sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 462,
+   "id": "ef22c5a1-7c8a-4e8c-bd2b-10ed99f20021",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m4 = RandomForestClassifier()\n",
+    "\n",
+    "m4.fit(x_train_sc, y_train)\n",
+    "\n",
+    "\n",
+    "y_pred_m4 = m4.predict(x_test_sc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 463,
+   "id": "7227dea5-afe3-4f20-8ffa-9cac4e287305",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m5 = SVC()\n",
+    "\n",
+    "m5.fit(x_train_sc, y_train)\n",
+    "\n",
+    "\n",
+    "y_pred_m5 = m5.predict(x_test_sc)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d911935f-9215-4eff-995f-37f74c149f10",
+   "metadata": {},
+   "source": [
+    "3.\tModel Evaluation:\n",
+    "Evaluate and compare models using accuracy, F1-score, and confusion matrix, and perform hyperparameter tuning to optimize performance on the test dataset.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 465,
+   "id": "57ebd50e-325c-425e-872f-4ee0f2b6e6d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "m1\n",
+      "Accuracy: 0.79\n",
+      "F1 Score: 0.78\n",
+      "Confusion Matrix:\n",
+      "[[120  28]\n",
+      " [ 29 100]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred_m1)\n",
+    "f1 = f1_score(y_test, y_pred_m1)  \n",
+    "cm = confusion_matrix(y_test, y_pred_m1)    \n",
+    "\n",
+    "print(f\"m1\")\n",
+    "print(f\"Accuracy: {accuracy:.2f}\")\n",
+    "print(f\"F1 Score: {f1:.2f}\")\n",
+    "print(\"Confusion Matrix:\")\n",
+    "print(cm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 466,
+   "id": "59262b36-bd01-4e16-bdb7-5df4d15548e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "m2\n",
+      "Accuracy: 0.73\n",
+      "F1 Score: 0.71\n",
+      "Confusion Matrix:\n",
+      "[[110  38]\n",
+      " [ 37  92]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred_m2)\n",
+    "f1 = f1_score(y_test, y_pred_m2)  \n",
+    "cm = confusion_matrix(y_test, y_pred_m2)    \n",
+    "\n",
+    "print(f\"m2\")\n",
+    "print(f\"Accuracy: {accuracy:.2f}\")\n",
+    "print(f\"F1 Score: {f1:.2f}\")\n",
+    "print(\"Confusion Matrix:\")\n",
+    "print(cm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 467,
+   "id": "d51bb2cf-e106-4137-a935-4652bb70f3cf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "m3\n",
+      "Accuracy: 0.82\n",
+      "F1 Score: 0.82\n",
+      "Confusion Matrix:\n",
+      "[[119  29]\n",
+      " [ 20 109]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred_m3)\n",
+    "f1 = f1_score(y_test, y_pred_m3)  \n",
+    "cm = confusion_matrix(y_test, y_pred_m3)    \n",
+    "\n",
+    "print(f\"m3\")\n",
+    "print(f\"Accuracy: {accuracy:.2f}\")\n",
+    "print(f\"F1 Score: {f1:.2f}\")\n",
+    "print(\"Confusion Matrix:\")\n",
+    "print(cm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 468,
+   "id": "55abf7a3-f924-4f72-ada2-95e85132e428",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "m4\n",
+      "Accuracy: 0.88\n",
+      "F1 Score: 0.88\n",
+      "Confusion Matrix:\n",
+      "[[127  21]\n",
+      " [ 11 118]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred_m4)\n",
+    "f1 = f1_score(y_test, y_pred_m4)  \n",
+    "cm = confusion_matrix(y_test, y_pred_m4)    \n",
+    "\n",
+    "print(f\"m4\")\n",
+    "print(f\"Accuracy: {accuracy:.2f}\")\n",
+    "print(f\"F1 Score: {f1:.2f}\")\n",
+    "print(\"Confusion Matrix:\")\n",
+    "print(cm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 469,
+   "id": "2f7e9cda-7105-4bb7-bb1e-a8a92d0ccd06",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "m5\n",
+      "Accuracy: 0.79\n",
+      "F1 Score: 0.78\n",
+      "Confusion Matrix:\n",
+      "[[117  31]\n",
+      " [ 26 103]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred_m5)\n",
+    "f1 = f1_score(y_test, y_pred_m5) \n",
+    "cm = confusion_matrix(y_test, y_pred_m5)    \n",
+    "\n",
+    "print(f\"m5\")\n",
+    "print(f\"Accuracy: {accuracy:.2f}\")\n",
+    "print(f\"F1 Score: {f1:.2f}\")\n",
+    "print(\"Confusion Matrix:\")\n",
+    "print(cm)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 470,
+   "id": "d17def9a-6e6a-4b26-854f-a55243bee6ff",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best Parameters: {'max_depth': 20, 'min_samples_leaf': 1, 'min_samples_split': 5, 'n_estimators': 100}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import GridSearchCV\n",
+    "\n",
+    "param_grid = {\n",
+    "    'n_estimators': [100, 200],\n",
+    "    'max_depth': [10, 20, None],\n",
+    "    'min_samples_split': [2, 5],\n",
+    "    'min_samples_leaf': [1, 2]\n",
+    "}\n",
+    "\n",
+    "grid_search_rf = GridSearchCV(RandomForestClassifier(), param_grid, cv=5)\n",
+    "grid_search_rf.fit(x_train_sc, y_train)\n",
+    "\n",
+    "print(f\"Best Parameters: {grid_search_rf.best_params_}\")\n",
+    "best_rf = grid_search_rf.best_estimator_\n",
+    "Y_pred_rf_tuned = best_rf.predict(x_test_sc)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NON IITK/Final Task/SukaranIITBHU/Presentationfinal.pptx b/NON IITK/Final Task/SukaranIITBHU/Presentationfinal.pptx
new file mode 100644
index 00000000..5ab5da40
Binary files /dev/null and b/NON IITK/Final Task/SukaranIITBHU/Presentationfinal.pptx differ
diff --git a/NON IITK/Final Task/SukaranIITBHU/Sukaran_IITBHU_Final_Project (2).ipynb b/NON IITK/Final Task/SukaranIITBHU/Sukaran_IITBHU_Final_Project (2).ipynb
new file mode 100644
index 00000000..b9de9897
--- /dev/null
+++ b/NON IITK/Final Task/SukaranIITBHU/Sukaran_IITBHU_Final_Project (2).ipynb	
@@ -0,0 +1,828 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "7053bace-0beb-4889-ae45-c314e34b107d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "from sklearn.model_selection import train_test_split, cross_val_score\n",
+    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.metrics import f1_score, accuracy_score, precision_score, recall_score\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "65203b8f-ea19-46c9-8698-a5a14359187b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Unnamed: 0</th>\n",
+       "      <th>Id</th>\n",
+       "      <th>CAS</th>\n",
+       "      <th>SMILES</th>\n",
+       "      <th>Status</th>\n",
+       "      <th>Experimental value</th>\n",
+       "      <th>Predicted value</th>\n",
+       "      <th>NumValenceElectrons</th>\n",
+       "      <th>qed</th>\n",
+       "      <th>TPSA</th>\n",
+       "      <th>MolMR</th>\n",
+       "      <th>BalabanJ</th>\n",
+       "      <th>BertzCT</th>\n",
+       "      <th>MolWt</th>\n",
+       "      <th>MolLogP</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>100-00-5</td>\n",
+       "      <td>O=[N+]([O-])c1ccc(cc1)Cl</td>\n",
+       "      <td>Training</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0.463602</td>\n",
+       "      <td>43.14</td>\n",
+       "      <td>38.1064</td>\n",
+       "      <td>3.003401</td>\n",
+       "      <td>244.429658</td>\n",
+       "      <td>157.556</td>\n",
+       "      <td>2.2482</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>100-01-6</td>\n",
+       "      <td>O=[N+]([O-])c1ccc(N)cc1</td>\n",
+       "      <td>Training</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0.359544</td>\n",
+       "      <td>69.16</td>\n",
+       "      <td>37.5088</td>\n",
+       "      <td>3.003401</td>\n",
+       "      <td>242.429658</td>\n",
+       "      <td>138.126</td>\n",
+       "      <td>1.1770</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>100-02-7</td>\n",
+       "      <td>O=[N+]([O-])c1ccc(O)cc1</td>\n",
+       "      <td>Training</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>52</td>\n",
+       "      <td>0.470728</td>\n",
+       "      <td>63.37</td>\n",
+       "      <td>34.7612</td>\n",
+       "      <td>3.003401</td>\n",
+       "      <td>241.674771</td>\n",
+       "      <td>139.110</td>\n",
+       "      <td>1.3004</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "      <td>100-11-8</td>\n",
+       "      <td>O=[N+]([O-])c1ccc(cc1)CBr</td>\n",
+       "      <td>Training</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>58</td>\n",
+       "      <td>0.432586</td>\n",
+       "      <td>43.14</td>\n",
+       "      <td>45.7274</td>\n",
+       "      <td>2.913802</td>\n",
+       "      <td>257.648013</td>\n",
+       "      <td>216.034</td>\n",
+       "      <td>2.4897</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>5</td>\n",
+       "      <td>100-12-9</td>\n",
+       "      <td>O=[N+]([O-])c1ccc(cc1)CC</td>\n",
+       "      <td>Training</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>58</td>\n",
+       "      <td>0.479785</td>\n",
+       "      <td>43.14</td>\n",
+       "      <td>42.4744</td>\n",
+       "      <td>2.913802</td>\n",
+       "      <td>253.299498</td>\n",
+       "      <td>151.165</td>\n",
+       "      <td>2.1572</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0  Id       CAS                     SMILES    Status  \\\n",
+       "0           0   1  100-00-5   O=[N+]([O-])c1ccc(cc1)Cl  Training   \n",
+       "1           1   2  100-01-6    O=[N+]([O-])c1ccc(N)cc1  Training   \n",
+       "2           2   3  100-02-7    O=[N+]([O-])c1ccc(O)cc1  Training   \n",
+       "3           3   4  100-11-8  O=[N+]([O-])c1ccc(cc1)CBr  Training   \n",
+       "4           4   5  100-12-9   O=[N+]([O-])c1ccc(cc1)CC  Training   \n",
+       "\n",
+       "   Experimental value Predicted value  NumValenceElectrons       qed   TPSA  \\\n",
+       "0                   1               1                   52  0.463602  43.14   \n",
+       "1                   1               1                   52  0.359544  69.16   \n",
+       "2                   0               1                   52  0.470728  63.37   \n",
+       "3                   1               0                   58  0.432586  43.14   \n",
+       "4                   0               0                   58  0.479785  43.14   \n",
+       "\n",
+       "     MolMR  BalabanJ     BertzCT    MolWt  MolLogP  \n",
+       "0  38.1064  3.003401  244.429658  157.556   2.2482  \n",
+       "1  37.5088  3.003401  242.429658  138.126   1.1770  \n",
+       "2  34.7612  3.003401  241.674771  139.110   1.3004  \n",
+       "3  45.7274  2.913802  257.648013  216.034   2.4897  \n",
+       "4  42.4744  2.913802  253.299498  151.165   2.1572  "
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df=pd.read_csv(\"mutagenicity_kNN.csv\")\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "851bc0e2-f09f-4923-bc4a-c4097bd7a269",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 5764 entries, 0 to 5763\n",
+      "Data columns (total 15 columns):\n",
+      " #   Column               Non-Null Count  Dtype  \n",
+      "---  ------               --------------  -----  \n",
+      " 0   Unnamed: 0           5764 non-null   int64  \n",
+      " 1   Id                   5764 non-null   int64  \n",
+      " 2   CAS                  5764 non-null   object \n",
+      " 3   SMILES               5764 non-null   object \n",
+      " 4   Status               5764 non-null   object \n",
+      " 5   Experimental value   5764 non-null   int64  \n",
+      " 6   Predicted value      5764 non-null   object \n",
+      " 7   NumValenceElectrons  5764 non-null   int64  \n",
+      " 8   qed                  5764 non-null   float64\n",
+      " 9   TPSA                 5764 non-null   float64\n",
+      " 10  MolMR                5764 non-null   float64\n",
+      " 11  BalabanJ             5764 non-null   float64\n",
+      " 12  BertzCT              5764 non-null   float64\n",
+      " 13  MolWt                5764 non-null   float64\n",
+      " 14  MolLogP              5764 non-null   float64\n",
+      "dtypes: float64(7), int64(4), object(4)\n",
+      "memory usage: 675.6+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "3736915f-151f-46f7-9cf3-a33fa5fc3dcd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "categorical_columns = df.select_dtypes(include=['object']).columns\n",
+    "for col in categorical_columns:\n",
+    "    df[col] = LabelEncoder().fit_transform(df[col])\n",
+    "df.fillna(df.median(), inplace=True)\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "a68abd4f-edd9-4822-8823-9c88f7b59b0d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "X = df.drop(columns=['Experimental value','Predicted value'])\n",
+    "\n",
+    "y = df['Experimental value']\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "scaler = StandardScaler()\n",
+    "X_train = scaler.fit_transform(X_train)\n",
+    "X_test = scaler.transform(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "b265be6c-1532-47cb-abb0-a9ed795b7b88",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best k: 20\n"
+     ]
+    }
+   ],
+   "source": [
+    "best_k = 1\n",
+    "best_score = 0\n",
+    "for k in range(1, 21):\n",
+    "    knn = KNeighborsClassifier(n_neighbors=k)\n",
+    "    scores = cross_val_score(knn, X_train, y_train, cv=2, scoring='f1_weighted')\n",
+    "    avg_score = scores.mean()\n",
+    "    if avg_score > best_score:\n",
+    "        best_score = avg_score\n",
+    "        best_k = k\n",
+    "\n",
+    "print(f'Best k: {best_k}')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "a9122f4d-5c91-4b99-ac10-9169d22c857d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: black;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  max-height: 0;\n",
+       "  max-width: 0;\n",
+       "  overflow: hidden;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  max-height: 200px;\n",
+       "  max-width: 100%;\n",
+       "  overflow: auto;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 1ex;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=20)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;KNeighborsClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.neighbors.KNeighborsClassifier.html\">?<span>Documentation for KNeighborsClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>KNeighborsClassifier(n_neighbors=20)</pre></div> </div></div></div></div>"
+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=20)"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "knn_best = KNeighborsClassifier(n_neighbors=best_k)\n",
+    "knn_best.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "9b2dafc7-9d6a-4bf6-b796-b4777111e26e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "y_pred = knn_best.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "dff4324d-65e1-4a04-9cb8-3f9ac8b1c7d4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "accuracy = accuracy_score(y_test, y_pred)\n",
+    "f1 = f1_score(y_test, y_pred, average='weighted', zero_division=1)\n",
+    "precision = precision_score(y_test, y_pred, average='weighted', zero_division=1)\n",
+    "recall = recall_score(y_test, y_pred, average='weighted', zero_division=1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "cfcf0ed2-9ae5-474c-9286-a701595e1fa8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "F1-score: 0.6957\n",
+      "Accuracy: 0.6956\n",
+      "Precision: 0.6958\n",
+      "Recall: 0.6956\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f'F1-score: {f1:.4f}')\n",
+    "print(f'Accuracy: {accuracy:.4f}')\n",
+    "print(f'Precision: {precision:.4f}')\n",
+    "print(f'Recall: {recall:.4f}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "f67b20e9-8762-4448-a08b-0a4e07691be8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import confusion_matrix\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "cm = confusion_matrix(y_test, y_pred)\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(y_test), yticklabels=np.unique(y_test))\n",
+    "\n",
+    "plt.title('Confusion Matrix')\n",
+    "plt.xlabel('Predicted Labels')\n",
+    "plt.ylabel('True Labels')\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04224305-1f55-482f-98b0-b12d5555ff69",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/NON IITK/Final Task/SukaranIITBHU/mutagenicity_kNN.csv b/NON IITK/Final Task/SukaranIITBHU/mutagenicity_kNN.csv
new file mode 100644
index 00000000..90a77189
--- /dev/null
+++ b/NON IITK/Final Task/SukaranIITBHU/mutagenicity_kNN.csv	
@@ -0,0 +1,5765 @@
+,Id,CAS,SMILES,Status,Experimental value,Predicted value,NumValenceElectrons,qed,TPSA,MolMR,BalabanJ,BertzCT,MolWt,MolLogP
+0,1,100-00-5,O=[N+]([O-])c1ccc(cc1)Cl,Training,1,1,52,0.46360210314198946,43.14,38.106400000000015,3.003400684579817,244.42965837655686,157.55599999999998,2.2482000000000006
+1,2,100-01-6,O=[N+]([O-])c1ccc(N)cc1,Training,1,1,52,0.35954360900709126,69.16,37.50880000000001,3.003400684579818,242.4296583765568,138.126,1.1769999999999998
+2,3,100-02-7,O=[N+]([O-])c1ccc(O)cc1,Training,0,1,52,0.47072821158342537,63.370000000000005,34.76120000000001,3.003400684579818,241.67477087439332,139.10999999999999,1.3003999999999998
+3,4,100-11-8,O=[N+]([O-])c1ccc(cc1)CBr,Training,1,0,58,0.43258614238048154,43.14,45.72740000000002,2.9138015626758045,257.6480131294879,216.03399999999996,2.489700000000001
+4,5,100-12-9,O=[N+]([O-])c1ccc(cc1)CC,Training,0,0,58,0.4797851049380659,43.14,42.474400000000024,2.9138015626758045,253.2994975838911,151.16499999999996,2.1572000000000005
+5,6,100129-07-5,O=C(N(C)Cc1ccccc1)C(C)Br,Training,0,0,76,0.7604223635937938,20.310000000000002,61.305000000000035,2.57468798373919,297.41565806557145,256.143,2.428400000000001
+6,7,100-13-0,O=[N+]([O-])c1ccc(C=C)cc1,Training,1,0,56,0.47766014176858135,43.14,43.18740000000002,3.000886645997868,276.6484617329528,149.149,2.2378
+7,8,100-14-1,O=[N+]([O-])c1ccc(cc1)CCl,Training,1,1,58,0.38948169603836147,43.14,42.65340000000002,2.9138015626758045,257.6480131294879,171.58299999999997,2.3336000000000006
+8,9,100-15-2,O=[N+]([O-])c1ccc(cc1)NC,Training,1,1,58,0.5172807562124302,55.17,42.64310000000002,2.9138015626758045,255.64801312948788,152.15299999999996,1.6364999999999996
+9,10,100-16-3,O=[N+]([O-])c1ccc(cc1)NN,Training,1,1,58,0.3751167479723402,81.19,40.90650000000001,2.9138015626758045,257.0348350774007,153.14099999999996,0.8803999999999998
+10,11,100-17-4,O=[N+]([O-])c1ccc(OC)cc1,Training,1,1,58,0.4786228959968398,52.370000000000005,39.64840000000002,2.9138015626758036,254.89312562732442,153.137,1.6034
+11,12,100-19-6,O=C(c1ccc(cc1)[N+](=O)[O-])C,Training,1,1,62,0.381035510605069,60.209999999999994,43.10090000000002,3.006149833729547,282.57978715700074,165.14799999999997,1.7973999999999999
+12,13,100-20-9,O=C(c1ccc(cc1)C(=O)Cl)Cl,Training,1,1,62,0.6913536643201288,34.14,46.80900000000001,3.006149833729547,283.3346746591642,203.02399999999997,2.4446000000000003
+13,14,100-21-0,O=C(O)c1ccc(cc1)C(=O)O,Training,0,0,62,0.6889088084368349,74.6,40.360600000000005,3.006149833729547,279.3346746591642,166.13199999999998,1.083
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+746,748,117929-15-4,O=[N+]([O-])c1cc2ccc3cc(cc4ccc(c1)c2c34)[N+](=O)[O-],Training,1,1,106,0.31104141056791274,86.28,83.45480000000005,2.2114813277602607,934.0603402813747,292.25,4.400400000000002
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+748,750,118326-90-2,c1cc(cc2C=CC3CCCCC3(c12))Br,Training,0,1,78,0.6332491845043108,0.0,67.87500000000003,2.0514474434635965,405.79976931784324,263.17799999999994,4.749700000000003
+749,751,118326-95-7,O(c1ccc2C=CC3CCCCC3(c2(c1)))C,Training,1,1,84,0.6863471435133849,9.23,66.72700000000003,2.0301329309728473,419.44316998312087,214.30799999999996,3.9958000000000036
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+751,753,118354-50-0,O(c1ccc2c(c1)C4CCCCC4(C3OC23))C,Training,0,0,90,0.6894154817626444,21.759999999999998,65.30700000000004,1.8084965272439422,454.2350837372882,230.30699999999996,3.422500000000002
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+769,771,118-82-1,Oc1c(cc(cc1C(C)(C)C)Cc2cc(c(O)c(c2)C(C)(C)C)C(C)(C)C)C(C)(C)C,Training,0,0,172,0.5145236178392886,40.46,133.8196,2.7336535006709797,802.6777478129438,424.66900000000027,7.878600000000009
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+774,776,118995-83-8,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CSC(=O)NCCCCl,Training,1,0,154,0.15728908190256774,187.92,98.61510000000003,4.650039079494198,549.5588612529018,426.87900000000013,-1.0641999999999974
+775,777,118995-84-9,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CSC(=O)NC(C)(C)C,Training,0,1,154,0.2671396105712138,187.92,98.16410000000005,4.793495607499502,577.0029631430282,406.4610000000001,-0.8945999999999972
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+777,779,1191-41-9,O=C(OCC)CCCCCCCC=CCC=CCC=CCC,Training,1,0,126,0.2187918771626433,26.3,95.89700000000006,3.266316512027962,326.59894558993125,306.49,6.139000000000007
+778,780,119143-41-8,OC3C=Cc2ccc1ncccc1c2C3(O),Training,0,1,80,0.6993314328514519,53.35000000000001,61.74360000000003,2.3730189773978214,577.1543443266695,213.23600000000002,1.6558999999999997
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+780,782,119143-43-0,n1cccc2c1ccc3c2C4OC4(CC3),Training,1,0,74,0.6064799515117929,25.42,57.678000000000026,2.0938640640786232,549.2272921324729,197.23699999999997,2.6209000000000007
+781,783,119-15-3,O=[N+]([O-])c2ccc(Nc1ccc(O)cc1)c(c2)[N+](=O)[O-],Training,1,1,102,0.5026447751149442,118.54000000000002,71.14030000000001,2.378017974613423,669.2930539431334,275.22,2.9522000000000004
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+810,812,119-75-5,O=[N+]([O-])c2ccccc2(Nc1ccccc1),Training,0,1,80,0.6293026950858532,55.17,62.82110000000003,2.314817218585019,497.38176398410803,214.224,3.338400000000001
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+815,817,119-90-4,O(c1cc(ccc1(N))c2ccc(N)c(OC)c2)C,Training,1,1,94,0.8138408001470395,70.5,73.80680000000002,2.480232986164691,516.2156041118582,244.29399999999998,2.5352000000000006
+816,818,119914-60-2,O=C(O)C1=CN(c2cc(c(F)c(c2(C1(=O)))C)N3CCNC(C)C3)C4CC4,Training,0,1,138,0.8795000805170116,74.57,97.81100000000005,1.989710836558867,964.8812880676296,359.4010000000001,2.28022
+817,819,1199-18-4,Oc1cc(O)c(cc1(O))CCN,Training,1,0,66,0.3786864988605503,86.71,44.194800000000015,3.0517048471500963,285.87661626856533,169.17999999999995,0.30459999999999987
+818,820,119-93-7,Nc1ccc(cc1C)c2ccc(N)c(c2)C,Training,1,1,82,0.7133911900621517,52.04,70.17680000000001,2.5020803743746223,480.75370517390644,212.296,3.1348400000000014
+819,821,119979-38-3,O=C(OCc1ccccc1[N+](=O)[O-])CCC,Training,0,0,86,0.4364101546772435,69.44,57.80040000000003,2.663059476079085,389.3258818636124,223.22799999999992,2.4381000000000004
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+822,824,120042-14-0,[N-]=[N+]=NCCC(N)C(=O)O,Training,1,1,56,0.3310506253198123,112.08,34.24119999999999,3.4839751938116463,162.64052645972987,144.13400000000001,0.09869999999999984
+823,825,120143-20-6,[N-]=[N+]=NCCC(N)C(=O)O,Training,1,1,56,0.3310506253198123,112.08,34.24119999999999,3.4839751938116463,162.64052645972987,144.13400000000001,0.09869999999999984
+824,826,120-14-9,O=Cc1ccc(OC)c(OC)c1,Training,0,0,64,0.6383852121799835,35.53,44.933500000000016,3.097737020758659,281.102178757748,166.176,1.5163
+825,827,120209-97-4,n1c3ccc(N)cc3(nc2ccc(N)cc12),Training,1,1,78,0.43881967405074745,77.82,65.86880000000001,2.435946576710954,629.4788965680244,210.24,1.9473999999999998
+826,828,120-22-9,O=Nc1ccc(cc1)N(CC)CC,Training,1,1,70,0.6638676317146944,32.67,55.458000000000034,2.8334708502688457,264.7581641533625,178.23499999999996,2.9307000000000016
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+828,830,120302-30-9,O=[N+]([O-])c1ccc2c(c1)[nH]cc2CCO,Training,1,1,78,0.5910435912136176,79.16,55.74290000000002,2.512933411861634,504.33685186656965,206.20099999999996,1.6108999999999993
+829,831,120314-14-9,O=Nn2cc(c1ccccc12)CCO,Training,1,1,72,0.748775046254697,54.59,53.92080000000003,2.663825324793996,462.0899797257961,190.20199999999997,1.7055999999999998
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+833,835,120388-69-4,O=Nc1ccc2ccc4c5ccccc5(cc3ccc1c2c34),Training,1,1,102,0.2061416820820953,29.43,93.10700000000003,2.1811781282692446,1190.1982587252537,281.3140000000001,6.135100000000003
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+835,837,120404-26-4,OCCNc2ccc(N=Nc1ccc(cc1)NCCO)cc2,Training,1,0,116,0.5643187832951836,89.24,88.21100000000003,1.9275871762553312,528.5997307098642,300.362,2.9104
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+837,839,1204-41-7,Nc1ccc(cc1)c2ccccc2C,Training,1,1,70,0.6746642883886572,26.02,61.02740000000002,2.498254962562555,429.2434804109701,183.254,3.244220000000002
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+839,841,1204-68-8,c1cc(ccc1N(CCCl)CCCl)C,Training,0,1,78,0.70395704265654,3.24,64.83200000000002,2.708634541407956,252.49497088267702,232.15399999999997,3.279020000000002
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+841,843,120-52-5,O=C(ON=C2C=CC(=NOC(=O)c1ccccc1)C=C2)c3ccccc3,Training,1,1,128,0.48188640599202487,77.32,96.865,1.5553012244528255,819.8420722949135,346.34200000000004,3.538400000000002
+842,844,120-57-0,O=Cc1ccc2OCOc2(c1),Training,0,0,56,0.5645624802089623,35.53,37.95250000000001,2.483389643538051,293.3886867286258,150.13299999999998,1.2278
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+844,846,120-62-7,O=S(CCCCCCCC)C(C)Cc1ccc2OCOc2(c1),Training,0,0,124,0.5962773501059656,35.53,92.11640000000007,1.6961850950562678,487.2206544944622,324.4860000000001,4.455500000000004
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+853,855,120812-47-7,O=[N+]([O-])c5ccc3c2c5(ccc1cccc(c12)c4c3CCCC4),Training,1,1,112,0.2692893128834907,43.14,93.44240000000003,2.121782588863524,1097.3759786701924,301.34500000000014,5.371000000000003
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+1020,1022,127183-64-6,[O-][n+]2onc1nc(N)ccc12,Training,1,1,56,0.5104994632331474,91.88,35.17640000000001,2.85649595116269,396.28178972761,152.113,-0.5616000000000003
+1021,1023,127-18-4,C(=C(Cl)Cl)(Cl)Cl,Training,0,0,36,0.51797640201532,0.0,30.438000000000002,3.675948764555208,55.617270614347476,165.834,3.0682
+1022,1024,127-19-5,O=C(N(C)C)C,Training,0,0,36,0.40990688283686283,20.310000000000002,24.36799999999999,3.2575861612334887,58.568425030288566,87.12199999999999,0.0944999999999998
+1023,1025,127-47-9,O=C(OCC=C(C=CC=C(C=CC1=C(C)CCCC1(C)C)C)C)C,Training,0,0,132,0.4359975230778408,26.3,102.75900000000006,2.665028163801521,595.459454640942,328.49600000000004,6.081100000000006
+1024,1026,127502-69-6,Nc1ccc(cc1C(C)C)c2ccccc2,Training,1,0,82,0.7447153485902291,26.02,70.37940000000003,2.480537679924803,472.0485541980777,211.30800000000002,4.059200000000002
+1025,1027,127-69-5,O=S(=O)(Nc1onc(c1C)C)c2ccc(N)cc2,Training,0,0,96,0.8241959038664723,98.22,67.63990000000003,2.327592361324992,659.3419266315426,267.31,1.6744399999999997
+1026,1028,127-90-2,O(CC(C(Cl)(Cl)Cl)Cl)CC(C(Cl)(Cl)Cl)Cl,Training,1,1,92,0.6292917155488371,9.23,70.68100000000003,3.8132498766279768,164.5513656778549,377.73699999999997,4.958200000000001
+1027,1029,127923-98-2,O=C(OCCBr)C(O)C(O)C(=O)OCCBr,Training,1,1,94,0.4713141257716729,93.06000000000002,61.519600000000025,4.091862173608079,210.5684250302886,363.9860000000001,-0.4156000000000004
+1028,1030,127923-99-3,O=C(OCCBr)CC(O)C(=O)OCCBr,Training,1,1,88,0.5394156525356072,72.83,60.129800000000024,3.7469809087648462,209.208709679732,347.98699999999997,0.6135999999999999
+1029,1031,127924-00-9,O=C(OCCBr)CC(O)(C(=O)OCCBr)CC(=O)OCCBr,Training,1,1,128,0.2530497728787625,99.13000000000001,88.44280000000002,4.831790022477372,353.73138483094755,512.9730000000002,1.3119999999999998
+1030,1032,128-08-5,O=C1N(C(=O)CC1)Br,Training,1,0,44,0.39838419073188525,37.38,30.013999999999996,2.7003421243315966,128.97373660251156,177.98499999999999,0.44530000000000003
+1031,1033,128349-98-4,N#CC(=CC(C)C(c1ccccc1)C(C#N)c2ccc(cc2)Br)c3ccc(cc3)Br,Training,0,0,148,0.3110991745078457,47.58,128.57500000000005,2.052776802386703,1089.0156975513814,520.268,7.845860000000005
+1032,1034,128350-00-5,N#CC(=CC(C)C(c1ccccc1)C(C#N)c2ccc(c(c2)Cl)Cl)c3ccc(c(c3)Cl)Cl,Training,1,0,160,0.3174583311129828,47.58,133.21499999999995,2.093153970708204,1222.8096694660662,500.2560000000001,8.934459999999998
+1033,1035,128350-04-9,N#CC(=CC(C)C(c1ccccc1)C(C#N)c2ccc(F)cc2)c3ccc(F)cc3,Training,0,0,148,0.4392896518871892,47.58,113.09100000000002,2.052776802386703,1089.0156975513814,398.4560000000001,6.599060000000005
+1034,1036,128-37-0,Oc1c(cc(cc1C(C)(C)C)C)C(C)(C)C,Training,0,0,90,0.6909972184662642,20.23,70.24380000000005,3.5078483379345893,353.8715828475769,220.35599999999997,4.295620000000004
+1035,1037,128-39-2,Oc1c(cccc1C(C)(C)C)C(C)(C)C,Training,0,0,84,0.6802500634680616,20.23,65.50680000000004,3.368901573147507,318.331941709556,206.32899999999995,3.987200000000003
+1036,1038,128505-52-2,O=C(O)C(NC(=O)C)CSSC(N(CC)CC)=S,Training,0,0,104,0.5463468534327056,69.64,80.80850000000004,4.097786383589419,308.7430298092722,310.46600000000007,1.5837999999999999
+1037,1039,128531-59-9,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CSSC(N(CC)CC)=S,Training,0,0,160,0.1860791513896466,162.06,112.98940000000005,4.749179685369104,573.9794811002853,454.5960000000002,-0.12779999999999703
+1038,1040,128-66-5,O=C3c1ccccc1c4ccc5C(=O)c2ccccc2c6ccc3c4c56,Training,0,0,120,0.3799719250240367,34.14,101.68500000000002,1.8596065356460607,1208.5989447426757,332.3580000000001,5.2626000000000035
+1039,1041,128714-75-0,O=[N+]([O-])c3ccc1ccc5c2c(ccc3(c12))c4ccccc4c5[N+](=O)[O-],Training,1,1,124,0.18196342363134224,86.28,100.96080000000003,2.179357708746185,1391.290208613586,342.31000000000006,5.553600000000004
+1040,1042,128714-76-1,O=[N+]([O-])c5ccc2ccc3c1ccccc1c(c4ccc5(c2c34))[N+](=O)[O-],Training,1,1,124,0.18196342363134224,86.28,100.96080000000005,2.179729002009055,1391.290208613586,342.3100000000001,5.553600000000002
+1041,1043,128753-82-2,O2OC3(Oc1ccccc1C23(OC))(C),Training,1,1,74,0.6355149240045027,36.92,46.33200000000002,2.1959889541814777,387.4633176285555,194.18599999999995,1.5562
+1042,1044,128753-83-3,O1OC2(c3ccccc3(OC12))(C),Training,1,1,62,0.5446947583883893,27.69,40.38000000000002,2.1929313727138156,336.30046214401995,164.15999999999997,1.5821
+1043,1045,128753-86-6,O=C(c3cccc1c3(OC2(OOC12(C))(C)))C,Training,1,1,84,0.537151340328221,44.760000000000005,55.00150000000003,2.2273414754839114,495.7921695417518,220.22399999999996,2.1748000000000003
+1044,1046,128753-87-7,O1OC2(c3c(OC)cccc3(OC12(C)))(C),Training,1,1,80,0.6611322681617035,36.92,51.54900000000003,2.2232562480151947,430.59614004636614,208.21299999999997,1.9808
+1045,1047,128753-88-8,O1OC2(c3cccc(OC)c3(OC12(C)))(C),Training,1,1,80,0.6611322681617033,36.92,51.54900000000003,2.199220622723114,430.59614004636614,208.21299999999994,1.9808
+1046,1048,128753-90-2,O=C(Oc3ccc1c(OC2(OOC12(C))(C))c3)C,Training,1,1,90,0.4231876394182302,53.99000000000001,56.30600000000003,2.004603750200338,511.61749416507485,236.22299999999996,1.8974999999999997
+1047,1049,128753-91-3,O=C(Oc1ccc2OC3(OOC3(c2(c1))(C))(C))C,Training,1,1,90,0.4231876394182302,53.99000000000001,56.30600000000003,2.0302513829231152,511.61749416507485,236.22299999999996,1.8974999999999997
+1048,1050,128753-93-5,OCC13(OOC3(c2ccccc2(O1))(C)),Training,0,1,74,0.6758613976698089,47.92,46.40880000000003,2.166317947937088,387.46331762855556,194.18599999999998,0.9446000000000001
+1049,1051,128753-94-6,OCC13(OOC3(c2ccccc2(O1))(CO)),Training,0,1,80,0.667943137447941,68.15,47.82060000000003,2.1652348714476877,398.55415076914994,210.18499999999997,-0.08299999999999991
+1050,1052,128753-95-7,O1OC2(c3ccccc3(OC12(COC)))(C),Training,1,1,80,0.6916024966516049,36.92,51.19900000000003,2.0746049271831333,405.32932438745,208.21299999999994,1.5987
+1051,1053,128753-96-8,O=C(OCC13(OOC3(c2ccccc2(O1))(C)))C,Training,1,1,90,0.5752158663575028,53.99000000000001,55.95600000000003,1.9337122610893422,485.53926173289534,236.22299999999998,1.5154
+1052,1054,128753-99-1,O=C(OCC13(OOC3(c2ccccc2(O1))(C)))Nc4ccc(cc4)Cl,Training,1,1,124,0.8540646180197633,66.02000000000001,85.74570000000003,1.4307719503063443,795.8228405426358,347.754,3.8544000000000027
+1053,1055,128946-65-6,O=CC=CC(O)CCCCC,Training,0,1,64,0.36071086981830164,37.3,45.35280000000002,3.2820573313511776,118.731140660285,156.225,1.6826999999999999
+1054,1056,128-95-0,O=C1c3ccccc3(C(=O)c2c(N)ccc(N)c12),Training,1,1,88,0.5826021477539957,86.17999999999999,68.5738,2.409415066945445,644.9353339687133,238.24599999999995,1.6264
+1055,1057,129018-59-3,O=[N+]([O-])c2nc1ncc(cc1n2C)c3ccccc3,Training,1,1,94,0.5199645401809315,73.85,70.59940000000002,2.210736739353802,764.9141944752428,254.24900000000002,2.5435000000000008
+1056,1058,129-03-3,c1ccc3c(c1)C=Cc2ccccc2C3=C4CCN(C)CC4,Training,0,0,110,0.5791645622326818,3.24,94.56500000000005,1.9631480815500684,705.4815373524832,287.40600000000006,4.697900000000005
+1057,1059,129-09-9,O=C5c7ccc2nc(c1ccccc1)sc2c7(C(=O)c6ccc4nc(c3ccccc3)sc4c56),Training,0,1,160,0.2702385666847766,59.92,136.9769999999999,1.4295447828835794,1650.4863748961964,474.5660000000002,7.015400000000004
+1058,1060,129117-54-0,O(c1ccc2[nH]c3c(cc(N)c(c3(c2(c1)))C)C)C,Training,1,1,92,0.6391972107940347,51.04,76.24310000000004,2.5403809725875615,756.1049639266773,240.30599999999998,3.5287400000000018
+1059,1061,129134-96-9,c3cc1c4c(cn1C2CCCC2)CC5N(C)CC(C)CC5(c4(c3)),Training,1,1,122,0.7387333275416295,8.17,96.08700000000006,1.672189398662396,737.6246809345752,308.469,4.7363000000000035
+1060,1062,129-15-7,O=C2c3ccccc3(C(=O)c1c2(ccc(c1[N+](=O)[O-])C)),Training,1,1,98,0.5013315018102388,77.28,71.14040000000001,2.39631881057486,792.4556772603132,267.23999999999995,2.6786200000000013
+1061,1063,129176-04-1,O1C(CBr)C1Cl,Training,1,1,36,0.4284959677573261,12.53,28.307999999999993,2.093910515440877,56.75488750216347,171.421,1.345
+1062,1064,129401-88-3,O=C(C=C)N2CCN(c1ccccc1)CC2,Training,0,0,84,0.6997622069687346,23.550000000000004,65.43200000000003,1.9535262161839506,366.77880083495194,216.28400000000002,1.5211999999999999
+1063,1065,129-43-1,O=C1c3ccccc3(C(=O)c2c(O)cccc12),Training,1,1,82,0.6362663133133345,54.370000000000005,61.41380000000002,2.3740939300606247,656.2669402785393,224.21499999999997,2.1675999999999993
+1064,1066,129-44-2,O=C1c3cccc(N)c3(C(=O)c2cccc(N)c12),Training,1,1,88,0.5826021477539957,86.18,68.5738,2.3954686409277963,643.4353339687134,238.24599999999998,1.6263999999999998
+1065,1067,129665-16-3,[O-][n+]4c5ccccc5(c1ccc2cccc3ccc4(c1c23)),Training,1,1,98,0.17737560779437653,26.939999999999998,86.61200000000004,2.2577078741048795,1128.2781068635381,269.30300000000005,4.370600000000002
+1066,1068,129-73-7,c1ccc(cc1)C(c2ccc(cc2)N(C)C)c3ccc(cc3)N(C)C,Training,0,1,128,0.6075387118035775,6.48,108.92500000000005,2.036714152805076,736.2611633458829,330.475,4.998800000000005
+1067,1069,129-79-3,O=C3c1cc(ccc1c2c3(cc(cc2[N+](=O)[O-])[N+](=O)[O-]))[N+](=O)[O-],Training,1,1,114,0.532561979950938,146.49,75.2737,2.344536319023847,935.4056578215543,315.19700000000006,2.622600000000002
+1068,1070,129812-24-4,O=C2Oc1cc3OC4(OOC4(c3(cc1C(=C2)C))(C))(C),Training,1,1,98,0.5373910089376743,57.900000000000006,65.77600000000002,2.06386660849842,777.2353650581198,260.24499999999995,2.3870200000000006
+1069,1071,129812-26-6,O=C3Oc2ccc1OC4(OOC4(c1c2C(=C3)C)(C))(C),Training,1,1,98,0.5373910089376743,57.900000000000006,65.77600000000002,2.1553751970827375,777.2353650581198,260.24499999999995,2.3870200000000006
+1070,1072,129812-29-9,O1OC2(c4c(OC12(C))ccc3ccccc34)(C),Training,0,1,86,0.6482386464329866,27.69,62.50300000000003,2.1085691806871094,636.3999689602875,228.24699999999999,3.1254000000000017
+1071,1073,129812-30-2,n3cccc4ccc1c(OC2(OOC12(C))(C))c34,Training,0,1,86,0.6507097426518721,40.58,60.29800000000003,2.072941233903075,641.5972215332599,229.23499999999996,2.5204000000000004
+1072,1074,129833-00-7,O=C2Oc1c3OC4(OOC4(c3(ccc1C(=C2)C))(C))(C),Training,1,1,98,0.5373910089376744,57.900000000000006,65.77600000000002,2.113446419522451,777.2353650581198,260.245,2.3870200000000006
+1073,1075,129833-02-9,O=C2c3ccccc3(C=CC12(OC1(C(=O)C)(C))),Training,0,0,86,0.6906391342418033,46.67,62.70850000000003,2.1142311325544925,572.5849838410452,228.24699999999996,2.0128
+1074,1076,129833-03-0,O=C3C=Cc1ccccc1C23(OC2(C(=O)C)(C)),Training,0,0,86,0.6890675808183143,46.67,62.33200000000003,2.2299503327374843,572.5849838410452,228.24699999999996,1.8557
+1075,1077,129927-33-9,O=C(OC(C#CCN(CC)CC)(C)C)C(O)(c1ccccc1)C2CCCCC2,Training,0,0,154,0.56652884860089,49.769999999999996,112.64880000000008,2.213983290871663,678.7969663314964,385.54800000000023,4.121500000000003
+1076,1078,129927-37-3,O=C(OC(C#CCNCC)(C)C)C(O)(c1ccccc1)C2CCCCC2,Training,0,0,142,0.46543441766897,58.56,103.40450000000006,2.2389893432301102,638.3463606882913,357.4940000000002,3.3892000000000015
+1077,1079,130005-62-8,Oc1ccc2[nH]c3c(cc(N)c(c3(c2(c1)))C)C,Training,1,1,86,0.5152305095149051,62.03999999999999,71.35590000000002,2.6274156668089383,740.8868760035249,226.27899999999997,3.225740000000001
+1078,1080,130-01-8,O=C1OC3CCN2CC=C(COC(=O)C(O)(C)C(C)CC1(=CC))C23,Training,0,1,132,0.40712016822519426,76.07,87.06180000000003,1.9091153937877579,606.5303777006083,335.4000000000001,1.1927999999999994
+1079,1081,130040-14-1,O=C(N(O)c1ccc(cc1)Sc2ccccc2)C,Training,1,1,92,0.6762535974818112,40.540000000000006,71.95350000000003,2.108917162710057,525.2500720764084,259.33000000000004,3.579900000000002
+1080,1082,13007-92-6,[C-]#[O+],Training,0,1,10,0.26218825573102733,19.9,3.9295,3.0,6.754887502163469,28.009999999999998,-0.03751
+1081,1083,13010-07-6,O=NN(C(=N)N[N+](=O)[O-])CCC,Training,1,1,68,0.20665135416411978,111.69,40.648800000000016,4.0205449666073685,193.13235378876152,175.14799999999997,0.0958699999999999
+1082,1084,13010-08-7,O=NN(C(=N)N[N+](=O)[O-])CCCC,Training,1,1,74,0.2146607842046341,111.69,45.26580000000001,3.98817029086805,206.34653910483817,189.17499999999995,0.4859699999999998
+1083,1085,13010-10-1,O=NN(C(=N)N[N+](=O)[O-])CCCCC,Training,1,1,80,0.16602767476191407,111.69,49.88280000000002,3.925695915917304,219.51251590650185,203.20199999999994,0.8760699999999999
+1084,1086,13010-47-4,O=NN(C(=O)NC1CCCCC1)CCCl,Training,1,1,86,0.4599613459771248,61.77,58.62570000000003,2.341813687064413,219.4029963976061,233.69899999999993,2.2509000000000006
+1085,1087,130-13-2,O=S(=O)(O)c2ccc(N)c1ccccc12,Training,0,0,78,0.5688803218109532,80.39,58.17500000000002,2.961958871524338,619.6001475530924,223.253,1.6687
+1086,1088,13014-18-1,c1cc(c(cc1Cl)Cl)C(Cl)(Cl)Cl,Training,1,1,66,0.5892629493246923,0.0,55.69900000000001,3.1892115119016715,288.338476501266,264.366,4.820100000000001
+1087,1089,13014-24-9,c1cc(c(cc1C(Cl)(Cl)Cl)Cl)Cl,Training,1,1,66,0.5892629493246924,0.0,55.69900000000001,3.138261335720988,288.338476501266,264.366,4.8201
+1088,1090,130-15-4,O=C1C=CC(=O)c2ccccc12,Training,1,1,58,0.5745508411642769,34.14,44.243000000000016,2.6926206830292423,351.5799823181129,158.156,1.6218000000000001
+1089,1091,13024-49-2,Nc1ccc(cc1)CCc2ccccc2,Training,1,1,76,0.7518221740803689,26.02,64.70440000000002,1.964224847715407,403.11365079834786,197.28100000000003,3.054000000000001
+1090,1092,130-26-7,Oc2c1ncccc1c(cc2I)Cl,Training,0,0,66,0.7583081059543383,33.120000000000005,61.13480000000001,2.966872933924146,472.3665095200525,305.50199999999995,3.1984000000000004
+1091,1093,13048-33-4,O=C(OCCCCCCOC(=O)C=C)C=C,Training,0,0,90,0.342622834939384,52.6,60.78000000000003,3.15307708526317,219.40331533468293,226.27199999999996,2.0052000000000003
+1092,1094,130536-37-7,n1cccc2c1C=CC3OC23,Training,0,0,54,0.5173459339900319,25.42,40.88500000000002,2.2378938315462826,332.08954744253975,145.16099999999997,1.5483
+1093,1095,130536-38-8,OC2C=Cc1ncccc1C2(O),Training,0,0,62,0.5853067841372052,53.35000000000001,44.23760000000002,2.515554619594146,322.0595034459553,163.176,0.5026999999999999
+1094,1096,130536-40-2,OC2C=Cc1cccnc1C2(O),Training,0,0,62,0.5853067841372052,53.35000000000001,44.23760000000002,2.515554619594146,322.0595034459553,163.176,0.5026999999999999
+1095,1097,130536-45-7,n1cccc2c1CCC3OC23,Training,0,0,56,0.519055597955803,25.42,40.17200000000001,2.1434653084546422,297.36913671997195,147.177,1.4677
+1096,1098,130536-46-8,n1cccc2c1C3OC3(CC2),Training,0,0,56,0.5190555979558029,25.42,40.17200000000001,2.1434653084546422,297.36913671997195,147.17699999999996,1.4677
+1097,1099,13060-14-5,O(c1cc(cc(OC)c1(OC))C2OCC3C(OCC23)c4cc(OC)c(OC)c(OC)c4)C,Training,0,0,174,0.6061481558353083,73.84000000000002,116.56200000000007,1.6387979238659036,831.5007764907035,446.4960000000002,3.8134000000000023
+1098,1100,13071-79-9,O(CC)P(OCC)(=S)SCSC(C)(C)C,Training,0,0,92,0.5052290262688,18.46,77.33900000000004,4.018684248799225,205.89322139327916,288.44,4.506300000000004
+1099,1101,130796-74-6,OCC5OC(n2cnc1c(ncnc12)NCC(O)COc3cccc4ccccc34)C(O)C5(O),Training,0,1,178,0.24651249389766075,155.01,122.27190000000002,1.2554623108034872,1277.9288340023013,467.4820000000002,0.44279999999999947
+1100,1102,130-80-3,O=C(Oc1ccc(cc1)C(=C(c2ccc(OC(=O)CC)cc2)CC)CC)CC,Training,0,0,148,0.3177881072568975,52.6,112.13200000000006,2.309808485946195,758.4137995516293,380.48400000000015,6.048200000000005
+1101,1103,13088-34-1,O=C1OC(C=C1)=C(Cl)Cl,Training,1,1,48,0.5106834564940519,26.3,33.964000000000006,2.831503833923838,201.0035345171666,164.975,1.7460999999999998
+1102,1104,130933-91-4,OC4c2ccc1c6C=Cc5cccc(cc1c2C3OC3C4(O))c56,Training,1,1,112,0.3868531148910159,52.989999999999995,88.96260000000002,1.7859374966359487,1049.8606430505138,302.329,3.3246000000000024
+1103,1105,130942-88-0,O=S(=O)(O)OCc3c1ccccc1c(c2ccccc23)C,Training,1,1,108,0.5926235127264717,63.60000000000001,82.52860000000005,2.3443577406198037,872.5632858742911,302.35100000000006,3.620820000000003
+1104,1106,130965-73-0,O=S(=O)(O)OCc1ccc2ccc3cccc4ccc1c2c34,Training,1,1,110,0.460090677204328,63.60000000000001,86.48360000000005,2.0377288249089993,1084.0100516237553,312.34600000000006,3.903400000000002
+1105,1107,13098-39-0,O=C(C(F)(F)F)C(F)(F)F,Training,0,0,60,0.5000308573930615,17.07,17.117,4.398990539719588,124.05236848565261,166.01999999999998,1.6801
+1106,1108,13104-21-7,O=P(OC(=CBr)c1ccc(cc1Cl)Cl)(OC)OC,Training,0,0,100,0.529827237441119,44.760000000000005,76.07550000000003,3.0869938947634066,498.65108862749366,375.97000000000014,5.104200000000003
+1107,1109,13107-39-6,O1CC1c2ccc(cc2)C,Training,1,1,52,0.5354720425966161,12.53,39.872000000000014,2.2754725699762357,220.9885115579334,134.17799999999997,2.06632
+1108,1110,13109-99-4,O=C2N(c1ncc([N+](=O)[O-])s1)CCC2,Training,1,1,74,0.5455811334505264,76.34,50.35540000000002,2.239359176285779,389.28666821012797,213.21799999999996,1.1781
+1109,1111,131-11-3,O=C(OC)c1ccccc1(C(=O)OC),Training,0,0,74,0.6648651607326014,52.60000000000001,49.12100000000002,3.153839931025287,321.89456038916694,194.18599999999995,1.2597999999999998
+1110,1112,131119-01-2,O=C(O)c2c1ccccc1n(c2CC(=O)OCCCl)C,Training,1,0,106,0.6780702875063851,68.53,75.26130000000003,2.4600998472847655,662.4828102473567,295.7219999999999,2.2010000000000005
+1111,1113,131119-02-3,O=C(OCCCl)c1c3c(nn[n+]1([O-]))c2ccccc2n3C,Training,1,1,108,0.3135675710679231,83.94999999999999,75.97750000000003,2.327725104029888,846.1603272597214,306.70900000000006,1.1504999999999999
+1112,1114,131-12-4,O=C1Oc2c3ccoc3(c(OC)c(OC)c2(C=C1)),Training,0,0,92,0.6500843101672217,61.81,65.36000000000003,2.626995649459891,781.017111466773,246.21799999999996,2.5564
+1113,1115,131-14-6,O=C1c3ccc(N)cc3(C(=O)c2ccc(N)cc12),Training,1,1,88,0.5826021477539957,86.18,68.5738,2.314758854452267,643.4353339687133,238.24599999999998,1.6264
+1114,1116,13114-72-2,O=C(NC)N(c1ccccc1)c2ccccc2,Training,0,0,86,0.8377166953342596,32.34,69.47870000000003,2.4314397275890385,442.5901008873748,226.27900000000002,3.1641000000000012
+1115,1117,131-17-9,O=C(OCC=C)c1ccccc1(C(=O)OCC=C),Training,0,0,94,0.5708799506503206,52.60000000000001,67.40100000000002,2.907709957142368,419.61672525206325,246.26199999999994,2.3722000000000003
+1116,1118,131229-60-2,O=C(ON(OCCCC)C(=O)c1ccc(OC)cc1)C,Training,1,1,110,0.5912571072956787,65.07,71.78950000000005,2.75908628325545,443.3824143868275,281.308,2.3472
+1117,1119,131229-61-3,O=C(ON(OCCCC)C(=O)c1ccc(cc1)C)C,Training,1,1,104,0.6063665578736995,55.839999999999996,69.97450000000003,2.7432920686821327,427.5770341177843,265.309,2.6470200000000013
+1118,1120,131229-62-4,O=C(ON(OCCCC)C(=O)c1ccc(cc1)Cl)C,Training,1,1,104,0.6163255394157399,55.839999999999996,70.24750000000003,2.7432920686821327,432.7742866907566,285.72700000000003,2.9920000000000018
+1119,1121,131229-63-5,O=C(ON(OCCCC)C(=O)c1ccc(cc1)Br)C,Training,1,1,104,0.614873626345248,55.839999999999996,72.93750000000003,2.7432920686821327,432.7742866907566,330.17800000000005,3.1011000000000015
+1120,1122,131229-64-6,O=C(ON(OCCCC)C(=O)c1ccc(cc1)[N+](=O)[O-])C,Training,1,1,114,0.45326002916784514,98.97999999999999,71.89190000000002,2.820550975130386,513.8976994651861,296.27900000000005,2.2468000000000004
+1121,1123,13132-28-0,O=[N+]([O-])C3=Cc2cccc1cccc3(c12),Training,1,1,72,0.5206872649937236,43.14,58.813400000000016,2.4498727114513374,608.7982708114702,197.19299999999998,2.928000000000001
+1122,1124,13147-25-6,O=NN(CC)CCO,Training,1,1,48,0.4166984595955861,52.900000000000006,30.127799999999986,3.2078392351792973,67.05865002596163,118.136,-0.01799999999999996
+1123,1125,131524-41-9,C#CCOCC[n+]1ccccc1(C=NO),Training,0,0,78,0.18914723053545698,45.7,55.66950000000002,2.559671707338352,369.0958253198426,205.23700000000002,0.43199999999999955
+1124,1126,131-53-3,O=C(c1ccccc1(O))c2ccc(OC)cc2(O),Training,1,1,92,0.8130923616212106,66.76,66.19810000000003,2.4379753004221536,590.0979048590729,244.24599999999998,2.337400000000001
+1125,1127,13154-57-9,O=C1C(=CC(OOC(C)(C)C)(C=C1C(C)(C)C)C)C(C)(C)C,Training,0,0,126,0.5305599968605096,35.53,90.41100000000006,3.3166880597521504,468.26906040867914,308.46200000000005,5.019500000000005
+1126,1128,13164-04-0,O=C1Oc2cc3OC(Cc3(cc2(C=C1C(C=C)(C)C)))C(O)(C)C,Training,1,1,122,0.6971440568548795,59.67,90.12480000000004,2.125442128590448,836.7940397022579,314.38100000000003,3.331000000000002
+1127,1129,13171-00-1,O=C(c1cc(cc2c1CCC2(C)C)C(C)(C)C)C,Training,0,0,98,0.6686858427701448,17.07,76.49350000000005,2.710745229436513,501.07675664304514,244.37799999999996,4.410500000000004
+1128,1130,13171-21-6,O=C(C(=C(OP(=O)(OC)OC)C)Cl)N(CC)CC,Training,1,1,106,0.4107081327861798,65.07000000000001,69.19050000000003,5.01806028081648,359.2795397887988,299.69100000000003,2.7426000000000013
+1129,1131,131-73-7,O=[N+]([O-])c2cc(c(Nc1c(cc(cc1[N+](=O)[O-])[N+](=O)[O-])[N+](=O)[O-])c(c2)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,160,0.4576602059418498,270.86999999999995,96.0931,2.9268661651154635,1030.9356650363045,439.20900000000023,2.879400000000002
+1130,1132,13177-25-8,Nc2ccc3cccc4c1ccccc1c2c34,Training,1,1,80,0.4413478987641275,26.02,72.79040000000002,2.326435797245274,756.5650785276885,217.271,4.069400000000002
+1131,1133,13177-26-9,Nc2cc3cccc4c1ccccc1c(c2)c34,Training,1,1,80,0.4413478987641275,26.02,72.79040000000002,2.295537546023585,756.5650785276885,217.271,4.069400000000002
+1132,1134,13177-27-0,Nc1cccc2c4cccc3cccc(c12)c34,Training,1,1,80,0.4413478987641275,26.02,72.79040000000002,2.306938940056878,751.3150785276883,217.271,4.069400000000002
+1133,1135,13177-28-1,O=[N+]([O-])c4ccc2cccc3c1ccccc1c4(c23),Training,1,1,90,0.36942414737519014,43.14,75.03240000000002,2.2794628853117755,852.4919023615512,247.253,4.395400000000002
+1134,1136,13177-29-2,O=[N+]([O-])c2cc3cccc4c1ccccc1c(c2)c34,Training,1,1,90,0.36942414737519014,43.14,75.03240000000002,2.214844090013318,852.4919023615512,247.253,4.395400000000002
+1135,1137,13177-31-6,O=[N+]([O-])c4cccc3c2cccc1cccc(c12)c34,Training,1,1,90,0.36942414737519014,43.14,75.03240000000004,2.2397047631191462,847.2419023615513,247.253,4.395400000000002
+1136,1138,13177-32-7,O=[N+]([O-])c1ccc2c4cccc3cccc(c2(c1))c34,Training,1,1,90,0.36942414737519014,43.14,75.03240000000002,2.1434118583571613,847.2419023615512,247.253,4.395400000000001
+1137,1139,131862-15-2,O=C(NCCN(C)C)c3cccc2c3(ncc1ccccc12),Training,1,1,112,0.7522609255785978,45.230000000000004,90.13620000000004,1.9990564811775586,826.794748692241,293.37000000000006,2.679400000000001
+1138,1140,131862-17-4,O=C(NCCN(C)C)c2cc1ccccc1c3cccnc23,Training,1,1,112,0.7522609255785978,45.230000000000004,90.13620000000006,2.053930135517587,826.7947486922409,293.37000000000006,2.679400000000001
+1139,1141,131862-18-5,O=C(NCCN(C)C)c1nc3c(cc1)ccc2cccnc23,Training,1,1,112,0.7484696072543549,58.120000000000005,87.93120000000005,1.943598609214132,829.1214179191104,294.35800000000006,2.0744
+1140,1142,131862-19-6,O=C(NCCN(C)C)c2cccc1nc(oc12)c3ccccc3,Training,0,1,118,0.7871387364672704,58.370000000000005,90.33220000000003,1.8946900287850776,809.5045791388817,309.369,2.786200000000001
+1141,1143,131862-20-9,O=C(NCCN(C)C)c2cccc1oc(nc12)c3ccccc3,Training,0,1,118,0.7871387364672704,58.370000000000005,90.33220000000003,1.8946900287850776,809.5045791388817,309.369,2.786200000000001
+1142,1144,131862-21-0,O=C(NCCN(C)C)c1cccn2cc(nc12)c3ccccc3,Training,1,1,118,0.7865999415944925,49.64,91.51520000000004,1.8946900287850776,808.2594666410452,308.38500000000005,2.292700000000001
+1143,1145,131862-22-1,O=C(NCCN(C)C)c2cccc1cc(oc12)c3ccccc3,Training,1,0,118,0.7855995299167868,45.480000000000004,92.53720000000003,1.8946900287850776,806.6074939115787,308.38100000000003,3.391200000000002
+1144,1146,131-91-9,O=Nc2c(O)ccc1ccccc12,Training,0,1,64,0.6737132753463418,49.66,51.06780000000003,2.9117844920054856,465.4314410863231,173.17099999999996,2.9433000000000016
+1145,1147,131-92-0,O=C(Nc7cccc8C(=O)c3c(ccc2c4cc(NC(=O)c1ccccc1)c5C(=O)c6ccccc6(C(=O)c5(c4([nH]c23))))C(=O)c78)c9ccccc9,Training,0,1,242,0.17756139177658672,142.26999999999998,202.07109999999975,1.3463121358514456,3199.457301800504,665.6610000000002,6.7549000000000055
+1146,1148,13195-64-7,O=C(OC(C)C)CC(=O)OC(C)C,Training,0,0,76,0.4923034851821036,52.60000000000001,47.07300000000003,3.722863587825631,164.05372307956134,188.22299999999998,1.2796999999999998
+1147,1149,132059-51-9,O=C1OC(O)C(=C1Cl)C(Cl)Br,Training,1,1,62,0.5720884885099857,46.53,43.545800000000014,2.9670766230798877,225.7674198630255,261.88599999999997,1.3143
+1148,1150,132059-52-0,O=C1OC(O)C(=C1Cl)C(Br)Br,Training,1,1,62,0.5893652988132857,46.53,46.61980000000001,2.9670766230798877,225.7674198630255,306.337,1.4704000000000002
+1149,1151,132059-53-1,O=C1OC(O)C(=C1Br)C(Br)Br,Training,1,1,62,0.5773247918679754,46.53,49.69380000000001,2.9670766230798877,223.01253236086205,350.788,1.6265
+1150,1152,132172-56-6,O1C=CC=Cc3c1c2ccccc2c4cc5ccccc5(cc34),Training,1,1,108,0.28253143268652714,9.23,97.76200000000003,2.0756353164744192,1132.9104319629298,294.35300000000007,6.065500000000004
+1151,1153,132172-57-7,OC4C=Cc3c1ccccc1c2cc5ccccc5(cc2c3C4(O)),Training,1,1,116,0.3687876113423682,40.46,98.96060000000004,2.0693344172133066,1140.9076069909265,312.36800000000005,4.567300000000004
+1152,1154,132172-58-8,OC3C=Cc2c4cc5ccccc5(cc4(c1ccccc1c2C3(O))),Training,1,1,116,0.3687876113423682,40.46,98.96060000000003,2.0599679352304126,1140.9076069909265,312.36800000000005,4.567300000000004
+1153,1155,1321-74-0,C=Cc1ccccc1(C=C),Training,0,0,50,0.5769827958270134,0.0,46.624000000000024,3.1971603955332917,218.97015243201014,130.18999999999997,2.9726000000000017
+1154,1156,132297-89-3,n1c5ccc(OC)cc5(cc2c1c4cccc3cccc2c34),Training,1,0,104,0.42954155894978735,22.12,90.23100000000002,1.9212802930340376,1060.629303453225,283.33000000000004,5.044000000000003
+1155,1157,13256-06-9,O=NN(CCCCC)CCCCC,Training,1,1,78,0.31407943541709066,32.67,56.41800000000005,3.3370759509002665,107.49237320457347,186.29899999999995,3.350200000000002
+1156,1158,13256-32-1,O=NN(C(=O)NC)C,Training,1,1,46,0.3859698014087872,61.77,28.013699999999993,3.6226406823849624,102.70165766734146,117.10799999999999,-0.06099999999999994
+1157,1159,132-64-9,o2c1ccccc1c3ccccc23,Training,0,1,62,0.49963491535856996,13.14,53.72000000000003,2.642438259907001,512.8841359099093,168.195,3.586000000000002
+1158,1160,132663-51-5,O=C(OCc1ccccc1[N+](=O)[O-])CC,Training,0,0,80,0.43196932627680157,69.44,53.18340000000003,2.7581067853951575,375.4400671803062,209.20099999999994,2.048
+1159,1161,132742-01-9,O=[N+]([O-])c3ccc1ccc5c2c(ccc3(c12))cc4C=CCCc45,Training,1,1,110,0.266245608034635,43.14,94.15540000000006,2.0680931302234318,1141.0427767523363,299.32900000000006,5.4516000000000036
+1160,1162,132742-02-0,O=[N+]([O-])c5c1ccc2cccc3ccc(c1c23)c4c5(C=CCC4),Training,1,1,110,0.266245608034635,43.14,94.15540000000004,2.1560961583977614,1125.2927767523363,299.32900000000006,5.451600000000003
+1161,1163,132742-03-1,O=[N+]([O-])c5ccc2ccc3cc1c(C=CCC1)c4ccc5(c2c34),Training,1,1,110,0.266245608034635,43.14,94.15540000000003,2.073491771308577,1141.042776752336,299.329,5.451600000000003
+1162,1164,132742-04-2,O=[N+]([O-])c4ccc1ccc3c5C=CCCc5(cc2ccc4(c1c23)),Training,1,1,110,0.266245608034635,43.14,94.15540000000003,2.0723346158230593,1141.042776752336,299.329,5.4516000000000036
+1163,1165,132742-05-3,O=[N+]([O-])c2c3ccc5cccc4ccc(c1C=CCCc12)c3c45,Training,0,1,110,0.266245608034635,43.14,94.15540000000004,2.158070534991862,1125.2927767523363,299.32900000000006,5.451600000000003
+1164,1166,132769-75-6,OC5c3ccc2ccc1c6ccccc6(ccc1c2c3C4OC4C5(O)),Training,1,1,122,0.37892924066441147,52.989999999999995,97.54060000000003,1.7978110070360744,1180.1605517949208,328.3670000000001,3.9940000000000038
+1165,1167,132832-27-0,OC5c3ccc2c6ccccc6(c1ccccc1c2c3C4OC4C5(O)),Training,1,1,122,0.37892924066441147,52.989999999999995,97.54060000000003,1.884289800619276,1144.9105517949208,328.3670000000001,3.9940000000000038
+1166,1168,13284-42-9,N#CC=CCC,Training,0,0,32,0.43838040297289493,23.79,25.04399999999999,3.0160614900204057,76.42945954287094,81.11800000000001,1.47618
+1167,1169,132-86-5,Oc1cc(O)c2ccccc2(c1),Training,1,1,60,0.6201010705740534,40.46,47.27760000000003,2.8920650451735157,421.10813525322834,160.17199999999997,2.2509999999999994
+1168,1170,132898-07-8,n1c(N)n(c2c1c3nc(c(nc3(cc2C))C)C)C,Training,1,1,92,0.6534106863674991,69.62,72.43340000000002,2.600521763366164,785.2622239646096,241.29799999999997,2.0239599999999998
+1169,1171,132929-89-6,O=[N+]([O-])c5ccc2ccc3cc1C=CCCc1c4ccc5(c2c34),Training,1,1,110,0.266245608034635,43.14,94.15540000000003,2.0691132654307314,1141.042776752336,299.329,5.451600000000003
+1170,1172,132934-48-6,O=[N+]([O-])c4cccc3c4(ncc2cnc1ccccc1c23),Training,1,1,100,0.30042961083919734,68.92,81.20440000000004,2.302736260053639,1027.690371598062,275.26700000000005,3.844400000000001
+1171,1173,13301-61-6,N#CCCN(c2ccc(N=Nc1c(cc(cc1Cl)[N+](=O)[O-])Cl)cc2)CC,Training,1,1,134,0.3251872843151439,94.89,101.85140000000003,2.1875177919216213,839.4423356386459,392.24600000000004,6.056980000000003
+1172,1174,13306-69-9,O(c1ccc(N)c(c1)C)P(OC)(OC)=S,Training,1,1,84,0.6539729251912091,53.71000000000001,64.52240000000002,2.8976369597653293,388.94388858544266,247.256,2.47332
+1173,1175,133-07-3,O=C1c2ccccc2(C(=O)N1SC(Cl)(Cl)Cl),Training,1,1,84,0.4533663728200827,37.38,64.82300000000001,2.3567193008884684,437.06705661543685,296.562,3.2585000000000006
+1174,1176,133-18-6,O=C(OCCc1ccccc1)c2ccccc2(N),Training,0,0,92,0.6610301369810663,52.32,71.28290000000003,1.8788102729908105,523.0266276810372,241.29,2.6683000000000003
+1175,1177,133-32-4,O=C(O)CCCc2c[nH]c1ccccc12,Training,0,0,78,0.8019371220308088,53.089999999999996,58.872500000000024,2.1105774136828446,473.1817844230892,203.241,2.5752000000000006
+1176,1178,133331-34-7,O=S5(=O)(CCS(=O)(=O)C35(CC1C4CCC(C(C)CCCC(C)C)C4(C)(CCC1C2(C)(CCC(CC23)Br)))),Training,1,0,208,0.3160715925355111,68.28,151.47259999999974,1.521600539692977,1034.8323103366336,605.7450000000005,7.020600000000009
+1177,1179,133-37-9,O=C(O)C(O)C(O)C(=O)O,Training,0,0,58,0.3652291848585975,115.06000000000002,27.285199999999996,4.069511908932012,133.82680599646994,150.08599999999998,-2.1226
+1178,1180,13345-21-6,Oc1ccc2ccc4c5ccccc5(cc3ccc1c2c34),Training,1,1,98,0.29257925528338974,20.23,89.31680000000004,2.2144030670666157,1138.300167721219,268.31500000000005,5.442800000000003
+1179,1181,13345-23-8,Oc2ccc3ccc4cc1ccccc1c5ccc2c3c45,Training,1,1,98,0.29257925528338974,20.23,89.31680000000004,2.2149901622360453,1138.300167721219,268.31500000000005,5.442800000000003
+1180,1182,13345-62-5,c1ccc2c(c1)ccc4c2c(c3ccccc3c4CCl)C,Training,1,1,102,0.22254115734111454,0.0,93.25400000000005,2.365308952713891,982.9549960983214,290.79299999999995,6.193420000000004
+1181,1183,133-49-3,c1(c(c(c(c(c1Cl)Cl)S)Cl)Cl)Cl,Training,0,0,66,0.3752157921208605,0.0,58.744000000000014,3.6035674514745475,230.20322477240757,282.406,5.242299999999999
+1182,1184,133502-50-8,N=C1C=CC(C=C1)=C(c2ccc(cc2)N(C)C)c3ccc(cc3)N(C)C,Training,0,0,132,0.8668781101117763,30.330000000000005,113.56670000000003,2.1096580842736588,808.5551038113279,343.47400000000005,4.766270000000004
+1183,1185,133550-91-1,OCc2ccc3cccc4c1ccccc1c2c34,Training,0,0,86,0.5260129714795542,20.23,74.30080000000002,2.272656602428363,771.6621453127873,232.28199999999998,3.9795000000000025
+1184,1186,133561-39-4,O=[N+]([O-])c1ccc(c(N)c1)c2ccc(N)cc2[N+](=O)[O-],Training,1,1,102,0.4999059360603501,138.32,74.0116,2.626998576512936,714.5986647406517,274.23600000000005,2.3343999999999996
+1185,1187,133591-33-0,O=[N+]([O-])c3cc(c2[nH]c1ccccc1c2c3C)C,Training,1,1,90,0.5184882756136585,58.93,71.93310000000002,2.581477399408803,787.1843868704011,240.262,3.846140000000002
+1186,1188,133591-35-2,O=[N+]([O-])c1ccc2[nH]c3c(cc(c(c3(c2(c1)))C)[N+](=O)[O-])C,Training,1,1,106,0.571606667808607,102.07,78.58750000000002,2.5104917087496363,926.9999388588645,285.259,3.7543400000000027
+1187,1189,133591-38-5,O=[N+]([O-])c1ccc2[nH]c3c(ccc(c3(c2(c1)))C)C,Training,1,1,90,0.5184882756136585,58.93,71.93310000000002,2.506622704886332,787.184386870401,240.26199999999997,3.846140000000002
+1188,1190,13360-61-7,C=CCCCCCCCCCCCCC,Training,0,0,90,0.27884590120686276,0.0,71.27500000000006,2.8335663014530574,115.20671786825557,210.40499999999994,5.873500000000005
+1189,1191,13360-63-9,N(CC)CCCC,Training,0,0,44,0.5276462374247944,12.03,33.45169999999999,2.447472887876344,23.360990398949916,101.193,1.396
+1190,1192,13365-37-2,n2c1ccccc1c(NCCCN(C)C)c3ccccc23,Training,1,1,108,0.5692547491260448,28.160000000000004,90.90970000000006,1.9931147403242573,695.62759147375,279.387,3.7516000000000025
+1191,1193,133740-20-2,O=C1OC(=Cc2c(OC)c3cc(OC)cc(O)c3(c(O)c12))C,Training,1,1,114,0.7074436684115241,89.13000000000001,81.16060000000003,2.672122727127154,954.6408354050405,302.28200000000004,2.6830200000000017
+1192,1194,133762-78-4,[N-]=[N+]=NCC(O)Cn2ncc1c(ncnc12)N,Training,1,1,88,0.43772827433928296,138.61,59.75520000000001,2.245425062685412,571.9089083137105,234.22299999999998,0.0797
+1193,1195,133762-79-5,[N-]=[N+]=NCC(O)Cn2cnc1c(nc(nc12)N)N,Training,1,1,94,0.3805929192497559,164.63000000000002,64.16760000000001,2.312817782626547,614.3003153243111,249.23799999999997,-0.33810000000000023
+1194,1196,133762-80-8,[N-]=[N+]=NCC(O)CN1C=C(C(=O)NC1(=O))C,Training,1,1,86,0.40796465768548285,123.85,56.07950000000001,2.8917961182720573,525.2106994549121,225.20799999999997,-0.4837800000000001
+1195,1197,133762-81-9,[N-]=[N+]=NCC(O)Cn2cnc1c2(nc(nc1Cl)N),Training,1,1,94,0.3641224532803496,138.61,64.76520000000001,2.312817782626547,618.8296403372918,268.668,0.7330999999999999
+1196,1198,133762-82-0,[N-]=[N+]=NCC(O)CN1C=CC(=NC1(=O))OC,Training,1,1,86,0.42859736881431526,113.11000000000003,55.068800000000024,2.738005859431106,451.2321588913963,225.20799999999997,-0.07690000000000019
+1197,1199,133762-83-1,[N-]=[N+]=NCC(O)Cn2cnc1c2(ncnc1Cl),Training,1,1,88,0.38098277375366846,112.59000000000002,60.352800000000016,2.245425062685412,576.2574238593073,253.653,1.1508999999999998
+1198,1200,133762-84-2,[N-]=[N+]=NCC(O)CN1C=C(C(=NC1(=O))OC)C,Training,1,1,92,0.44973812198012736,113.11000000000003,59.805800000000026,2.882723353450062,491.8949598577534,239.23499999999996,0.23152000000000017
+1199,1201,133762-85-3,[N-]=[N+]=NCC(O)Cn2cnc1c2(ncnc1SC),Training,1,1,94,0.2869328181305251,112.59000000000002,67.12380000000002,2.2646783916758957,591.6137180680576,265.302,1.2193999999999998
+1200,1202,133762-86-4,[N-]=[N+]=NCC(O)CN1C=CC(=NC1(=O))N,Training,1,1,80,0.3935633252176279,129.90000000000003,52.92920000000001,2.7200226554542377,435.3517047422334,210.19699999999997,-0.5033000000000001
+1201,1203,13379-35-6,O=C1c3cc(OC)ccc3(Oc2cc(OC)cc(O)c12),Training,1,1,102,0.7262165151453279,68.9,74.75880000000002,2.4699748485532926,863.3818970935897,272.256,2.669000000000001
+1202,1204,133830-97-4,Oc1ccc(cc1)C3=C(c2cc(O)ccc2C3CC)C,Training,0,0,102,0.837643372989383,40.46,81.73360000000004,2.1713133801992046,681.0644522255075,266.34,4.535700000000003
+1203,1205,133831-60-4,O=[N+]([O-])c1ccccc1SSC(=C(Cl)Cl)Cl,Training,1,1,86,0.43599557455367516,43.14,71.12940000000002,2.8206061891499528,435.0465289172486,316.61799999999994,5.178100000000001
+1204,1206,133831-61-5,O=[N+]([O-])c1ccccc1SSC(F)=C(Cl)Cl,Training,1,1,86,0.4500045430945613,43.14,66.38440000000001,2.8206061891499528,437.8014164194121,300.1629999999999,4.9088
+1205,1207,133831-62-6,O=[N+]([O-])c1ccccc1SSC(=C(C(F)(F)F)Cl)Cl,Training,1,1,104,0.4059922116712243,43.14,71.3314,2.8658446026991586,522.4313390850302,350.16999999999996,5.5441
+1206,1208,133-90-4,O=C(O)c1cc(cc(N)c1Cl)Cl,Training,1,0,64,0.6923332593166821,63.31999999999999,47.8337,3.3738590108748685,338.423415200434,206.028,2.2738
+1207,1209,13394-86-0,Nc1ccc(cc1C)c2ccccc2C,Training,1,1,76,0.694974605878639,26.02,65.76440000000002,2.5510019801121246,486.44741565536316,197.281,3.552640000000002
+1208,1210,13395-02-3,O=C2Nc3cc1c(OC)cccc1c4c5OCOc5(cc2c34),Training,1,1,108,0.6994067870521689,56.790000000000006,82.08220000000003,2.0818322617347804,993.2678163618921,293.278,3.296000000000001
+1209,1211,133960-21-1,O=C(OC)c3oc(NOC(=O)C)c(c1ccccc1)c3(c2ccccc2),Training,0,0,132,0.5456639025129004,77.77000000000001,96.30820000000001,2.2700366715695406,916.1344164279675,351.35800000000006,4.290200000000003
+1210,1212,133960-22-2,O=C(OC)c3oc(c(c1ccccc1)c3(c2ccccc2))N(O)C(=O)C,Training,0,0,132,0.43397183918772303,79.97999999999999,95.86600000000004,2.3856263652552663,931.595211571006,351.3580000000001,4.142300000000003
+1211,1213,134-09-8,O=C(OC1CC(C)CCC1C(C)C)c2ccccc2(N),Training,0,0,110,0.6723443520304883,52.32,81.40090000000005,2.10059985690455,469.81273773139947,275.39200000000005,3.886400000000002
+1212,1214,134109-01-6,OC3c4ccccc4(c2cc1ccccc1c(c2C3(O))Cl),Training,0,0,104,0.6512111763820185,40.46,84.31360000000002,2.1503314105097457,856.9612954585153,296.75300000000004,4.240600000000002
+1213,1215,134109-02-7,OC3C=Cc2cc1c4ccccc4(ccc1c(c2C3(O))Cl),Training,0,1,104,0.6140361009796148,40.46,86.46460000000003,2.158140301545759,898.4934064082672,296.75300000000004,4.067500000000003
+1214,1216,134109-03-8,OC3C=Cc2c4cc1ccccc1c(c4(ccc2C3(O)))Cl,Training,1,0,104,0.6140361009796148,40.46,86.46460000000002,2.1485535643340357,898.4934064082672,296.75300000000004,4.067500000000003
+1215,1217,134170-56-2,O=C(OC)c2oc(c(c1ccccc1)c2c3ccccc3)N(OC(=O)C)C(=O)C,Training,0,0,148,0.48699476793266194,86.04999999999998,105.84550000000004,2.391234270208644,1039.9242664405567,393.3950000000002,4.231200000000004
+1216,1218,13417-43-1,C(=C(C)CCl)C,Training,1,1,36,0.35347387191916835,0.0,30.150999999999986,3.2188150560434132,54.95878455585175,104.57999999999998,2.1914
+1217,1219,134-20-3,O=C(OC)c1ccccc1(N),Training,0,0,58,0.4818862664217506,52.32,42.19390000000001,3.0326621558006566,270.54949758389114,151.16499999999996,1.0554
+1218,1220,134-29-2,O(c1ccccc1(N))C,Training,1,1,48,0.5706913849970715,35.25,37.4064,3.0065240073265844,197.86256853719752,123.155,1.2774
+1219,1221,134308-13-7,O=C(c1ccc(cc1)C)c2cc(O)c(O)c(c2)[N+](=O)[O-],Training,0,1,102,0.38710486030618185,100.67,71.0375,2.4986509580630023,691.4556053660622,273.244,2.545420000000002
+1220,1222,134-32-7,Nc1cccc2ccccc12,Training,1,1,54,0.5629544406745023,26.02,48.36040000000001,2.9131611636048604,374.03449039867843,143.189,2.4220000000000006
+1221,1223,13436-58-3,O=[N+]([O-])c2cccc1cn(nc12)C,Training,1,1,66,0.4892445861739232,60.96,47.368400000000015,2.8191970893131817,475.1939168291226,177.16299999999995,1.4814999999999998
+1222,1224,134514-27-5,O=[N+]([O-])c1cc(N)c(F)cc1(N),Training,1,1,64,0.372411956687844,95.17999999999999,41.8792,3.3258841466405995,339.81023714834686,171.131,0.8983000000000001
+1223,1225,134523-00-5,O=C(O)CC(O)CC(O)CCn4c(c1ccc(F)cc1)c(c2ccccc2)c(C(=O)Nc3ccccc3)c4C(C)C,Training,0,0,214,0.162760439349283,111.78999999999999,157.2465999999997,1.891136858699184,1467.261472278087,558.6500000000001,6.3136000000000045
+1224,1226,134-62-3,O=C(c1cccc(c1)C)N(CC)CC,Training,0,0,76,0.7184022097170996,20.310000000000002,58.43050000000004,2.8805938648817375,315.8526973504348,191.27399999999994,2.4770200000000004
+1225,1227,134-72-5,OC(c1ccccc1)C(NC)C,Training,0,0,66,0.7078187228911748,32.26,49.92350000000003,2.711040723233061,222.5400055614587,165.23599999999996,1.3279
+1226,1228,134-81-6,O=C(c1ccccc1)C(=O)c2ccccc2,Training,0,0,78,0.5762605941819152,34.14,61.54500000000003,2.278573274768037,451.2732551825604,210.232,2.752200000000001
+1227,1229,134874-62-7,O=[N+]([O-])c4cc(c3c5ccccc5(c2cccc1ccc4(c3(c12))))[N+](=O)[O-],Training,1,1,124,0.18196342363134224,86.28,100.96080000000005,2.2655492178352965,1391.290208613586,342.3100000000001,5.553600000000002
+1228,1230,134959-55-0,O=C(OCc1ccccc1)c3cccc2cccnc23,Training,0,0,98,0.6777541709505978,39.19,77.30450000000003,1.8248139591204064,732.8258856494507,263.296,3.5918000000000028
+1229,1231,134959-56-1,O=C(OCc1ccc(cc1)Cl)c3cccc2cccnc23,Training,0,0,104,0.6786124876958833,39.19,82.31450000000005,1.7938940593546924,778.9069169304881,297.74100000000004,4.245200000000003
+1230,1232,134959-57-2,O=C(OCc1ccc(cc1Cl)Cl)c3cccc2cccnc23,Training,0,0,110,0.6406038434987933,39.19,87.32450000000003,1.8175261578799857,843.6865913161552,332.18600000000004,4.898600000000004
+1231,1233,134959-60-7,O=C(O)c3cc(ccc3(N=Cc1cccc2cccnc12))C,Training,0,0,108,0.7416986120637038,62.55,87.13530000000006,2.055421700432287,879.8944809749554,290.32200000000006,3.992020000000003
+1232,1234,134998-71-3,O=C(O)CCCCC(=O)OCC(CC)CCC(O)C,Training,0,0,112,0.44613489740729934,83.83,71.75860000000004,3.6531065108045273,262.56193848901216,274.35699999999997,2.3618000000000006
+1233,1235,134998-72-4,O=C(O)CCCCC(=O)OCC(CC)CCC(=O)C,Training,0,0,110,0.46158018772565745,80.66999999999999,70.75880000000005,3.6802669241796053,298.211449108696,272.341,2.5700000000000003
+1234,1236,134998-76-8,O=Nc1ccc2ccc4c3c(ccc1c23)cc5c4CCCC5,Training,1,1,106,0.31789928725307787,29.43,92.24300000000004,2.0698398513782443,1048.0661780455932,285.34600000000006,5.860700000000005
+1235,1237,134998-77-9,O=[N+]([O-])c5cc3cccc4c1ccccc1c2cccc5(c2c34),Training,1,1,108,0.17366715134946126,43.14,94.30640000000005,2.255782841637275,1240.4324987418463,297.31300000000005,5.645400000000003
+1236,1238,134998-78-0,O=C(Oc2c(OC(=O)C)c5c(ccc4c1ccccc1c3cccc2c3c45)[N+](=O)[O-])C,Training,1,1,152,0.09682087045234276,95.74000000000001,116.92440000000006,2.1810099376875827,1569.7045881378415,413.3850000000002,5.496000000000003
+1237,1239,134998-79-1,O=[N+]([O-])c5cc1cccc3c1c2c5(cccc2c4c3CCCC4),Training,1,1,112,0.2692893128834907,43.14,93.44240000000005,2.1425220213957905,1097.3759786701924,301.34500000000014,5.371000000000004
+1238,1240,135086-99-6,O=C(NN=Cc1ccccc1)c2[nH]c3ccccc3(c2(N)),Training,0,0,104,0.5078478805742385,83.27,84.21330000000003,1.782591602062152,805.5148575560493,278.31500000000005,2.514
+1239,1241,135105-89-4,O1C=CC2c3c(OC)cc(OC)cc3(OC12),Training,1,1,84,0.7639571621185459,36.92,56.92800000000003,2.129306082986538,452.57713685934266,220.224,2.0498
+1240,1242,135105-90-7,O(c4cc(OC)c2c(OC3OC1OC1C23)c4)C,Training,1,1,90,0.7234111129347341,49.45,56.449000000000034,1.84384093293523,486.0294867285685,236.223,1.261
+1241,1243,13523-86-9,OC(COc1cccc2[nH]ccc12)CNC(C)C,Training,0,0,98,0.7315916457547718,57.28,72.93920000000004,1.9143095421480512,493.254577902345,248.326,1.9055999999999997
+1242,1244,135294-98-3,c1ccc4c(c1)c2cccc3c2c4(ccc3CBr),Training,1,1,86,0.41338630040837765,0.0,81.00900000000003,2.2345018001350607,742.4121453127873,295.179,5.382100000000002
+1243,1245,135294-99-4,OCc4cccc3c2cccc1cccc(c12)c34,Training,0,0,86,0.5260129714795542,20.23,74.30080000000002,2.2420196325358948,766.4121453127873,232.28199999999998,3.9795000000000025
+1244,1246,135295-00-0,OCc1ccc2c4cccc3cccc(c2(c1))c34,Training,1,0,86,0.5260129714795542,20.23,74.30080000000002,2.1687428088046565,766.4121453127873,232.28199999999998,3.9795000000000016
+1245,1247,135325-62-1,c1ccc2c(c1)c4cccc3ccc(c2c34)CBr,Training,1,1,86,0.41338630040837765,0.0,81.00900000000003,2.2726566024283628,771.6621453127873,295.179,5.382100000000002
+1246,1248,135-49-9,n1c3cc(N)c(cc3(cc2cc(c(N)cc12)C))C,Training,1,1,90,0.4659624892789388,64.92999999999999,77.54780000000002,2.4309822627872317,646.6298966071573,237.30599999999998,3.169240000000001
+1247,1249,135-51-3,O=S(=O)(O)c1ccc2cc(O)c(cc2(c1))S(=O)(=O)O,Training,0,0,102,0.7066598306440867,128.97,65.24200000000002,2.832990251928953,866.1314648335255,304.30100000000004,1.0388000000000002
+1248,1250,13551-87-6,O=[N+]([O-])c1nccn1CC(O)COC,Training,1,1,78,0.5258044389151287,90.42,46.76420000000003,2.6606864596644657,311.63848126407265,201.182,-0.20140000000000025
+1249,1251,135577-57-0,[N-]=[N+]=Nc2nc1ncc(cc1n2C)c3ccccc3,Training,1,1,92,0.39552103406589384,79.47,72.75100000000002,2.2074514996043724,783.5035862472806,250.26500000000001,3.5771000000000015
+1250,1252,135626-95-8,O=C1OC34(CCCC1(C)C4(CCC2CC(C=C)(C)CC(O)C23(C))),Training,0,0,128,0.5898491975573227,46.53,88.64680000000006,1.817761859537977,571.234094566873,318.45700000000005,3.851700000000003
+1251,1253,135673-14-2,O=Nc2ccc(Oc1ccc(cc1)NC(=O)C)cc2,Training,1,1,96,0.8449216824488154,67.75999999999999,72.71670000000003,2.054348077652563,576.6450014443017,256.26099999999997,3.835200000000002
+1252,1254,135-68-2,Nc1ccc(cc1)c2ccc(cc2)Cl,Training,1,1,70,0.7047337891406046,26.02,61.30040000000002,2.396509039726096,373.5796467381504,203.672,3.5892000000000017
+1253,1255,135-73-9,O=C(c1ccc(cc1)c2ccccc2)CBr,Training,1,0,80,0.6123591372461117,17.07,70.00250000000003,2.298282787786087,473.84834508395556,275.145,3.9312000000000014
+1254,1256,135-88-6,c1ccc(cc1)Nc2ccc3ccccc3(c2),Training,0,0,82,0.6646509169781277,12.03,73.67270000000003,1.961246717577175,629.1061251510306,219.287,4.583400000000002
+1255,1257,13593-03-8,n1cc(nc2ccccc12)OP(OCC)(OCC)=S,Training,0,0,102,0.7626518845640481,53.47000000000001,77.70300000000005,2.258211706768993,598.2991189533659,298.3039999999999,3.3061000000000016
+1256,1258,13603-07-1,O=NN1CCCC(C)C1,Training,1,1,52,0.4998709700388202,32.67,35.766,2.310570132500946,105.2309826803223,128.17499999999998,1.3997
+1257,1259,13608-87-2,O=C(c1ccc(c(c1Cl)Cl)Cl)C,Training,1,0,64,0.5219835155704365,17.07,51.476500000000016,3.3612251104663047,333.3200121526738,223.486,3.849400000000001
+1258,1260,136112-70-4,O=[N+]([O-])c1ccc(cc1)c2nc(N)c3ncn(c3(n2))c4ccc(cc4)[N+](=O)[O-],Training,1,1,138,0.42002968895321363,155.9,99.8172,1.81811963623016,1216.978561765904,377.3200000000001,2.881100000000001
+1259,1261,136112-71-5,O=[N+]([O-])c1ccc(cc1)c3nc2c(ncnc2n3c4ccc(cc4)[N+](=O)[O-])N,Training,1,1,138,0.42002968895321363,155.90000000000003,99.8172,1.9520140562379265,1216.978561765904,377.3200000000001,2.881100000000001
+1260,1262,136112-72-6,O=[N+]([O-])c1ccc(cc1)Nc4ncnc3c4(ncn3(c2ccc(cc2)[N+](=O)[O-])),Training,1,1,138,0.41184579577579894,141.91000000000003,99.69350000000001,1.6801741101545908,1186.5929442417214,377.3200000000001,3.3755000000000015
+1261,1263,136112-73-7,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])n3cnc2c(ncnc23)N,Training,1,1,110,0.5583120389103328,155.9,74.3812,2.2833877137762904,919.9446155199563,301.22200000000004,1.2140999999999997
+1262,1264,13615-38-8,O=[N+]([O-])c2cc(cc1ccccc12)C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.8657325704443615,505.61373284730047,187.19799999999998,3.056420000000001
+1263,1265,136196-46-8,O=[N+]([O-])c1ccc(cc1)NN=C(N=Nc2ccc(cc2)I)c3ccccc3,Training,0,1,134,0.1281721078038187,92.25,113.3731,1.838501910985735,971.2465531588973,471.25800000000004,5.757000000000003
+1264,1266,136-35-6,N(=Nc1ccccc1)Nc2ccccc2,Training,1,1,74,0.5893339610285244,36.75,61.02270000000003,1.968643821266043,423.13492426563516,197.241,3.7974000000000014
+1265,1267,136379-59-4,O=C(O)CC(C(=O)O)CC(=O)OC(CC(C)CC(O)CCCCCCC(O)C(N)C)C(OC(=O)CC(C(=O)O)CC(=O)O)C(C)CCCC,Training,0,0,284,0.043274922740881634,268.28,176.20319999999967,5.938604655984825,1034.3525720323046,705.8390000000002,3.5934000000000026
+1266,1268,136587-13-8,O=NN(O)N(CCCN)CCCCNCCCN,Training,1,1,108,0.20316151127196796,120.21000000000001,70.44000000000003,3.5888891179031246,195.2067178682556,262.35799999999995,-0.35659999999999775
+1267,1269,13674-87-8,O=P(OC(CCl)CCl)(OC(CCl)CCl)OC(CCl)CCl,Training,1,0,122,0.3328217157050315,44.760000000000005,86.54550000000003,4.947205147936471,242.81734999619414,430.90700000000004,4.682900000000004
+1268,1270,13675-34-8,O=C(OCCCCCOC(=O)C(=C)C)C(=C)C,Training,0,0,96,0.37117860680365533,52.6,65.39700000000003,3.359569854387089,274.54132320940784,240.29899999999995,2.3953000000000007
+1269,1271,13676-54-5,O=C1C=CC(=O)N1c2ccc(cc2)Cc3ccc(cc3)N4C(=O)C=CC4(=O),Training,0,1,132,0.7850414572288755,74.76,98.95600000000006,1.4653979067261391,897.6520651109073,358.3530000000001,2.1361999999999997
+1270,1272,136-77-6,Oc1ccc(c(O)c1)CCCCCC,Training,0,0,78,0.7064082483225955,40.46,57.61760000000004,2.424494224033286,281.65026016439094,194.27399999999994,3.220600000000001
+1271,1273,13684-63-4,O=C(Oc1cccc(c1)NC(=O)OC)Nc2cccc(c2)C,Training,1,1,114,0.9039154808102652,76.66,83.29540000000003,1.9910569204245536,685.3509531428246,300.314,3.7842200000000012
+1272,1274,136861-00-2,O=[N+]([O-])c2cc(N)cc(c2(c1ccccc1))[N+](=O)[O-],Training,1,1,96,0.5169085847143471,112.30000000000001,69.59920000000001,2.8247111306532613,620.2741136328642,259.221,2.752200000000001
+1273,1275,136861-01-3,O=[N+]([O-])c2cc(N)cc(N)c2(c1ccccc1),Training,1,1,86,0.4692910837938651,95.17999999999999,67.3572,2.722812105276341,567.4634663423765,229.239,2.4262000000000006
+1274,1276,13687-09-7,N(C)P(N1CC1)(N2CC2)=S,Training,1,1,58,0.48483086369833817,18.049999999999997,46.490700000000025,2.107627462828576,171.33208472898127,177.213,0.06149999999999989
+1275,1277,136911-37-0,N1=NCCN1C,Training,1,1,34,0.41543791565569727,27.96,22.35299999999999,2.3774886045778656,68.43856189774725,85.10999999999999,0.29900000000000004
+1276,1278,136950-74-8,O=C(c1ccc2[nH]c3c(cc(c(c3(c2(c1)))C)[N+](=O)[O-])C)C,Training,1,1,106,0.43739237702123096,76.0,81.93760000000002,2.5104917087496363,922.302907767671,282.29900000000004,4.048740000000003
+1277,1279,137-05-3,N#CC(=C)C(=O)OC,Training,1,0,42,0.27643348091516096,50.09,26.768999999999995,3.888030356583285,154.30183003209248,111.09999999999998,0.23917999999999995
+1278,1280,13707-88-5,OC(COc1ccccc1CC=C)CNC(C)C,Training,0,0,100,0.6936807740895572,41.49,74.98350000000005,2.4441362532698547,363.26616352106794,249.35399999999996,2.1528
+1279,1281,137-08-6,O=C(O)CCNC(=O)C(O)C(C)(C)CO,Training,0,0,88,0.4560957521485702,106.86000000000001,52.13610000000003,4.050539880408987,238.6572029354464,219.237,-1.0433000000000001
+1280,1282,137-09-7,Oc1ccc(N)cc1(N),Training,1,1,48,0.26855419530554153,72.27,36.931599999999996,3.171678030440915,222.29788705001033,124.14300000000001,0.5566000000000002
+1281,1283,137-17-7,Nc1cc(c(cc1C)C)C,Training,1,1,54,0.5420721160262785,26.02,45.06540000000002,3.2824629074535223,200.900333363576,135.20999999999998,2.1940600000000003
+1282,1284,137-18-8,O=C1C=C(C(=O)C=C1C)C,Training,0,0,52,0.4659417707377386,34.14,37.528000000000006,3.0346436965730383,228.43115658409943,136.14999999999998,1.0308
+1283,1285,137-26-8,C(N(C)C)(=S)SSC(N(C)C)=S,Training,1,0,70,0.46886077125428943,6.48,67.75200000000002,3.6934830872422997,158.38689879982147,240.44400000000002,2.0608
+1284,1286,13743-07-2,O=NN(C(=O)N)CCO,Training,1,1,52,0.38301386813563276,95.99000000000001,29.170199999999998,3.67532946882013,114.87060032410331,133.10700000000003,-0.9592
+1285,1287,137-89-3,O=C(OCC(CC)CCCC)c1cccc(c1)C(=O)OCC(CC)CCCC,Training,0,0,158,0.3433083562994692,52.60000000000001,113.61900000000009,2.5908220563354685,534.4728097510646,390.5640000000003,6.433000000000007
+1286,1288,13810-83-8,O=C(O)c1c(C(=O)O)c(c(c(c1Br)Br)Br)Br,Training,0,0,86,0.4919577248120488,74.6,71.16060000000002,3.831879914593588,452.54705704391523,481.71599999999995,4.133
+1287,1289,138154-39-9,O=C2c1cc(O)ccc1n4cnc3ccc(NCCN(CC)CC)c2c34,Training,1,1,134,0.5234011058259932,69.86999999999999,105.60250000000003,1.8705415744570377,1131.5366823953473,350.42200000000014,2.8980000000000015
+1288,1290,138154-40-2,O=C2c1cc(O)ccc1n4c(nc3ccc(NCCN(CC)CC)c2c34)C,Training,1,1,140,0.5142906658797711,69.86999999999999,110.33950000000006,1.9176231627603166,1178.0079910527286,364.4490000000002,3.2064200000000014
+1289,1291,138245-73-5,[N-]=[N+]=NCC(O)C(O)C(O)C(O)C(=O)O,Training,1,1,86,0.19401506724069253,166.98,45.67600000000002,4.348155886274944,265.59284654013777,221.16899999999998,-2.175100000000001
+1290,1292,138245-74-6,[N-]=[N+]=NCC(O)C(O)C(O)C(O)CO,Training,1,1,82,0.18893070539545856,149.91,45.126000000000026,4.145140583960836,207.6436571479203,207.18599999999998,-2.2674
+1291,1293,138331-98-3,[N-]=[N+]=NCC1OC(O)C(O)C(O)C1(O),Training,1,1,80,0.23659408394586956,138.91000000000003,42.91320000000002,2.644451756639141,243.6214754166154,205.17,-1.9034000000000006
+1292,1294,13838-16-9,FC(F)OC(F)(F)C(F)Cl,Training,0,0,62,0.48329409286155045,9.23,22.784999999999997,3.8655589302387363,105.06618564394175,184.491,2.3528000000000002
+1293,1295,138-42-1,O=[N+]([O-])c1ccc(cc1)S(=O)(=O)O,Training,0,0,70,0.4359959731213461,97.51,42.911000000000016,3.15526874357476,420.84276272939394,203.17499999999995,0.8414999999999999
+1294,1296,13849-08-6,O=C1Oc2cc3OC(Cc3(cc2(C=C1)))C(O)(C)C,Training,1,1,94,0.7802173990933166,59.67,66.90180000000002,2.090732718388322,663.5288188719239,246.26199999999997,1.8673999999999997
+1295,1297,138542-40-2,O=[N+]([O-])c2cc3ccc4cc1ccccc1c5ccc(c2)c3c45,Training,1,1,108,0.17366715134946126,43.14,94.30640000000005,2.0885235899854986,1221.682498741846,297.31300000000005,5.645400000000003
+1296,1298,13855-74-8,O=C(NCO)c1ccc(cc1)Cl,Training,0,0,64,0.6763363921302618,49.33,46.00400000000002,2.753742758109602,270.89127877505575,185.60999999999999,1.0196
+1297,1299,138580-44-6,O=C4C=CC(=O)c1c4(nc(c2c3ccccc3([nH]c12))C),Training,1,1,96,0.6770938943106324,62.82,76.13770000000002,2.2787701255757047,947.9155537650477,262.26800000000003,2.959720000000001
+1298,1300,138-59-0,O=C(O)C1=CC(O)C(O)C(O)C1,Training,0,0,68,0.3869234584394271,97.99000000000001,38.35620000000001,2.809449955869897,221.83662511442938,174.152,-1.5162000000000004
+1299,1301,138805-29-5,N(=Nc1cc(N)ccc1C)c2cc(N)ccc2C,Training,1,1,92,0.6168352408731984,76.75999999999999,75.35880000000002,2.3520351227332705,549.2381412126717,240.31,3.8832400000000025
+1300,1302,138805-30-8,[O-][N+](=Nc1cc(N)ccc1C)c2cc(N)ccc2C,Training,1,1,98,0.3731835117104867,90.47,76.55820000000001,2.4788232323251727,649.8893784000562,256.30899999999997,3.3935400000000016
+1301,1303,138805-31-9,O=C(Nc2cc(N=Nc1ccc(c(c1)NC(=O)C)C)ccc2C)C,Training,0,0,124,0.8033149492938425,82.91999999999999,95.14140000000003,2.243550045877072,745.1612140517699,324.38400000000007,4.635640000000003
+1302,1304,138805-32-0,O=C(Nc2ccc(c(N=[N+]([O-])c1cc(ccc1C)NC(=O)C)c2)C)C,Training,0,0,130,0.49695883355826465,96.63,96.34080000000003,2.4097077326133833,859.394837070384,340.3830000000001,4.145940000000003
+1303,1305,138805-33-1,O=C(Nc2ccc(c(N=Nc1cc(ccc1C)NC(=O)C)c2)C)C,Training,0,0,124,0.8033149492938425,82.91999999999999,95.14140000000003,2.2982315179658594,745.1612140517698,324.38400000000007,4.635640000000003
+1304,1306,138835-33-3,O=[N+]([O-])c3ccc1ccc5c2c(ccc3(c12))c4ccccc4[n+]5([O-]),Training,1,1,114,0.11574238156822503,70.08,93.26640000000003,2.1751125897280947,1294.2099968942562,314.3,4.278800000000004
+1305,1307,138835-34-4,O=[N+]([O-])c5ccc2ccc3c1ccccc1[n+]([O-])c4ccc5(c2c34),Training,1,1,114,0.11574238156822503,70.08,93.26640000000003,2.1746010068766304,1294.2099968942562,314.30000000000007,4.278800000000003
+1306,1308,138835-35-5,O=[N+]([O-])c2ccc3ccc4nc1ccccc1c5ccc2c3c45,Training,1,1,108,0.18841558621541948,56.03,92.10140000000004,2.144352010669374,1244.1604378841655,298.30100000000004,5.040400000000003
+1307,1309,138835-36-6,O=[N+]([O-])c1ccc2ccc4c5ccccc5(nc3ccc1c2c34),Training,1,1,108,0.18841558621541948,56.03,92.10140000000004,2.143176327147487,1244.1604378841655,298.30100000000004,5.040400000000003
+1308,1310,138-89-6,O=Nc1ccc(cc1)N(C)C,Training,1,1,58,0.6049107079638116,32.67,46.224000000000025,2.9098227999015407,240.77390023702037,150.18099999999998,2.1505
+1309,1311,13889-92-4,O=C(Cl)SCCC,Training,1,0,42,0.5457516889856048,17.07,33.998,2.8219389370591843,64.71013448036486,138.619,2.4884000000000004
+1310,1312,138914-14-4,O=[N+]([O-])C(C)CO,Training,0,1,42,0.3851114474274968,63.370000000000005,23.542199999999994,3.3434170589539596,72.58027134782354,105.093,-0.3561
+1311,1313,13909-09-6,O=NN(C(=O)NC1CCC(C)CC1)CCCl,Training,1,1,92,0.4713603546084927,61.77,63.172700000000034,2.347711067064734,242.21864103769911,247.72599999999994,2.496900000000001
+1312,1314,13911-90-5,n2c4cccc(c4(cc3ccc1ccccc1c23))C,Training,1,1,90,0.31760721028739625,12.89,81.49200000000005,2.2590525379083615,922.3919838784873,243.309,4.849620000000003
+1313,1315,139-13-9,O=C(O)CN(CC(=O)O)CC(=O)O,Training,0,1,74,0.46957914776014226,115.14,39.3474,4.095996370610992,187.12526634448807,191.13899999999998,-1.4577999999999993
+1314,1316,13925-00-3,n1ccnc(c1)CC,Training,0,0,42,0.5367952647550015,25.78,31.40999999999999,2.8320858350070903,147.87452390041133,108.14399999999999,1.039
+1315,1317,139259-64-6,O=C(ON(OC(C)C)C(=O)c1ccccc1)C,Training,1,1,92,0.7537971666110419,55.839999999999996,60.59850000000004,2.823932554655154,388.751919053098,237.255,1.9468999999999999
+1316,1318,139259-91-9,O=C(ON(OCc1ccc(OC)cc1)C(=O)c2ccccc2)C,Training,1,1,120,0.793836320407029,65.07,82.16050000000004,2.055969200099808,654.443761248586,315.325,2.747300000000001
+1317,1319,139259-92-0,O=C(ON(OCc2ccc(Oc1ccccc1)cc2)C(=O)c3ccccc3)C,Training,1,1,142,0.5906316391203469,65.07,102.12450000000003,1.623596630952008,910.6767418311751,377.39600000000013,4.531000000000003
+1318,1320,139259-93-1,O=C(ON(OCc1ccc(cc1)C(C)(C)C)C(=O)c2ccccc2)C,Training,1,1,132,0.7878064742665738,55.839999999999996,94.30850000000005,2.072755197880326,717.6114149932156,341.40700000000004,4.036200000000004
+1319,1321,139259-94-2,O=C(ON(OCc1ccc(cc1)C)C(=O)c2ccccc2)C,Training,1,1,114,0.8142376294124882,55.839999999999996,80.34550000000004,2.071636668424096,637.4683307013453,299.326,3.0471200000000014
+1320,1322,139259-95-3,O=C(ON(OCc1ccc(cc1)c2ccccc2)C(=O)c3ccccc3)C,Training,1,1,136,0.631982347784682,55.839999999999996,101.04450000000003,1.679040085232145,892.6154953126836,361.3970000000001,4.405700000000003
+1321,1323,139259-96-4,O=C(ON(OCc1ccc(cc1)Cl)C(=O)c2ccccc2)C,Training,1,1,114,0.8105289254161446,55.839999999999996,80.61850000000004,2.071636668424096,642.955199002601,319.744,3.392100000000002
+1322,1324,139259-97-5,O=C(ON(OCc1ccc(cc1)Br)C(=O)c2ccccc2)C,Training,1,1,114,0.779643526782638,55.839999999999996,83.30850000000004,2.071636668424096,642.955199002601,364.1950000000001,3.5012000000000016
+1323,1325,139259-98-6,O=C(ON(OCc1ccc(cc1)[N+](=O)[O-])C(=O)c2ccccc2)C,Training,1,1,124,0.6170919850851969,98.97999999999999,82.26290000000003,2.0703007653575236,729.9926721639025,330.296,2.6469000000000005
+1324,1326,139347-89-0,OC5c3ccc2c1ccccc1c(c(c2c3C4OC4C5(O))C)C,Training,1,1,116,0.49385739960149244,52.989999999999995,89.50860000000004,1.9736612768690833,975.6854803814787,306.36100000000005,3.4576400000000023
+1325,1327,139-40-2,n1c(nc(nc1NC(C)C)Cl)NC(C)C,Training,0,0,84,0.8286985185089378,62.730000000000004,62.354400000000034,2.8436364364825457,298.02878439482896,229.715,2.1655999999999995
+1326,1328,139493-54-2,OC4c2ccc1c5cc(ccc5(cc(c1c2C3OC3C4(O))C))C,Training,1,1,116,0.49385739960149244,52.989999999999995,89.50860000000003,1.9315774625769044,975.6854803814787,306.36100000000005,3.4576400000000023
+1327,1329,139495-76-4,O=C1C=C3N(C(=O)N1)c2cc(F)c(cc2N3C4CC4)N5CCN(C)CC5,Training,1,1,136,0.7477540165695241,65.75,97.72270000000002,1.7878203460468125,1132.370809196306,357.38900000000024,1.1682999999999997
+1328,1330,139495-80-0,O=C1C=C3N(C(=O)N1(O))c2cc(F)c(cc2N3C4CC4)N5CCN(C)CC5,Training,1,1,142,0.6752717709404118,75.11999999999998,98.54650000000004,1.8082213315195705,1181.8639372121427,373.38800000000026,0.8789999999999998
+1329,1331,139-59-3,O(c1ccccc1)c2ccc(N)cc2,Training,1,1,70,0.7295816801359168,35.25,57.37040000000002,2.155110851234288,394.42672290326936,185.226,3.0611000000000006
+1330,1332,139627-44-4,OC4c2ccc1c5cccc(c5(cc(c1c2C3OC3C4(O))C))C,Training,1,1,116,0.49385739960149244,52.989999999999995,89.50860000000003,1.9406557639417856,975.6854803814787,306.36100000000005,3.4576400000000023
+1331,1333,139-65-1,Nc1ccc(cc1)Sc2ccc(N)cc2,Training,1,1,76,0.7586424920230067,52.04,65.83180000000002,2.1467113756182017,390.6842279806418,216.309,3.0022
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+1414,1416,142-84-7,N(CCC)CCC,Training,0,0,44,0.5276462374247944,12.03,33.45169999999999,2.447472887876344,23.360990398949916,101.193,1.396
+1415,1417,142-96-1,O(CCCC)CCCC,Training,0,0,56,0.5020748997224442,9.23,40.635000000000005,2.595082706793886,37.832293921787276,130.231,2.603200000000001
+1416,1418,143-07-7,O=C(O)CCCCCCCCCCC,Training,0,0,84,0.5412525786782161,37.3,59.47980000000005,2.884064614706359,132.28341890015258,200.32199999999995,3.991900000000004
+1417,1419,14308-65-7,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NC,Training,1,1,74,0.4426272918784832,85.38,48.46310000000002,2.73189815151121,380.44792766885814,196.16199999999998,0.9469999999999998
+1418,1420,143-16-8,N(CCCCCC)CCCCCC,Training,0,0,80,0.5112689857081927,12.03,61.15370000000006,2.7581498184332935,71.19366193720087,185.35499999999996,3.736600000000003
+1419,1421,143-27-1,NCCCCCCCCCCCCCCCC,Training,0,0,104,0.4033492716888433,26.02,79.36640000000007,2.846262262649495,108.69358616951132,241.4629999999999,5.426400000000006
+1420,1422,143347-57-3,O=CC1=CCCC2(C)(CC12(C=O)),Training,1,0,64,0.57945067941945,34.14,44.602000000000025,2.424495546063508,279.56316677717933,164.204,1.5008
+1421,1423,14346-19-1,O=[N+]([O-])c1ccc2nsc(N)c2(c1),Training,1,1,66,0.5550570073696386,82.05,50.68680000000001,2.724812383846014,479.5424323747194,195.20299999999997,1.7867
+1422,1424,143-50-0,O=C1C2(C3(C4(C1(C5(C2(C3(C(C45Cl)(Cl)Cl)Cl)Cl)Cl)Cl)Cl)Cl)Cl,Training,0,0,116,0.45322305695005977,17.07,88.11599999999999,2.0846484126260205,630.626975453629,490.6389999999999,4.618199999999999
+1423,1425,143603-72-9,O=C(OCC)c2[nH]c3ccccc3(c2(N=Cc1ccc(cc1)[N+](=O)[O-])),Training,1,1,126,0.3291071561384978,97.59,94.60560000000002,1.9988425480738006,958.1165602871001,337.3350000000001,4.003400000000003
+1424,1426,143603-75-2,O=C(OCC)c2[nH]c3ccccc3(c2(N=Cc1cc(OC)c(OC)c(OC)c1)),Training,1,1,146,0.49092323717074676,82.14000000000001,107.60720000000003,2.0816581191254704,997.80300346245,382.41600000000017,4.121000000000003
+1425,1427,143603-79-6,O=C(OCC)c2[nH]c3ccccc3(c2(N=Cc1ccc(cc1)NC(=O)C)),Training,1,1,132,0.5381912771410364,83.55000000000001,102.25490000000002,1.9373887216276275,971.6350192280235,349.3900000000001,4.053600000000002
+1426,1428,143603-80-9,O=C(OCC)c2[nH]c3ccccc3(c2(N=Cc1ccc(O)cc1)),Training,1,1,116,0.5683930606834465,74.68,89.61600000000001,2.04893419842896,863.6090124133043,308.33700000000005,3.8008000000000015
+1427,1429,143603-81-0,O=C(OCC)c2[nH]c3ccccc3(c2(N=Cc1ccc(cc1)C)),Training,0,1,116,0.5733651292406189,54.45,92.68820000000002,2.04893419842896,860.7119271860013,306.36500000000007,4.403620000000003
+1428,1430,1436-34-6,O1CC1CCCC,Training,0,0,42,0.49034763229426653,12.53,29.264999999999983,1.7961504729772093,48.14170945007629,100.161,1.5754000000000001
+1429,1431,143-67-9,O=C(OC2C(O)(C(=O)OC)C5N(c1cc(OC)c(cc1C45(CCN3CC=CC2(CC)C34))C9(C(=O)OC)(c7[nH]c6ccccc6c7CCN8CC(CC(O)(C8)CC)C9))C)C,Training,0,0,316,0.179801053533736,154.1,220.42829999999924,1.3637618830141265,2257.0913930587544,810.9889999999997,3.9909000000000043
+1430,1432,14385-22-9,O=C(N(O)c1ccc(cc1)Cl)C(C)C,Training,1,0,76,0.6063146154512841,40.540000000000006,55.56250000000003,2.840685065791601,321.3988126104432,213.664,2.7182000000000004
+1431,1433,143922-95-6,O=Nc1cccc(c1C)[N+](=O)[O-],Training,0,1,62,0.3840324131563308,72.57,43.28840000000001,3.3188809690716052,335.42341520043396,166.13599999999997,2.30112
+1432,1434,143922-96-7,[O-][N+](=Nc1cccc(N)c1C)c2cccc(N)c2C,Training,1,1,98,0.37318351171048675,90.47,76.55820000000003,2.488450378526431,649.8893784000562,256.30899999999997,3.3935400000000007
+1433,1435,143922-97-8,N(=Nc1cccc(N)c1C)c2cccc(N)c2C,Training,1,1,92,0.6168352408731984,76.75999999999999,75.35880000000002,2.362386828007207,549.2381412126717,240.31,3.8832400000000016
+1434,1436,143922-98-9,O=C(Nc2cccc(N=[N+]([O-])c1cccc(NC(=O)C)c1C)c2C)C,Training,0,0,130,0.49695883355826465,96.63,96.34080000000003,2.4275217812526093,859.3948370703841,340.38300000000015,4.145940000000002
+1435,1437,143922-99-0,O=C(Nc2cccc(N=Nc1cccc(NC(=O)C)c1C)c2C)C,Training,0,0,124,0.8033149492938425,82.91999999999999,95.14140000000005,2.316788853084559,745.1612140517698,324.38400000000007,4.635640000000003
+1436,1438,143924-52-1,OC4c3cccc2ccc1c5ccccc5(cc4(c1c23)),Training,1,1,94,0.4578155570406712,20.23,83.02180000000004,2.167966827575799,1013.4296448620271,256.304,4.541300000000003
+1437,1439,144280-50-2,O=[N+]([O-])c2ccc3oc1ccc(cc1c3(c2))[N+](=O)[O-],Training,1,1,94,0.5175755189960696,99.42,67.02880000000002,2.371822246494393,768.3685849938656,258.189,3.402400000000002
+1438,1440,144425-09-2,O=C1Oc2c3cc(OC)ccc3(cc(c2(C=C1))[N+](=O)[O-]),Training,1,0,100,0.3095448532605137,82.58,73.19640000000001,2.5530622634835423,897.0844555682155,271.228,2.8630000000000013
+1439,1441,14448-67-0,N(N)=C2N(c1ccccc1S2)C,Training,1,1,62,0.47585673156552405,43.309999999999995,50.54640000000001,2.976002585649184,466.3528629997788,179.24799999999996,1.0141999999999998
+1440,1442,144-48-9,O=C(N)CI,Training,0,1,30,0.44964764674553986,43.09,28.081400000000002,2.8473789230876716,44.912609383243264,184.964,-0.09329999999999988
+1441,1443,144561-63-7,O=[N+]([O-])c2ccc3c1cc4c(cc1CCc3(c2))CCCC4,Training,1,1,106,0.5785625726963264,43.14,82.58240000000005,1.859510935116503,749.1238129946602,279.339,4.239200000000003
+1442,1444,1445-69-8,O=C1NNC(=O)c2ccccc12,Training,0,0,60,0.5813853374586314,65.72,45.189400000000006,3.156967286258461,475.559165455531,162.148,0.21639999999999937
+1443,1445,144605-96-9,O=NN3C(c2[nH]c1ccc(cc1c2CC3(C(=O)OC))[N+](=O)[O-])C,Training,1,0,120,0.4010212655437124,117.9,80.51010000000002,2.1740786495573925,814.8456838397318,318.28900000000004,2.2181999999999995
+1444,1446,144-62-7,O=C(O)C(=O)O,Training,0,0,34,0.37994913775585776,74.6,15.2716,3.567703455043203,71.5488750216347,90.03399999999999,-0.8443999999999998
+1445,1447,144651-75-2,O=C(O)C3NC(c2[nH]c1ccccc1c2C3)Cc4ccccc4(O),Training,0,0,122,0.5972005785438643,85.35000000000001,91.11400000000003,1.79140393607985,915.8708294312287,322.36400000000003,2.756200000000001
+1446,1448,144730-01-8,O=C3c2cc(c1c4ccccc4(ccc1c2CC3))C(F)(F)F,Training,1,1,110,0.5252748753193351,17.07,79.10750000000004,2.265439479291221,938.3539155713424,300.27899999999994,5.140700000000002
+1447,1449,1447-88-7,O=C1C=C(Oc2cc(O)c(OC)c(O)c12)c3ccc(O)cc3,Training,0,0,112,0.6723108130019759,100.13000000000001,79.46640000000001,2.2945853186285357,908.5527285597918,300.266,2.5854
+1448,1450,144-80-9,O=C(NS(=O)(=O)c1ccc(N)cc1)C,Training,0,0,76,0.6828174314400922,89.26,51.85690000000001,3.047486126365013,436.159125541551,214.246,0.09359999999999968
+1449,1451,144-82-1,O=S(=O)(Nc1nnc(C)s1)c2ccc(N)cc2,Training,0,0,90,0.8173307365183631,97.97,66.30890000000002,2.2767262836744524,618.7003402944883,270.339,1.2295199999999997
+1450,1452,145142-70-7,O=C(ON(OCCCC)C(=O)c1ccc(cc1)c2ccccc2)C,Training,1,1,126,0.5941305413166198,55.839999999999996,90.67350000000005,2.1188451064981333,667.5259601734274,327.38000000000005,4.005600000000003
+1451,1453,145142-71-8,O=C(ON(OCCCC)C(=O)c1ccc(cc1)C(C)(C)C)C,Training,1,1,122,0.6154157299265783,55.839999999999996,83.93750000000006,2.854254916387612,502.38537723143105,307.3900000000001,3.6361000000000026
+1452,1454,145241-75-4,Fc1cc(F)c2ncccc2(c1),Training,1,1,60,0.5840485195000186,12.89,41.65900000000001,2.8920650451735157,425.7980911891212,165.142,2.513
+1453,1455,145241-76-5,Fc1ccc2cccnc2(c1(F)),Training,1,1,60,0.5840485195000186,12.89,41.659000000000006,2.9077745072579826,425.7980911891212,165.14199999999997,2.513000000000001
+1454,1456,145-39-1,O=[N+]([O-])c1c(c(c(c(c1C(C)(C)C)[N+](=O)[O-])C)C)C,Training,0,0,104,0.6024742555825864,86.28,72.66180000000003,4.034102107518916,529.9815533573726,266.29699999999997,3.725760000000003
+1455,1457,145438-96-6,O=NN(c1ncn(c1(C(=O)NC))C)C,Training,0,1,76,0.5415717431855829,79.59,50.79620000000002,3.1800742469642866,358.9621695139179,197.198,-0.10270000000000024
+1456,1458,145438-97-7,O=NN(C(=O)c1c(ncn1C)N(N=O)C)C,Training,1,1,86,0.5421674963262688,100.22999999999999,55.29450000000002,3.2066434603246474,427.75669591910264,226.19599999999997,0.2910999999999999
+1457,1459,145439-00-5,O=NN(C(=O)c1c(ncn1C)N(C(=O)OC(C)(C)C)C)C,Training,1,1,116,0.6224356672597929,97.10000000000001,75.73350000000005,3.1200523902094583,560.4842841814736,297.315,1.5448
+1458,1460,145439-03-8,O=NN(C(=O)c1c(ncn1C)NC)C,Training,1,0,76,0.5547108437784766,79.59,50.64320000000002,3.0992561567552284,358.96216951391784,197.19799999999998,0.21519999999999984
+1459,1461,145-49-3,O=C1c3c(O)ccc(N)c3(C(=O)c2c(O)ccc(N)c12),Training,1,1,100,0.35681972395939343,126.63999999999999,71.90339999999999,2.461802657327663,666.7462922813075,270.244,1.0375999999999999
+1460,1462,145531-22-2,[N-]=[N+]=Nc4ccc3c(nc1ccc(N=[N+]=[N-])cc1c3(Nc2ccc(cc2)NS(=O)(=O)CCCN))c4,Training,1,1,176,0.11039542211274915,194.63,137.66659999999996,1.7621329223851119,1607.4298409373685,488.53700000000026,6.105700000000005
+1461,1463,145531-23-3,[N-]=[N+]=Nc4ccc3c(nc1cc(N=[N+]=[N-])ccc1c3(Nc2ccc(cc2)NS(=O)(=O)CCCN))c4,Training,1,1,176,0.11039542211274915,194.63,137.66659999999996,1.7491835422393989,1531.4298409373682,488.53700000000026,6.105700000000005
+1462,1464,145531-24-4,[N-]=[N+]=Nc3ccc4nc1ccccc1c(Nc2ccc(cc2(OC))NS(=O)(=O)C)c4(c3),Training,1,1,156,0.18026392584454123,129.08,122.79820000000002,1.8981539602884263,1463.244436003904,434.4810000000002,5.453500000000004
+1463,1465,145569-98-8,O=C(OC)C(C=C(C=C(C=CC=C(C(=O)C12(OC2(C(O)(NC1(=O))CCO)))C)C)C)=CCO,Training,1,1,174,0.12363018153024154,145.69000000000003,115.00210000000004,2.0930796114377386,941.6430570541133,447.4840000000002,0.38069999999999987
+1464,1466,145627-68-5,OC2C=Cc1c3ccc4c(c3(ccc1C2(O)))CCC4,Training,1,1,96,0.7565748012749618,40.46,75.97360000000003,2.0421485786155795,699.9645494181885,252.31299999999996,2.749600000000001
+1465,1467,145627-69-6,OC2C=Cc1c3c(ccc1C2(O))c4c(cc3C)CCC4,Training,1,1,102,0.7690983013669618,40.46,80.71060000000003,2.0974197391898963,742.9020122882657,266.34,3.058020000000001
+1466,1468,145627-70-9,OC5c3ccc1c(ccc2c1CCC2)c3C4OC4C5(O),Training,1,1,102,0.7200102872078737,52.989999999999995,74.55360000000003,1.8336935324841959,736.5828031378987,268.31199999999995,2.1763
+1467,1469,1456-28-6,O=NN1CC(OC(C)C1)C,Training,1,1,58,0.5104704037725574,41.900000000000006,37.377,2.417613433147248,118.91622381280227,144.17399999999998,0.7769999999999999
+1468,1470,1456-55-9,O=C2N(C)C4(C(=O)N3C5N(c1c(OC)c(OC)c(cc1C5(O)(C(O)C23SS4))Cl)C)(C),Training,0,0,162,0.6035815841030472,102.78000000000002,112.58460000000001,1.807443285637722,1028.126126574389,473.96000000000004,0.8033000000000006
+1469,1471,145679-85-2,OC5c3ccc1c(c(cc2c1CCC2)C)c3C4OC4C5(O),Training,1,1,108,0.7299157355283321,52.989999999999995,79.29060000000003,1.8775677742162695,779.8624800361639,282.33899999999994,2.4847200000000007
+1470,1472,145763-35-5,O=C3OCC=C3(C=C(C=C(C=CC=C(C(=O)C12(OC2(C(O)(NC1(=O))CCO)))C)C)C),Training,1,1,160,0.175779666944725,125.46000000000002,106.85930000000003,1.656048908673071,939.1327198472565,415.4420000000002,0.7721999999999998
+1471,1473,146177-57-3,n1ccnc2c1c3nc(N)n(c3(cc2C))C,Training,1,1,80,0.6125617576025736,69.62,62.95940000000002,2.6379330683135027,698.2240623065195,213.24399999999997,1.4071199999999997
+1472,1474,146177-58-4,n1c(N)n(c2cc(c3nc(c(nc3(c12))C)C)C)C,Training,1,1,92,0.6534106863674991,69.62,72.43340000000002,2.6047549754545063,785.2622239646097,241.29799999999997,2.0239599999999998
+1473,1475,146177-59-5,n1ccnc3c1c2nc(N)n(c2c(c3C)C)C,Training,1,1,86,0.6344439144723893,69.62,67.69640000000001,2.6972875431442276,741.5606544292405,227.27099999999996,1.7155399999999998
+1474,1476,146177-60-8,n1cc(nc3c1c(c(c2c3(nc(N)n2C))C)C)C,Training,1,1,92,0.653410686367499,69.62,72.4334,2.675986976950849,785.2622239646096,241.29799999999994,2.0239599999999998
+1475,1477,146177-61-9,n1cc(nc3c1c2nc(N)n(c2c(c3C)C)C)C,Training,1,1,92,0.653410686367499,69.62,72.4334,2.661297192097986,785.2622239646096,241.29799999999994,2.0239599999999998
+1476,1478,146177-62-0,n1c(N)n(c3c1c2nc(c(nc2c(c3C)C)C)C)C,Training,1,1,98,0.6690215655597974,69.62,77.17040000000001,2.666371111771827,829.3156160850594,255.32499999999996,2.3323800000000006
+1477,1479,146177-63-1,n2c(N)n(c3ccc1nc(c(nc1c23)c4ccccc4)c5ccccc5)C,Training,0,1,130,0.5105872860631943,69.62,109.09440000000001,1.8978065795920764,1274.3589214100787,351.41300000000007,4.432700000000002
+1478,1480,146177-64-2,n1cc(nc3c1c(cc2c3(nc(N)n2C))C)c4ccccc4,Training,1,1,108,0.5843848863455381,69.62,88.3954,2.0986665764939403,1002.0925122999955,289.342,3.0741200000000015
+1479,1481,146177-65-3,n1cc(nc2c1c3nc(N)n(c3(cc2C))C)c4ccccc4,Training,1,1,108,0.5843848863455381,69.62,88.3954,2.0527933514860575,1002.0925122999955,289.342,3.0741200000000015
+1480,1482,146-22-5,O=C1Nc3ccc(cc3(C(=NC1)c2ccccc2))[N+](=O)[O-],Training,0,1,104,0.6771088741597446,84.6,78.67410000000002,2.198099775373001,754.0140888404637,281.271,2.3843000000000005
+1481,1483,14625-58-2,n1c(oc2ccccc12)c3cccc(c3)C,Training,0,0,78,0.6088199043422198,26.03,64.18200000000003,2.188768834307986,606.7853140522719,209.248,3.8032200000000023
+1482,1484,14628-90-1,O=C1C=CC(=CC=C1(OC))[N+](=O)[O-],Training,1,0,68,0.502984442746451,69.44,45.91840000000001,3.3150055762649675,388.24010037223206,181.147,0.9636
+1483,1485,1465-25-4,NCCNc2cccc1ccccc12,Training,1,0,72,0.7708911563863441,38.05,61.49210000000002,2.4297472261299626,418.0961725957642,186.25799999999998,2.2104
+1484,1486,146-56-5,FC(F)(F)c1ccc3c(c1)N(c2ccccc2S3)CCCN4CCN(CCO)CC4,Training,0,0,162,0.7278115473639661,29.950000000000003,113.59780000000006,1.4716669756319087,868.9465296058858,437.5310000000004,4.308100000000004
+1485,1487,146-59-8,n2c1ccc(OC)cc1c(NCCCN(CC)CCCl)c3ccc(cc23)Cl,Training,1,1,144,0.2928593664358786,37.39,116.75170000000003,1.8993904218019497,916.7017997337709,406.3570000000001,5.412700000000005
+1486,1488,146683-80-9,O2C3c4cc5ccccc5(cc4(c1c(cccc1C23)C)),Training,1,1,96,0.5201339718934308,12.53,80.68800000000005,1.9158545926580504,862.7692903384003,258.31999999999994,4.941220000000003
+1487,1489,1466-88-2,O=CC=Cc1ccccc1[N+](=O)[O-],Training,1,1,66,0.30589552850747875,60.209999999999994,48.19440000000001,3.112427326287727,357.6323762499241,177.15899999999996,1.8069000000000002
+1488,1490,146724-31-4,OCc2cc3ccc1cccnc1c3([nH]2),Training,0,1,74,0.6294133038191451,48.910000000000004,59.52250000000003,2.4732188463629114,627.6405121546441,198.225,2.2083999999999997
+1489,1491,146724-32-5,O=C(OC)c2cc3ccc1cccnc1c3([nH]2),Training,0,0,84,0.6484360605266297,54.98,64.93920000000003,2.3476254273233743,715.5895287465975,226.23499999999999,2.5027
+1490,1492,1467-79-4,N#CN(C)C,Training,0,0,28,0.2967543325075944,27.03,19.299999999999997,2.939447246323328,50.40362799390803,70.095,0.029079999999999995
+1491,1493,146795-26-8,O=C(Nc1ccc(OC)cc1)c2cc([N+](=O)[O-])sc2,Training,1,1,98,0.6882849299438668,81.47,71.92060000000001,2.084461741134886,606.4468736034538,278.289,2.917200000000001
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+1500,1502,146795-35-9,O=C(Nc1ccc(F)cc1)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6850957092946555,72.24,65.32660000000001,2.1128987724323425,594.5907229758122,266.253,3.0477000000000016
+1501,1503,146795-36-0,O=C(Nc1cccc(F)c1)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6850957092946555,72.24,65.32660000000001,2.1398737408792936,611.8407229758121,266.253,3.0477000000000007
+1502,1504,146795-37-1,O=C(Nc1ccccc1(F))c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6850957092946555,72.24,65.32660000000001,2.1698264026687077,611.8407229758121,266.25299999999993,3.0477000000000007
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+1504,1506,146795-39-3,O=C(Nc1cccc(c1)Cl)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6908351963967999,72.24,70.37860000000002,2.1398737408792936,611.8407229758121,282.70799999999997,3.562000000000001
+1505,1507,146795-40-6,O=C(Nc1ccccc1Cl)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6908351963967999,72.24,70.37860000000002,2.1698264026687077,611.8407229758121,282.70799999999997,3.562000000000001
+1506,1508,146795-41-7,O=C(Nc1ccc(cc1)Br)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6904244426929917,72.24,73.0686,2.1128987724323425,594.5907229758122,327.159,3.671100000000001
+1507,1509,146795-42-8,O=C(Nc1cccc(c1)Br)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6904244426929917,72.24,73.0686,2.1398737408792936,611.8407229758121,327.159,3.671100000000001
+1508,1510,146795-43-9,O=C(Nc1ccccc1Br)c2cc([N+](=O)[O-])sc2,Training,1,1,92,0.6904244426929917,72.24,73.0686,2.1698264026687077,611.8407229758121,327.159,3.671100000000001
+1509,1511,146795-44-0,O=C(Nc1ccc(cc1)[N+](=O)[O-])c2cc([N+](=O)[O-])sc2,Training,1,1,102,0.6869160820096621,115.38,72.02300000000001,2.1011231101732784,679.6219730332184,293.25999999999993,2.8168000000000015
+1510,1512,146795-45-1,O=C(Nc1cccc(c1)[N+](=O)[O-])c2cc([N+](=O)[O-])sc2,Training,1,1,102,0.6869160820096621,115.38,72.02300000000001,2.1622001356866005,696.8719730332183,293.25999999999993,2.8168000000000015
+1511,1513,146795-46-2,O=C(Nc1ccccc1[N+](=O)[O-])c2cc([N+](=O)[O-])sc2,Training,1,1,102,0.6869160820096621,115.38,72.02300000000001,2.2314491496988715,696.8719730332183,293.25999999999993,2.8168000000000015
+1512,1514,146795-48-4,O=C(c1cc([N+](=O)[O-])sc1)N(c2ccccc2)C,Training,1,1,92,0.6307001279435109,63.449999999999996,70.14890000000003,2.2295202870901183,580.0182758749165,262.29,2.932900000000001
+1513,1515,146818-20-4,O=C(Nc1ccc(cc1)CC)c2cc([N+](=O)[O-])sc2,Training,1,1,98,0.6860925971765544,72.24,74.74660000000002,2.0844617411348865,604.60581977411,276.31699999999995,3.4710000000000027
+1514,1516,1468-95-7,OCc2c3ccccc3(cc1ccccc12),Training,1,1,78,0.6068392074529543,20.23,67.37680000000003,2.562614287594416,601.7040048216327,208.26,3.4853000000000014
+1515,1517,14691-88-4,ON1C(C)(C)CC(N)CC1(C)C,Training,1,0,72,0.5797175868157824,49.489999999999995,48.99290000000002,2.835521890302059,159.36734879116756,172.272,1.3559
+1516,1518,14692-41-2,n1cccc3c1ccc2c3(ncn2C),Training,1,1,68,0.5341430205837688,30.71,56.015000000000015,2.6140649160081972,610.0317173319993,183.21399999999997,2.1214999999999997
+1517,1519,14698-29-4,O=C(O)C1=CN(c2cc3OCOc3(cc2(C1(=O))))CC,Training,1,1,98,0.8847688106737668,77.75999999999999,66.96430000000001,2.429100337665146,746.7624788594738,261.23299999999995,1.4483
+1518,1520,14703-71-0,O=[N+]([O-])c1c(O)cccc1(N),Training,0,0,58,0.3566686028760262,89.39,39.17360000000001,3.318913173486669,277.6289117242989,154.12499999999997,0.8826
+1519,1521,147151-61-9,O=C(OC4CCC2(C)(C(CCC1C3CCC(=O)NC3(C)(CCC12))C4))C=Cc5cccc(c5)N(CCCl)CCCl,Training,1,1,214,0.21035781449651525,58.64000000000001,159.17669999999967,1.1799855653605953,1073.248766178354,575.6210000000001,6.806900000000008
+1520,1522,147151-64-2,O=C(OC2CCC3C4CCC1=CC(=O)NCCC1(C)C4(CCC23(C)))C=Cc5cccc(c5)N(CCCl)CCCl,Training,0,1,212,0.21682197650135296,58.64000000000001,159.10469999999964,1.2478122770622961,1130.1657980464936,573.6050000000001,6.584500000000007
+1521,1523,147151-67-5,O=C(OC3CC2=CCC1C4CCC(=O)NC4(C)(CCC1C2(C)CC3))C=Cc5cccc(c5)N(CCCl)CCCl,Training,1,1,212,0.16228901199680718,58.64000000000001,159.15269999999964,1.2076779614288886,1130.1657980464936,573.6050000000001,6.727000000000008
+1522,1524,147-24-0,O(CCN(C)C)C(c1ccccc1)c2ccccc2,Training,0,0,100,0.784550440095116,12.47,79.23300000000006,2.1446055624492186,427.63544259070466,255.36100000000002,3.3542000000000023
+1523,1525,147293-13-8,n2cccc3ccc1c(nc(N)n1C)c23,Training,1,1,74,0.5978088445050177,56.73,60.427400000000006,2.600988463864526,654.0413933819901,198.22899999999996,1.7036999999999998
+1524,1526,147293-14-9,n2ccc3ccc1c(nc(N)n1C)c3(c2),Training,1,1,74,0.5978088445050178,56.73,60.42740000000001,2.600988463864526,654.0413933819901,198.22899999999998,1.7036999999999998
+1525,1527,147293-15-0,n1ccc2c3nc(N)n(c3(ccc2(c1)))C,Training,1,1,74,0.5978088445050178,56.73,60.42740000000002,2.6009884638645255,654.0413933819901,198.229,1.7036999999999998
+1526,1528,147318-81-8,O=C(NC(C(=O)NC(Cc1ccccc1)C(O)C(=O)N2CSCC2(C(=O)NC(C)(C)C))CSC)COc3cccc4cnccc34,Training,0,0,246,0.21557795460503137,149.95999999999998,181.48889999999957,1.4576157281011268,1513.9135119602172,667.8540000000003,2.3660000000000005
+1527,1529,147-47-7,c1ccc2c(c1)NC(C=C2C)(C)C,Training,0,0,68,0.6344286770888338,12.03,57.79470000000003,2.5497488306977703,361.1421555222323,173.25899999999996,3.2940000000000014
+1528,1530,1477-42-5,n1c(N)sc2cccc(c12)C,Training,0,1,56,0.6478348406982907,38.91,48.769400000000005,2.9003583079088235,391.8914302020468,164.23299999999998,2.1869199999999998
+1529,1531,1477-55-0,NCc1cccc(c1)CN,Training,0,0,54,0.6253132172200817,52.04,42.224800000000016,2.8711457287957725,188.91749419417292,136.19799999999995,0.604
+1530,1532,147974-61-6,O=C(c1cc(ccc1(N))Cc2ccc(N)c(c2)C(=O)C)C,Training,1,1,108,0.6665721257588407,86.18,84.52380000000002,2.3434063441292183,659.2252018546907,282.343,2.8470000000000013
+1531,1533,148021-80-1,O=C3c2ccc1c4C=CC(O)C(O)c4(ccc1c2CC3),Training,1,1,100,0.7694424149097111,57.53,76.60010000000001,2.0441828950364873,773.3890452824267,266.296,2.3898
+1532,1534,148174-23-6,O=C(N=C2c1ccccc1N(C(=O)CCCl)S2)CCCl,Training,0,1,106,0.8088402376509748,51.43,81.68550000000003,2.565740833757991,705.7042225682029,331.22400000000005,3.028100000000002
+1533,1535,148174-24-7,O=C(N=C2c1ccccc1N(C(=O)CCCCl)S2)CCCCl,Training,0,1,118,0.7367873031775998,51.43,90.91950000000003,2.4133023119425987,736.4628288605,359.278,3.8083000000000027
+1534,1536,148193-29-7,n3cc2cccc(OCC1OC1)c2s3,Training,1,1,72,0.7225493112983317,34.65,54.85500000000002,1.8935585451308745,450.0736536922578,207.254,2.0739
+1535,1537,148193-30-0,n2c(c1cc(N)ccc1s2)Cl,Training,1,1,56,0.639482602551298,38.91,49.04240000000001,2.8730859234238983,396.23994574764356,184.65099999999998,2.5319000000000003
+1536,1538,148193-31-1,n2c(c1cccc(N)c1s2)Cl,Training,1,1,56,0.639482602551298,38.91,49.04240000000001,2.941490232177503,396.2399457476436,184.65099999999998,2.5319000000000003
+1537,1539,148193-32-2,O=[N+]([O-])c1ccc2c(nsc2(c1))OC,Training,1,1,72,0.5626673388952586,65.26,52.82640000000003,2.627443517560262,494.29209068966935,210.21399999999997,2.2131
+1538,1540,148193-33-3,n2c(OC)c1ccc(N)cc1s2,Training,1,1,62,0.6815523127175505,48.14,50.58440000000002,2.7269901784620787,410.3501069254241,180.232,1.8871
+1539,1541,148193-34-4,n3c(OC)c2cc(OCC1OC1)ccc2s3,Training,1,1,84,0.7635921569968548,43.88,61.407000000000025,1.8659266680718272,506.8990260763053,237.28,2.0825
+1540,1542,148193-35-5,n3c(OC)c2ccc(OCC1OC1)cc2s3,Training,1,1,84,0.7635921569968548,43.88,61.407000000000025,1.8378723305297313,506.8990260763053,237.27999999999997,2.0825
+1541,1543,148193-36-6,n3c(OC)c2cccc(OCC1OC1)c2s3,Training,1,1,84,0.7635921569968548,43.88,61.40700000000004,1.9288645310078874,506.8990260763053,237.27999999999994,2.0825
+1542,1544,148193-37-7,O=C1NSc2cc(N)ccc12,Training,0,0,56,0.5770324516731969,58.879999999999995,46.85810000000001,2.9664750241250126,442.88245407860506,166.20499999999998,1.1718
+1543,1545,148193-38-8,O=C3c2ccc(OCC1OC1)cc2SN3CC4OC4,Training,1,0,100,0.7727115448815811,56.29,71.06000000000003,1.6130726911176303,668.8233205657455,279.317,1.2393999999999998
+1544,1546,148317-76-4,O=C2c1ccccc1C3=C2c4ccccc4(C(=O)N3CCNCCO),Training,0,1,126,0.546044366754328,71.33,97.03200000000004,1.9787281867879778,1036.780979836882,334.3750000000001,1.7948
+1545,1547,1484-12-4,c1ccc3c(c1)c2ccccc2n3C,Training,1,1,68,0.5010145222980148,4.93,60.42500000000003,2.6885238843864836,551.4846363033388,181.23799999999997,3.331500000000002
+1546,1548,148-53-8,O=Cc1cccc(OC)c1(O),Training,0,0,58,0.6477438574453785,46.53,40.046300000000016,3.195435194253712,268.03972257956417,152.14899999999997,1.2132999999999998
+1547,1549,14861-17-7,O(c1ccc(N)cc1)c2ccc(cc2Cl)Cl,Training,1,1,82,0.8074181641013488,35.25,67.39040000000001,2.2338171177404904,496.8719889797811,254.116,4.3679000000000014
+1548,1550,148-65-2,n1ccccc1N(Cc2ccc(Cl)s2)CCN(C)C,Training,0,0,102,0.8144411549958077,19.370000000000005,83.17000000000004,2.096666878106475,498.40200086647474,295.83900000000006,3.364700000000002
+1549,1551,148-79-8,n1cscc1c2nc3ccccc3([nH]2),Training,1,1,68,0.6572828314318542,41.57,57.20170000000002,2.244094775249905,520.5285963600785,201.25400000000002,2.6864
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+1551,1553,148-82-3,O=C(O)C(N)Cc1ccc(cc1)N(CCCl)CCCl,Training,1,1,106,0.720239222897486,66.55999999999999,79.41020000000005,2.7067949179355035,392.1346196779266,305.20500000000004,1.9249999999999996
+1552,1554,14882-94-1,O=C1Oc2cc3OC(Cc3(cc2(C=C1C(C=C)(C)C)))C(OC(=O)C)(C)C,Training,0,1,138,0.47212547637050095,65.74000000000001,99.67200000000005,2.0230067854775933,948.7631544789208,356.4180000000001,3.9018000000000024
+1553,1555,14901-07-6,O=C(C=CC1=C(C)CCCC1(C)C)C,Training,0,0,78,0.6101503454772369,17.07,60.15300000000004,2.96127747123545,292.35742381695854,192.302,3.6582000000000026
+1554,1556,149022-16-2,Oc1ccc2c(c1)[nH]c3c(nccc23)C,Training,1,1,74,0.5831173613840934,48.91,60.001500000000014,2.569945350412583,655.0755911783466,198.225,2.7301200000000003
+1555,1557,149127-56-0,OOC(N=NC)(C)C,Training,1,1,48,0.3372151941909752,54.18,28.572799999999987,3.7141365611929857,90.03910001730776,118.13599999999998,1.2941
+1556,1558,149127-57-1,OOC(N=NCC)(C)C,Training,0,1,54,0.360588689832148,54.18,33.18979999999999,3.6996952491541264,101.13111721021241,132.16299999999998,1.6842
+1557,1559,149127-58-2,OOC(N=NCCC)(C)C,Training,1,1,60,0.37473649643461066,54.18,37.8068,3.6302496935437243,112.3154437621596,146.19,2.0743
+1558,1560,14919-77-8,O=C(NNCc1ccc(O)c(O)c1(O))C(N)CO,Training,1,1,100,0.24400755497559506,148.07,61.48000000000002,2.548568974159402,437.7664825155729,257.246,-1.7562000000000006
+1559,1561,14925-39-4,O=CC(=C)Br,Training,1,1,28,0.38814676754923916,17.07,24.130999999999997,3.204805417886435,57.91340299823497,134.95999999999998,1.0939
+1560,1562,149-32-6,OCC(O)C(O)CO,Training,0,0,50,0.338933418507044,80.92,26.18519999999999,3.292478156075495,48.0,122.11999999999999,-2.3071999999999995
+1561,1563,149396-88-3,O=[N+]([O-])c1cnc(n1C)C(O)c2cc(OC)cc(c2(O))C(C)(C)C,Training,1,0,130,0.6555577547599837,110.65,87.28300000000003,2.611305903119354,776.7505636482674,335.3600000000001,2.4217000000000004
+1562,1564,149396-89-4,O=[N+]([O-])c1cnc(n1C)C(O)c2cc(cc(c2(O))C(C)(C)C)C(C)(C)C,Training,0,0,142,0.6408380263792417,101.42,99.43100000000005,2.6997009005102774,841.6898438996678,361.4420000000002,3.710600000000002
+1563,1565,149396-90-7,O=[N+]([O-])c1cnc(n1C)C(O)c2cc(cc(c2(O))C(C)(C)C)C,Training,0,0,124,0.6688002251974927,101.42,85.46800000000003,2.5832019636463937,759.4163328709396,319.3610000000001,2.721520000000001
+1564,1566,149396-91-8,O=[N+]([O-])c1cnc(n1C)C(O)c2c(O)c(ccc2C)C(C)(C)C,Training,0,0,124,0.6688002251974927,101.42,85.46800000000003,2.6011814387956744,759.4163328709396,319.3610000000001,2.721520000000001
+1565,1567,149418-41-7,O=C1OCC(=C1Br)Br,Training,1,1,44,0.6019363352718591,26.3,35.839,2.8648876586152836,161.42124551085627,241.86599999999999,1.5446
+1566,1568,14953-62-9,O=[N+]([O-])c2[nH]cnc2(c1ccccc1),Training,1,1,70,0.5795171757015773,71.82,50.67810000000002,2.522989098837681,450.090443367725,189.17400000000004,1.9848999999999999
+1567,1569,14953-63-0,O=[N+]([O-])c1c(ncn1C)c2ccccc2,Training,1,1,76,0.5535471513966052,60.96,55.29840000000002,2.5924539204507857,490.6235375029438,203.20100000000002,1.9952999999999999
+1568,1570,149573-80-8,O=Nn1cnc(c1)CC(=O)NO,Training,1,1,64,0.3613872093866969,96.58,37.0532,2.6341744596807466,294.63836858050365,170.12800000000001,-0.5395000000000003
+1569,1571,149862-55-5,n2c1ccccc1c(NCCCC)s2,Training,0,0,74,0.7742670837981703,24.92,63.01770000000003,2.1670908071296395,408.33466552272984,206.31399999999996,3.508300000000002
+1570,1572,149862-56-6,n2c1ccccc1c(NCCCCC)s2,Training,0,0,80,0.7729718492348818,24.92,67.63470000000004,2.017150386257655,422.2342701321014,220.34099999999995,3.8984000000000023
+1571,1573,149862-57-7,n2c1ccccc1c(NCCC(C)C)s2,Training,0,0,80,0.8483703562033346,24.92,67.56470000000003,2.0795958393709766,433.8696692668343,220.34099999999998,3.7543000000000024
+1572,1574,149-91-7,O=C(O)c1cc(O)c(O)c(O)c1,Training,0,0,64,0.45988822950048275,97.99000000000001,38.39570000000001,3.306535412749064,307.56377472599723,170.11999999999998,0.5015999999999998
+1573,1575,149922-82-7,c1ccc5c(c1)cc4c3c5(ccc2cccc(c23)C4Cl),Training,1,1,94,0.28124067596933583,0.0,86.65600000000002,2.1679668275757997,1013.4296448620271,274.75,5.787800000000003
+1574,1576,14992-81-5,C=Cc1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,0,70,0.46262600559316364,0.0,61.58300000000001,3.6578071781815327,340.2825150477956,276.377,5.5966000000000005
+1575,1577,1499-54-3,O=C(NCC(=O)NO)c1ccccc1,Training,1,1,74,0.4649401214591356,78.43,48.704400000000014,2.477088871072,324.088768546336,194.19000000000003,-0.07820000000000027
+1576,1578,149996-82-7,O=NN(C=O)CC,Training,1,1,40,0.2890047582363909,49.74,24.23899999999999,3.355805391901801,65.33515884998701,102.093,0.1461
+1577,1579,150-13-0,O=C(O)c1ccc(N)cc1,Training,0,0,52,0.5665891872452881,63.31999999999999,37.813700000000004,3.003400684579818,240.2879489264805,137.138,0.9670000000000001
+1578,1580,150147-09-4,OCCN(c2ncc(N=Nc1ccc(cc1)N(CCO)CCO)cc2)CCO,Training,0,0,152,0.4003404509961658,125.01,107.62420000000004,2.0247165982218314,635.7688538696674,389.4560000000002,1.0789999999999993
+1579,1581,150-30-1,O=C(O)C(N)Cc1ccccc1,Training,0,0,64,0.6904627990029388,63.31999999999999,45.75720000000002,2.5846040823975205,258.4908622767174,165.192,0.6409999999999995
+1580,1582,150366-18-0,N#CCCC(O)c2nc1ccc(cc1s2)N3C(=O)OC(COC)C3,Training,0,1,126,0.8627647459636777,95.68,88.91780000000003,1.8125997744743998,785.2107705919142,347.3960000000002,2.60508
+1581,1583,1503-91-9,O=C(N(O)c1ccc(cc1)Cl)C,Training,0,0,64,0.5377173648555731,40.540000000000006,46.39850000000002,2.8925610901856844,283.6142639365964,185.60999999999999,2.0820999999999996
+1582,1584,150445-96-8,O=[N+]([O-])c4ccc2c(nc(C=NOCc1ccccc1[N+](=O)[O-])n2Cc3ccccc3)c4,Training,1,0,160,0.23041499305821053,125.69000000000003,117.41080000000002,1.6223163393029694,1317.0530968646622,431.4080000000002,4.451700000000003
+1583,1585,150445-97-9,O=[N+]([O-])c1cccc(c1)CON=Cc3nc2cc(ccc2n3Cc4ccc(cc4)Cl)[N+](=O)[O-],Training,0,1,166,0.20212874147865367,125.69000000000003,122.42080000000003,1.6021714201913053,1367.6217237199266,465.8530000000001,5.105100000000005
+1584,1586,150445-98-0,O=[N+]([O-])c4ccc2c(nc(C=NOCc1ccccc1[N+](=O)[O-])n2Cc3ccc(cc3Cl)Cl)c4,Training,1,0,172,0.1720958233343597,125.69000000000003,127.43080000000002,1.6543522634035386,1436.7302555046817,500.29800000000023,5.758500000000003
+1585,1587,150445-99-1,O=[N+]([O-])c4ccc2c(nc(C=NOCc1cccc(c1)[N+](=O)[O-])n2Cc3ccc(F)cc3)c4,Training,0,1,166,0.21998128751832935,125.69000000000003,117.36880000000002,1.6021714201913058,1367.6217237199266,449.39800000000014,4.590800000000003
+1586,1588,150446-00-7,O=[N+]([O-])c1cccc(c1)CON=Cc3c2cc(ccc2n(c3C)Cc4ccccc4)[N+](=O)[O-],Training,1,0,166,0.20606221617277062,112.80000000000001,124.35280000000003,1.6437912023103387,1362.2997597870763,444.4470000000002,5.365120000000005
+1587,1589,150446-01-8,O=[N+]([O-])c1ccc3c(c1)c(C=NOCc2ccc(cc2Cl)Cl)c(n3Cc4ccc(cc4)Cl)C,Training,0,1,168,0.14994344441962243,69.66,132.72839999999994,1.6677306948930388,1365.1349627506959,502.78500000000014,7.417120000000004
+1588,1590,150446-02-9,O=[N+]([O-])c1ccc3c(c1)c(C=NOCc2ccc(cc2)Cl)c(n3Cc4ccccc4)C,Training,0,1,156,0.20037445448001379,69.66,122.70840000000001,1.6645524663718125,1248.801075611321,433.8950000000001,6.110320000000005
+1589,1591,150446-03-0,O=[N+]([O-])c1cccc(c1)Cn3c4ccc(cc4(c(C=NOCc2ccccc2)c3C))[N+](=O)[O-],Training,1,0,166,0.20606221617277062,112.80000000000001,124.35280000000003,1.7034753836292587,1362.2997597870763,444.4470000000002,5.365120000000005
+1590,1592,150446-04-1,O=[N+]([O-])c1ccc2c(c1)c(c(n2Cc3ccccc3)C)Cn4cncc4,Training,1,1,130,0.40262397380153364,65.89,100.20240000000003,1.8783526131037775,1066.3457054868743,346.39000000000004,4.151020000000003
+1591,1593,1504-74-1,O=CC=Cc1ccccc1(OC),Training,1,0,62,0.500938838941861,26.3,48.09200000000003,2.960974340860822,289.64498298772276,162.18799999999996,1.9073
+1592,1594,150-60-7,c1ccc(cc1)CSSCc2ccccc2,Training,1,0,82,0.5504188095909515,0.0,75.47400000000003,1.6982174709605096,356.0952225964737,246.4,4.768200000000004
+1593,1595,150-68-5,O=C(Nc1ccc(cc1)Cl)N(C)C,Training,0,0,70,0.7388016668237095,32.34,54.15770000000002,2.646093538970966,294.9879407824652,198.65299999999996,2.4335000000000004
+1594,1596,150-69-6,O=C(N)Nc1ccc(OCC)cc1,Training,0,1,70,0.7411654495143486,64.35000000000001,50.81710000000002,2.6359726406075623,282.1711052507959,180.20699999999997,1.5759000000000003
+1595,1597,150-76-5,Oc1ccc(OC)cc1,Training,0,0,48,0.6127725486570803,29.46,34.6588,2.8815558776461354,178.61256853719755,124.13899999999998,1.4008
+1596,1598,150-78-7,O(c1ccc(OC)cc1)C,Training,0,0,54,0.6189113153967103,18.46,39.546000000000014,2.7972512629697874,167.91749419417292,138.166,1.7038
+1597,1599,15088-70-7,O=C(OCC)CNC(=O)CBr,Training,0,1,64,0.5422503683371357,55.4,43.436700000000016,3.376141118426766,148.76282190103143,224.05399999999997,0.060600000000000265
+1598,1600,15104-03-7,O=NN1CCC(C)CC1,Training,1,1,52,0.4998709700388202,32.67,35.766,2.255115324010933,97.23098268032228,128.17499999999998,1.3997
+1599,1601,15110-74-4,O=[N+]([O-])c2ccc3c1c(cccc1Cc3(c2))[N+](=O)[O-],Training,1,1,94,0.520386281365871,86.28,67.99280000000002,2.225147451632783,724.5783106971867,256.217,3.074200000000001
+1600,1602,151109-62-5,O=C3c2cc(c1c4C=CC(O)C(O)c4(ccc1c2CC3))C(F)(F)F,Training,1,1,124,0.7762054158222167,57.53,81.60210000000002,2.1577936673819247,912.0905436004631,334.293,3.4086000000000007
+1601,1603,151-18-8,N#CCCN,Training,0,0,28,0.4664303712842974,49.81,19.2844,2.483699570591265,43.344977967946406,70.095,-0.14122
+1602,1604,15121-84-3,O=[N+]([O-])c1ccccc1CCO,Training,1,1,64,0.5417475266576313,63.370000000000005,43.886200000000024,2.9976300631078683,285.3863912728923,167.16399999999996,1.1296
+1603,1605,15131-84-7,O3C4c5ccccc5(c2ccc1ccccc1c2C34),Training,1,1,90,0.525011143629999,12.53,75.95100000000004,1.9395601511469522,818.7881607391033,244.293,4.632800000000003
+1604,1606,1513-65-1,Fc1nc(F)ccc1,Training,0,0,42,0.46499899164539066,12.89,24.153,3.077660437970554,170.2884734445621,115.08199999999998,1.3598
+1605,1607,151378-32-4,OC2c5cccc4c1c6ccccc6(ccc1C3(OC3(C2(O)))(c45)),Training,1,1,112,0.6278749006091012,52.989999999999995,86.00360000000003,1.8120218810233373,1008.9394614841586,302.329,2.870500000000003
+1606,1608,151378-34-6,OC6c4ccc3c2cccc1cccc(c12)c3c4C5OC5C6(O),Training,1,1,112,0.489864650905983,52.989999999999995,86.9586,1.7554264236547859,1001.9345739819951,302.329,3.335000000000003
+1607,1609,151455-09-3,O=C(O)c2cc1OCOc1c3c4cc(OC)cc(OC)c4(cc(c23)[N+](=O)[O-]),Training,0,1,138,0.4214291551417849,117.36000000000001,94.29470000000006,2.33474044605542,1137.8450305058102,371.30100000000016,3.3453000000000017
+1608,1610,151-56-4,N1CC1,Training,1,0,18,0.36613880903998086,21.94,12.869700000000002,2.25,7.509775004326937,43.068999999999996,-0.4104000000000001
+1609,1611,1516-21-8,O=Nc1ccc(OC)cc1,Training,1,1,52,0.5851724886791005,38.66,38.44900000000002,2.895351845489354,217.5526454939854,137.13799999999998,2.0930999999999997
+1610,1612,1516-71-8,[N-]=[N+]=Nc2nc1c3ccccc3(ccc1n2C),Training,1,1,82,0.3523088494686262,66.58000000000001,67.02600000000002,2.5069991697201743,765.0076245514706,223.239,3.668300000000002
+1611,1613,1516-73-0,[N-]=[N+]=Nc2nc1ccccc1n2C,Training,1,1,64,0.3708419809023367,66.58000000000001,49.52000000000002,2.804076496651331,492.2037372448764,173.17899999999997,2.5151000000000003
+1612,1614,1516-74-1,[N-]=[N+]=Nc1nc2ccccc2([nH]1),Training,1,1,58,0.38695161052401317,77.44,44.89970000000001,2.690941225685865,418.5196043478405,159.152,2.5046999999999997
+1613,1615,1517-05-1,[N-]=[N+]=NCCO,Training,1,1,34,0.2932581938031057,68.99000000000001,21.098799999999997,2.85600674522422,65.19344939991072,87.082,0.289
+1614,1616,151751-83-6,O=NN(C(=O)OCC)CCC=O,Training,1,1,68,0.3492164550066315,76.03999999999999,40.204000000000015,3.8617659653395138,170.93102051518318,174.15599999999998,0.7153
+1615,1617,15176-29-1,O=C1NC(=O)N(C=C1CC)C2OC(CO)C(O)C2,Training,0,0,100,0.6258377504628361,104.55000000000001,62.32030000000003,2.3494776591947035,534.970489178027,256.258,-1.2603000000000006
+1616,1618,151910-74-6,OC3C=Cc2c4cc5ccc1c(C=CC(O)C1(O))c5(cc4(ccc2C3(O))),Training,0,1,130,0.4719956513719803,80.92,101.4552,1.8069656248550698,1022.7663486075745,346.38200000000006,2.8352000000000026
+1617,1619,151910-75-7,OC2C=Cc1c3cc5c(cc3(ccc1C2(O)))c4ccccc4C(O)C5(O),Training,0,1,130,0.5043951772200385,80.92,99.30420000000001,1.8196945641376345,1069.170464333737,346.38200000000006,3.0083000000000024
+1618,1620,1520-21-4,C=Cc1ccc(N)cc1,Training,1,1,46,0.5613086802775786,26.02,40.945400000000014,3.0097819477866,198.31254955650078,119.16699999999999,1.9118000000000002
+1619,1621,152-18-1,O(C)P(OC)(OC)=S,Training,0,1,50,0.5727084241256473,27.69,35.312,3.7910098125875025,85.68210765868758,156.14299999999997,1.1501
+1620,1622,152-20-5,O=P(OC)(OC)SC,Training,0,0,50,0.5829372327177553,35.53,35.1395,3.7910098125875016,85.68210765868758,156.143,1.7502999999999997
+1621,1623,1522-92-5,OCC(CBr)(CBr)CBr,Training,1,1,56,0.7857135851919995,20.23,50.90080000000002,3.824684203207495,55.09358392980084,324.83799999999997,2.1498
+1622,1624,15254-64-5,c1ccc3c(c1)ccc2cc(cc(c23)C)C,Training,1,1,78,0.4710734601666233,0.0,70.92800000000004,2.5981174015438255,677.9984465766784,206.28799999999995,4.609840000000003
+1623,1625,152-84-1,O=C3c5ccccc5(C(=O)c4c(O)c(OC2OC(COC1OCC(O)C(O)C1(O))C(O)C(O)C2(O))ccc34),Training,0,1,204,0.18553892411207848,212.67,122.43560000000002,1.334310818865824,1231.7333113032673,534.4700000000001,-2.1903999999999995
+1624,1626,1528-74-1,O=[N+]([O-])c1ccc(cc1)c2ccc(cc2)[N+](=O)[O-],Training,1,1,90,0.6124206955055239,86.28,65.18680000000002,2.308527167558888,534.979404881328,244.206,3.1700000000000017
+1625,1627,15299-08-8,c1ccc3c(c1)cc4c2cc(ccc2c5c6ccccc6(cc3c45))C,Training,1,1,116,0.20693231142406437,0.0,108.12700000000004,1.9810360346207099,1339.1508948716862,316.4030000000001,7.102020000000004
+1626,1628,153117-10-3,O=NN(CCCC)CC(OCc1ccccc1)CO,Training,1,0,106,0.5213599620609738,62.13000000000001,74.38080000000005,2.373691501443642,345.8041302504847,266.341,2.3476000000000012
+1627,1629,153260-24-3,n1c(N)sc2c1C3CCCNC3(CC2),Training,0,1,76,0.6806725049232961,50.94,58.613100000000024,1.9825886605498473,347.13635186398085,209.31799999999996,1.5071
+1628,1630,153260-26-5,O=C(Nc3nc2C1=CCCN(CC=C)C1CCc2s3)C,Training,0,1,106,0.8702311557480994,45.230000000000004,82.89070000000004,1.906572845241011,575.6737986181815,289.40399999999994,2.6914000000000007
+1629,1631,153260-27-6,n2cccc3c1ncsc1CCc23,Training,0,1,64,0.6336569442599087,25.78,52.75300000000002,2.2994531779351313,447.6903249764533,188.25499999999997,2.3037
+1630,1632,153260-28-7,n2cccc3c1nc(N)sc1C(C)(C)Cc23,Training,1,0,82,0.7579329519778534,51.8,66.48740000000002,2.3250340204852336,557.141558026284,231.32399999999998,2.6210000000000013
+1631,1633,15356-70-4,OC1CC(C)CCC1(C(C)C),Training,0,0,66,0.6179494584335712,20.23,47.34980000000002,2.437159260034696,120.0411847243922,156.26899999999998,2.4395000000000007
+1632,1634,153654-32-1,O=[N+]([O-])c2ccc3[nH]c1c(cc(c(O)c1[N+](=O)[O-])[N+](=O)[O-])c3(c2),Training,1,1,116,0.5526443596258548,165.44000000000003,77.43269999999998,2.526067299611121,1023.3343538465563,318.201,2.7513000000000005
+1633,1635,153654-33-2,O=[N+]([O-])c1cc3c(cc1(O))[nH]c2ccccc23,Training,1,1,84,0.49604250867203176,79.16,64.12390000000002,2.473765347462536,745.925182405841,228.20700000000002,2.9349
+1634,1636,153654-34-3,O=[N+]([O-])c2cc1c3ccccc3([nH]c1c(c2(O))[N+](=O)[O-]),Training,1,1,100,0.5485777223057716,122.30000000000001,70.7783,2.580489505505343,883.5568168275274,273.204,2.8431
+1635,1637,153654-35-4,O=[N+]([O-])c2c(O)ccc1c3ccccc3([nH]c12),Training,0,1,84,0.49604250867203176,79.16,64.12390000000003,2.556987846666295,745.925182405841,228.207,2.9349000000000007
+1636,1638,153-78-6,Nc2ccc3c1ccccc1Cc3(c2),Training,1,1,68,0.5301091582882801,26.02,59.09640000000002,2.274244663498904,500.33879156140733,181.23799999999997,2.8400000000000007
+1637,1639,15386-58-0,O=C2N(c1ccc(c(c1)Cl)Cl)C(=O)CC2,Training,0,0,78,0.7118590099339056,37.38,58.189000000000014,2.407405462958875,429.0485707542534,244.0769999999999,2.6468000000000007
+1638,1640,153954-29-1,OCc3cc1ncc(nc1c2nc(N)n(c23)C)C,Training,1,1,92,0.6623737367328514,89.85,68.88220000000001,2.582511394499673,762.0791323777144,243.26999999999998,0.8994199999999999
+1639,1641,153-98-0,Oc1ccc2[nH]cc(c2(c1))CCN,Training,0,0,68,0.6468452624532928,62.03999999999999,52.72190000000001,2.576000355142546,419.7820090914246,176.21899999999997,1.3747
+1640,1642,154028-32-7,O(c2cccc(C=Cc1ccc(N)cc1)c2)C,Training,1,1,86,0.6410985982688429,35.25,72.77640000000002,2.1638256008867813,514.6999584541678,225.291,3.4478000000000018
+1641,1643,15403-45-9,O=C(OC)c1cc(ccc1(N))c2ccc(N)c(c2)C(=O)OC,Training,1,0,114,0.664018092159369,104.64,83.38180000000001,2.5278299487551004,677.4208195249173,300.314,2.0911999999999997
+1642,1644,154159-06-5,C2C1C(CCl)(C(Cl)Cl)C(CC1(Cl)Cl)(C(Cl)Cl)C2(Cl)Cl,Training,0,0,112,0.4284053144373024,0.0,88.17200000000001,2.719738475072829,379.1966168974202,448.259,6.576800000000001
+1643,1645,154-41-6,OC(c1ccccc1)C(N)C,Training,0,0,60,0.6637111557988821,46.25,45.05120000000002,2.767917781307444,208.06253483771292,151.20899999999995,1.0672000000000001
+1644,1646,15444-20-9,O=C1c3nccc4cc(OC)c(OC)c(c2ccccc12)c34,Training,1,1,108,0.5672182950127347,48.42,83.71550000000003,2.275793671199055,931.0087410403206,291.306,3.463400000000002
+1645,1647,154-69-8,n1ccccc1N(Cc2ccccc2)CCN(C)C,Training,0,0,100,0.7908033413514379,19.370000000000005,80.28300000000004,2.1023390727063194,467.86742338979684,255.365,2.649800000000001
+1646,1648,154-93-8,O=NN(C(=O)NCCCl)CCCl,Training,1,1,70,0.4236058600444414,61.77,47.339700000000015,3.76615173955013,155.62875863456514,214.052,1.157
+1647,1649,155014-05-4,Fc1cnc2cccc(N)c2(c1),Training,1,1,60,0.601154234546762,38.91,46.113400000000006,2.8771445584268402,425.7980911891212,162.16699999999994,1.9561
+1648,1650,155014-06-5,O=C(Nc2cccc1cc(F)cnc12)C,Training,1,1,76,0.7741289163798877,41.99,56.004700000000014,2.6023705288305456,524.9768903137901,204.20399999999995,2.3323
+1649,1651,155-09-9,NC2CC2(c1ccccc1),Training,0,0,52,0.6169364851642573,26.02,41.775400000000026,2.2038147347065578,217.42969243757128,133.194,1.5011999999999999
+1650,1652,1551-44-6,O=C(OC1CCCCC1)CCC,Training,0,0,70,0.6085520277708585,26.3,47.87300000000003,2.1520380845200338,136.77400566229178,170.25199999999998,2.6624000000000008
+1651,1653,155144-64-2,O=C1C=C3N(C(=O)N1(O))c2cc(F)c(cc2N3C4CC4)c5cc(nc(c5)C)C,Training,1,1,142,0.5423989723070296,81.52999999999999,101.5415,1.932293560150217,1389.2370890535333,380.3790000000002,2.806040000000001
+1652,1654,155164-57-1,O=C1C(=C(C=NN1S(=O)(=O)c2ccccc2)Cl)Cl,Training,0,0,94,0.8479364015466342,69.03,67.54280000000003,2.7101062081692384,741.4632634711622,305.14200000000005,1.7871000000000001
+1653,1655,155164-58-2,O=C1C(=C(C=NN1S(=O)(=O)c2ccc(cc2)C)Cl)Cl,Training,0,0,100,0.8498499916703516,69.03,72.27980000000002,2.6730324048897773,782.5778640065146,319.169,2.09552
+1654,1656,155164-59-3,O=C1C(=C(C=NN1S(=O)(=O)c2ccc(OC)cc2)Cl)Cl,Training,0,0,106,0.8545874260094879,78.26,74.09480000000003,2.6056154785880037,800.1631043939726,335.168,1.7957
+1655,1657,155164-60-6,O=C1C(=C(C=NN1S(=O)(=O)c2ccc(cc2)Cl)Cl)Cl,Training,0,0,100,0.8424657155781998,69.03,72.55280000000002,2.6730324048897773,784.6574433604877,339.587,2.440500000000001
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+1661,1663,155164-67-3,O=C(c1ccc(cc1)C)N2N=CC(=C(C2(=O))Cl)Cl,Training,0,0,92,0.8077641746310545,51.96,69.42450000000001,2.500637962418539,662.7678950436214,283.114,2.5470200000000007
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+1665,1667,155379-82-1,O=[N+]([O-])c1cc(N)cc(c1(N))C,Training,1,1,64,0.37116878927500957,95.17999999999999,46.6582,3.3738590108748685,335.66852769827057,167.16799999999998,1.06762
+1666,1668,155379-83-2,O=[N+]([O-])c1c(N)c(cc(N)c1C)C,Training,1,1,70,0.38830895814919625,95.17999999999999,51.39520000000001,3.5551420285916264,347.89215552223243,181.19499999999996,1.37604
+1667,1669,15545-48-9,O=C(Nc1ccc(c(c1)Cl)C)N(C)C,Training,0,0,76,0.7629960812555915,32.34,58.89470000000002,2.781208374094021,349.9752768616324,212.67999999999998,2.7419200000000012
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+1683,1685,1570-64-5,Oc1ccc(cc1C)Cl,Training,0,0,48,0.5897674587091335,20.23,37.85380000000001,3.1716780304409156,220.15617759993404,142.58499999999998,2.3540200000000002
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+1686,1688,15743-13-2,O=C1C(=C(C(=O)C1(Cl)Cl)Cl)Cl,Training,0,1,60,0.473979920829504,34.14,43.18300000000001,3.2394527050259523,252.20700504797264,233.865,2.0012999999999996
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+1725,1727,159092-80-5,O=[N+]([O-])c1ccc3c(c1)c(cc2cccc(c23)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,114,0.41125247234536727,129.42000000000002,81.41720000000004,2.5690858085868715,1014.2317338423622,313.225,3.717600000000002
+1726,1728,159092-81-6,O=[N+]([O-])c1ccc2c(c1)cc(c3ccc(cc23)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,114,0.41125247234536727,129.42000000000002,81.41720000000004,2.477560607084302,1014.2317338423622,313.225,3.717600000000002
+1727,1729,159092-84-9,O=[N+]([O-])c1ccc2cc(c3ccc(cc3(c2(c1)))[N+](=O)[O-])[N+](=O)[O-],Training,1,1,114,0.41125247234536727,129.42000000000002,81.41720000000004,2.5051934416622177,1014.2317338423622,313.225,3.717600000000002
+1728,1730,159092-85-0,O=[N+]([O-])c1ccc3c(c1)c2c(cccc2[N+](=O)[O-])cc3[N+](=O)[O-],Training,1,1,114,0.41125247234536727,129.42000000000002,81.41720000000002,2.596912070305402,1002.2317338423621,313.225,3.717600000000002
+1729,1731,1591-56-6,O=C(Nc2ccc(N=Nc1ccc(cc1)N(C)C)cc2)C,Training,1,1,108,0.8572088211128207,57.06,85.69070000000005,2.0451284466011566,630.3314817687708,282.34700000000004,4.126400000000003
+1730,1732,159394-72-6,N#Cc2cccc(C=Cc1ccc(cc1)[N+](=O)[O-])c2,Training,1,1,92,0.4741795495940828,66.92999999999999,73.18140000000001,2.1785790811269012,667.2900842263577,250.25699999999998,3.6368800000000023
+1731,1733,159416-83-8,Oc3ccc(O)c4c(OC)c(c1cc(O)c2c(OC)cc(cc2(c1(O)))C)c(cc34)C,Training,0,0,154,0.3526988517774165,99.38000000000001,116.12720000000002,2.172289164373976,1323.562333201286,406.4340000000002,5.116440000000004
+1732,1734,1594-56-5,N#CSc1ccc(cc1[N+](=O)[O-])[N+](=O)[O-],Training,1,1,76,0.33671210853308775,110.07,51.2208,3.2771084979110388,467.79336860597874,225.18499999999997,2.07618
+1733,1735,15950-66-0,Oc1ccc(c(c1Cl)Cl)Cl,Training,0,0,54,0.6324908101043021,20.23,43.13680000000001,3.3421538077705124,232.41499587006638,197.448,3.3524000000000003
+1734,1736,15961-88-3,[O-][N+](=Nc2ccc3c1ccccc1Cc3(c2))c5ccc6c4ccccc4Cc6(c5),Training,0,1,138,0.18750221473230858,38.43,114.74340000000002,1.3291614515950476,1320.099637180764,374.44300000000015,6.754700000000005
+1735,1737,1596-84-5,O=C(O)CCC(=O)NN(C)C,Training,0,1,64,0.5409408843832045,69.63999999999999,38.69950000000001,3.4541025653196717,155.90638535044312,160.173,-0.556
+1736,1738,159714-84-8,c1ccc2cc4c(cc2(c1))c3c(cccc3C5NC45)C,Training,1,1,96,0.5877598926839473,21.94,82.73870000000004,1.9158545926580508,862.7692903384004,257.33599999999996,4.514220000000003
+1737,1739,159714-85-9,O3C4c5ccccc5(c2cc1ccccc1c(c2C34)CC),Training,1,1,102,0.5549177876391853,12.53,85.32900000000005,1.939077442027344,878.1408518693399,272.34700000000004,5.195200000000003
+1738,1740,159714-86-0,c1ccc4c(c1)cc3c2ccccc2C5NC5(c3c4CC),Training,1,1,102,0.6327035033732831,21.94,87.37970000000004,1.939077442027344,878.14085186934,271.363,4.768200000000004
+1739,1741,15980-15-1,O1CCSCC1,Training,0,0,36,0.4482458192403558,9.23,28.14399999999999,2.0,23.019550008653873,104.17399999999999,0.7498
+1740,1742,160543-00-0,OCc2c3ccc4ccccc4(c3(nc1ccc(cc12)C)),Training,1,1,102,0.41313080357456766,33.120000000000005,87.41480000000004,2.275649986342755,988.6829352406405,273.33500000000004,4.3419200000000036
+1741,1743,160543-02-2,OCc2ccc3nc1c4ccccc4(ccc1c(c3(c2))C),Training,1,1,102,0.4131308035745678,33.120000000000005,87.41480000000003,2.208101137721788,988.6829352406405,273.33500000000004,4.341920000000003
+1742,1744,160543-04-4,OCc2ccc3nc1c4ccccc4(ccc1c(c3(c2))CO),Training,1,1,108,0.43829098022353485,53.35000000000001,88.60060000000003,2.2158534480730188,1008.18286766976,289.33400000000006,3.5258000000000025
+1743,1745,160543-06-6,OCc2c4ccc(cc4(nc1c3ccccc3(ccc12)))C,Training,0,1,102,0.4131308035745678,33.120000000000005,87.41480000000004,2.2801636107335446,988.6829352406405,273.33500000000004,4.341920000000003
+1744,1746,160543-08-8,OCc4ccc2c(nc1c3ccccc3(ccc1c2C))c4,Training,1,0,102,0.4131308035745678,33.120000000000005,87.41480000000003,2.2198825806250464,988.6829352406405,273.33500000000004,4.341920000000003
+1745,1747,160543-10-2,OCc4ccc2c(nc1c3ccccc3(ccc1c2CO))c4,Training,0,1,108,0.43829098022353485,53.35000000000001,88.60060000000003,2.2231246505174767,1008.18286766976,289.33400000000006,3.525800000000002
+1746,1748,160543-14-6,OCc3ccc4nc2c(ccc1c2(C=CC(O)C1(O)))c(c4(c3))C,Training,1,1,116,0.6042414922538245,73.58000000000001,89.9094,2.086001561767048,961.8841920375567,307.3490000000001,2.609820000000001
+1747,1749,160543-15-7,OCc3c4ccc1c(C=CC(O)C1(O))c4(nc2ccc(cc23)C),Training,1,1,116,0.6042414922538245,73.58,89.90940000000002,2.1419062615804347,961.8841920375567,307.34900000000005,2.60982
+1748,1750,160543-16-8,OC3c4ccccc4(c2nc1ccc(cc1c(c2C3(O))C)C),Training,0,0,110,0.6651473632315603,53.35000000000001,86.57260000000002,2.137082242463004,901.320926263548,291.35,3.5990400000000022
+1749,1751,160543-18-0,OCc3ccc4nc2c1ccccc1C5OC5(c2c(c4(c3))C),Training,0,0,108,0.6924864339256883,45.650000000000006,84.40580000000003,1.8730973293225754,932.1116558130176,289.33400000000006,3.828520000000003
+1750,1752,160543-23-7,OC3c4ccccc4(c2nc1cc(ccc1c(c2C3(O))C)C),Training,0,0,110,0.6651473632315603,53.35000000000001,86.57260000000002,2.139436402431601,901.320926263548,291.35,3.5990400000000022
+1751,1753,160637-28-5,OC3C=Cc2c4nc1ccc(cc1c(c4(ccc2C3(O)))C)C,Training,1,1,110,0.6239357879457406,53.35000000000001,88.72360000000003,2.131521968068291,943.2117178462031,291.35,3.4259400000000024
+1752,1754,160637-29-6,OC4c2c(nc1c3ccccc3(ccc1c2C))C=C(C)C4(O),Training,1,1,110,0.6231995625360164,53.35000000000001,88.60360000000003,2.159242290211517,942.9666053483664,291.35,3.5076200000000033
+1753,1755,160637-30-9,OC3C=Cc2c4nc1cc(ccc1c(c4(ccc2C3(O)))C)C,Training,1,1,110,0.6239357879457406,53.35000000000001,88.72360000000003,2.139452106605537,943.2117178462031,291.35,3.4259400000000024
+1754,1756,1606-67-3,Nc1ccc2ccc3cccc4ccc1c2c34,Training,1,1,80,0.3470341741319264,26.02,74.55840000000003,2.483254905410699,829.9816720069383,217.271,4.166200000000002
+1755,1757,16069-36-6,O1CCOC3CCCCC3(OCCOCCOC2CCCCC2(OCC1)),Training,0,0,152,0.6516863882048354,55.38000000000001,97.53400000000008,1.4379965511800195,300.21056897461733,372.5020000000002,2.7220000000000004
+1756,1758,1608-51-1,O=C(C=Cc1ccc(F)cc1)c2ccccc2,Training,0,0,84,0.575467204449596,17.07,66.20650000000003,2.1119604930862836,526.6080948683215,226.25000000000003,3.7218000000000027
+1757,1759,1609-47-8,O=C(OC(=O)OCC)OCC,Training,0,0,64,0.45221324802487844,61.83000000000001,35.129,3.4899621428296506,125.90806892875807,162.14099999999996,1.316
+1758,1760,1609-93-4,O=C(O)C=CCl,Training,1,0,34,0.5028445247419783,37.3,22.6288,3.3016278719934826,76.86238311218402,106.50800000000001,0.8235000000000001
+1759,1761,16110-09-1,n1cc(ccc1Cl)Cl,Training,0,0,42,0.5143628381850539,12.89,34.257000000000005,3.032455532033676,149.2884734445621,147.99200000000002,2.3884000000000007
+1760,1762,161221-84-7,O=C(Oc3ccc(OC(=O)C)c4c(OC)c(c1cc(OC(=O)C)c2c(OC)cc(cc2(c1(OC(=O)C)))C)c(cc34)C)C,Training,0,0,218,0.19185975182194512,123.66,154.7039999999997,2.2555622808158526,1784.6735333596744,574.5820000000002,5.995240000000005
+1761,1763,1613-37-2,[O-][n+]2cccc1ccccc12,Training,0,0,54,0.4070923401956498,26.939999999999998,42.908000000000015,2.9131611636048604,378.7244463345712,145.16099999999997,1.4732
+1762,1764,1615-02-7,O=C(O)C=Cc1ccc(cc1)Cl,Training,0,0,62,0.7137541339827018,37.3,48.121800000000015,2.7720256132280023,300.8095034459553,182.606,2.437800000000001
+1763,1765,16156-53-9,O=S(=O)(OCC(C)C)C,Training,1,1,56,0.5566476474471487,43.370000000000005,35.633799999999994,3.5343515152249494,157.04192083187502,152.21499999999997,0.6186
+1764,1766,16156-54-0,O=S(=O)(OC(C)CC)C,Training,1,1,56,0.5606657241997783,43.370000000000005,35.681799999999996,3.7515016690303664,159.04192083187502,152.21499999999997,0.7611
+1765,1767,16156-55-1,O=S(=O)(OCCC(C)C)C,Training,1,1,62,0.585281273436688,43.370000000000005,40.250800000000005,3.3927730832999727,169.43195019909115,166.242,1.0087000000000002
+1766,1768,16169-16-7,O=[N+]([O-])c1ccc(cc1)NO,Training,1,1,58,0.498218848841358,75.4,38.50560000000001,2.9138015626758045,257.0348350774007,154.12499999999997,1.3958999999999997
+1767,1769,16169-17-8,ONc2ccccc2(c1ccccc1),Training,1,1,70,0.7042156722210636,32.26,57.28720000000002,2.513020981657148,411.67672290326936,185.226,3.154700000000001
+1768,1770,161696-98-6,n1ccnc2c1ccc(NC)c2C,Training,1,1,66,0.7161242605173158,37.81,53.82170000000002,2.78910696684952,437.11794596887324,173.21899999999997,1.97992
+1769,1771,161696-99-7,n1cc(nc2ccc(NC)c(c12)C)C,Training,1,1,72,0.7439142133180788,37.81,58.55870000000003,2.7706662315779114,477.1614928905081,187.24599999999995,2.2883400000000007
+1770,1772,161697-00-3,n1c2ccc(NC)c(c2(nc(c1C)C))C,Training,1,1,78,0.7702533877643923,37.81,63.295700000000025,2.812817380093522,517.7464256036562,201.27299999999997,2.5967600000000006
+1771,1773,161697-01-4,n1c2ccc(NC)c(c2(nc(c1CC)CC))C,Training,1,1,90,0.8784283994038832,37.81,72.57770000000004,2.739293912164263,546.6488864201382,229.32699999999994,3.1047200000000013
+1772,1774,161697-02-5,n1cc(nc2c1ccc(NC)c2C)c3ccccc3,Training,1,1,94,0.7530109962456326,37.81,79.25770000000003,2.2226142989396362,720.6456093291966,249.31699999999998,3.6469200000000015
+1773,1775,161697-03-6,n1c2ccc(N)c(c2(nc(c1C)C))C,Training,1,1,72,0.6426887289151259,51.8,58.161400000000015,2.8946303513006795,503.34907034081004,187.246,2.1372600000000004
+1774,1776,161697-04-7,n1c2ccc(c(c2(nc(c1C)C))C)N(C)C,Training,1,1,84,0.7319071340291001,29.020000000000003,68.07600000000004,2.787410596267332,544.3592706918546,215.29999999999998,2.621060000000001
+1775,1777,161708-24-3,O=C(O)C(=C(C(=O)O)Cl)C,Training,0,1,56,0.5885338308674268,74.6,33.8246,4.674344436799367,183.6934904530594,164.54399999999998,0.6684000000000001
+1776,1778,162022-85-7,[O-][n+]1ncc2cnccc2(c1),Training,0,0,54,0.3965176479850006,52.72,38.49800000000001,2.8289012156206956,388.09739939098534,147.137,0.2631999999999999
+1777,1779,162022-88-0,n1nc(NN)c2ccncc2(c1),Training,1,1,60,0.4646516791648335,76.72,45.14310000000001,2.7909670297392637,394.4237978552908,161.168,0.3103999999999997
+1778,1780,162022-89-1,n1nc(NN)c2cnccc2(c1),Training,1,1,60,0.4646516791648335,76.72,45.14310000000001,2.7909670297392637,394.4237978552908,161.168,0.3103999999999997
+1779,1781,162022-90-4,n1nc(OC)c2ccncc2(c1),Training,0,0,60,0.626400015282235,47.900000000000006,43.885000000000026,2.7909670297392637,396.9300352819674,161.164,1.0333999999999999
+1780,1782,162022-91-5,n1nc(OC)c2cnccc2(c1),Training,0,0,60,0.626400015282235,47.900000000000006,43.885000000000026,2.7909670297392637,396.9300352819674,161.164,1.0333999999999999
+1781,1783,162022-92-6,n1nc(c2ccncc2(c1))Cl,Training,0,0,54,0.5963278359800787,38.67,42.34300000000001,2.913161163604861,382.84739939098546,165.583,1.6782
+1782,1784,162022-93-7,n1nc(c2cnccc2(c1))Cl,Training,0,0,54,0.5963278359800787,38.67,42.34300000000001,2.913161163604861,382.84739939098546,165.583,1.6782
+1783,1785,162050-09-1,O=C(c1oc(c(c1Cl)Cl)[N+](=O)[O-])CBr,Training,1,1,76,0.37210350547754245,73.35,53.506899999999995,3.2836236141124058,402.7809221650789,302.895,3.0722000000000005
+1784,1786,162050-11-5,O=C(OC)C1OC(=NO)C(=C1Cl)Cl,Training,0,1,72,0.41159297569998116,68.12,44.84250000000001,2.9255109905913605,299.0093770680184,226.015,1.0351
+1785,1787,16219-75-3,C(=C1CC2C=CC1C2)C,Training,0,0,48,0.43080727720378237,0.0,39.111000000000004,2.2890296293112073,174.47733175670794,120.19499999999998,2.5287000000000006
+1786,1788,16219-98-0,O=NN(c1ncccc1)C,Training,1,0,52,0.45411732387694603,45.56,38.43500000000002,2.8420150159808886,211.49273048806666,137.14199999999997,1.1992
+1787,1789,16219-99-1,O=NN(c1ccncc1)C,Training,0,0,52,0.45411732387694603,45.56,38.435000000000024,2.8420150159808886,211.49273048806666,137.14199999999997,1.1992
+1788,1790,1622-57-7,n1c(N)n(c2ccccc12)C,Training,1,1,56,0.6071902214685283,43.839999999999996,45.12640000000001,2.9241656172402415,389.1365426998833,147.18099999999995,1.1555
+1789,1791,1622-62-4,O=C1N(c3ccc(cc3(C(=NC1)c2ccccc2(F)))[N+](=O)[O-])C,Training,1,0,116,0.6313255490777444,75.81,83.41240000000003,2.273997256650807,848.2141468702094,313.288,2.5477000000000007
+1790,1792,16238-56-5,c1ccc2c(c1)ccc4c2c(c3ccccc3c4CBr)C,Training,1,1,102,0.2159521785653936,0.0,96.32800000000005,2.365308952713891,982.9549960983214,335.24399999999997,6.3495200000000045
+1791,1793,16239-84-2,O=[N+]([O-])c2oc(C=Cc1nc(N)sc1)cc2,Training,1,1,82,0.6527499148925086,95.19,60.816800000000015,2.139737291745449,543.6965322803351,237.23999999999998,2.3969000000000005
+1792,1794,16292-86-7,O=[N+]([O-])c1ccc(N)cc1(O),Training,1,0,58,0.3566686028760262,89.39,39.17360000000001,3.1960696621259195,297.87891172429886,154.125,0.8825999999999998
+1793,1795,1629-58-9,O=C(C=C)CC,Training,1,1,34,0.45855122306098733,17.07,25.49499999999999,3.234390866915873,64.33869642763739,84.11800000000001,1.1515
+1794,1796,16301-26-1,[O-][N+](=NCC)CC,Training,0,1,42,0.2908438411971552,38.43,27.137399999999985,3.285979158672653,70.09004635215048,102.137,0.9887
+1795,1797,16306-16-4,O=C2c1ccccc1c4ccc(O)c3cccc2c34,Training,1,1,90,0.5126713395724526,37.3,74.48130000000002,2.281723269387338,847.0050340602953,246.265,3.756800000000002
+1796,1798,16310-69-3,c1ccc5c(c1)c4cc2c(ccc3c2CCCC3)cc4CC5,Training,1,1,108,0.5122288663244727,0.0,93.43400000000004,1.8187738119944765,885.9240534089556,284.40200000000004,5.484200000000004
+1797,1799,16311-38-9,O=[N+]([O-])c1ccc(cc1)c3nc2n(ccs2)c3[N+](=O)[O-],Training,1,1,100,0.5445586905378662,103.58,71.81380000000001,2.178481686660632,820.685826184496,290.26000000000005,2.879200000000001
+1798,1800,16323-43-6,O=C(O)C=Cc1ccc(C=CC(=O)O)cc1,Training,0,0,82,0.7564494741921491,74.6,59.78160000000002,2.7512076917409365,397.59149412625413,218.208,1.8822
+1799,1801,163275-57-8,Fc3cnc1c(ccc2ccccc12)c3,Training,0,1,72,0.5022458708973095,12.89,59.20700000000003,2.5458785187157504,646.1543647116673,197.212,3.5271000000000017
+1800,1802,163275-58-9,Fc1cc3ccccc3(c2ncccc12),Training,1,1,72,0.5022458708973095,12.89,59.20700000000002,2.6384478838128724,646.1543647116673,197.212,3.5271000000000017
+1801,1803,163275-59-0,Fc2cc1cccnc1c3ccccc23,Training,1,1,72,0.5022458708973095,12.89,59.20700000000002,2.6384478838128724,646.1543647116673,197.212,3.5271000000000017
+1802,1804,163275-60-3,Fc1cccc2c3ncccc3(ccc12),Training,1,1,72,0.5022458708973097,12.89,59.20700000000002,2.6048627936520328,646.1543647116673,197.21200000000002,3.5271000000000017
+1803,1805,163275-61-4,Fc2ccc3ccc1cccnc1c3(c2),Training,1,1,72,0.5022458708973095,12.89,59.20700000000003,2.5738335916816117,646.1543647116673,197.212,3.5271000000000017
+1804,1806,163275-62-5,Fc1cnc2c(c1)cc(F)c3ccccc23,Training,0,1,78,0.5212527987391667,12.89,59.165000000000035,2.585789556344243,691.8927302408441,215.20199999999997,3.6662000000000017
+1805,1807,163275-64-7,Fc1ccc(F)c2c3ncccc3(ccc12),Training,1,1,78,0.5212527987391669,12.89,59.16500000000002,2.644748799899826,691.8927302408441,215.20200000000003,3.6662000000000017
+1806,1808,163275-65-8,Fc2cnc3ccc1ccccc1c3(c2),Training,1,1,72,0.5022458708973095,12.89,59.20700000000003,2.5738335916816117,646.1543647116673,197.212,3.5271000000000017
+1807,1809,163275-66-9,Fc3cccc2c3(ccc1ncccc12),Training,1,1,72,0.5022458708973095,12.89,59.20700000000002,2.604862793652033,646.1543647116673,197.212,3.5271000000000017
+1808,1810,163275-67-0,Fc2cccc3ccc1ncccc1c23,Training,1,1,72,0.5022458708973095,12.89,59.20700000000002,2.6381252216599282,646.1543647116673,197.212,3.527100000000001
+1809,1811,163275-68-1,Fc3ccc(F)c2c3(ccc1ncccc12),Training,1,1,78,0.5212527987391669,12.89,59.16500000000002,2.6447487998998254,691.8927302408441,215.20200000000003,3.6662000000000017
+1810,1812,1633-83-6,O=S1(=O)(OCCCC1),Training,1,1,48,0.44433919607615946,43.370000000000005,28.97279999999999,2.583679042459061,146.12223629333104,136.172,0.12660000000000005
+1811,1813,16338-97-9,O=NN(CC=C)CC=C,Training,1,1,50,0.3161387554975435,32.67,37.76200000000001,3.514423957313491,101.62548782626679,126.15899999999999,1.3418
+1812,1814,16339-05-2,O=NN(CCCC)CCCCC,Training,1,1,72,0.32014906919976677,32.67,51.80100000000004,3.324088257132405,106.70165766734148,172.27199999999996,2.9601000000000015
+1813,1815,1634-04-4,O(C)C(C)(C)C,Training,0,0,38,0.4349873803799564,9.23,26.761999999999986,3.168489872670569,33.69332843436965,88.14999999999999,1.4313
+1814,1816,1634-78-2,O=C(OCC)CC(C(=O)OCC)SP(=O)(OC)OC,Training,0,1,112,0.47151029395319255,88.13000000000002,70.88650000000004,4.80781070887242,338.7698692298092,314.29600000000005,2.0054
+1815,1817,16354-50-0,c1ccc2c(c1)ccc4c2c(c3ccccc3c4CC)C,Training,0,0,102,0.29301132178422473,0.0,93.07500000000006,2.365308952713891,977.1548921177147,270.37499999999994,6.017020000000004
+1816,1818,16354-52-2,c1ccc2c(c1)ccc4c2c(c3ccccc3c4CC)CC,Training,0,0,108,0.30037578741162485,0.0,97.71600000000007,2.3647783951509855,992.7859948151676,284.402,6.271000000000004
+1817,1819,16354-55-5,c1ccc2c(c1)ccc4c2c(c3ccccc3c4C)CC,Training,0,0,102,0.29301132178422473,0.0,93.07500000000006,2.3760990396040507,977.1548921177147,270.37499999999994,6.017020000000004
+1818,1820,1635-61-6,O=[N+]([O-])c1ccc(cc1(N))Cl,Training,1,1,58,0.39921483447818135,69.16,42.518800000000006,3.1960696621259204,300.6337992264623,172.57099999999997,1.8303999999999998
+1819,1821,163930-30-1,O(c1ccc(cc1)CCI)Cc2ccccc2,Training,1,1,88,0.5852285928112427,9.23,79.80700000000003,1.9092896327699718,436.2388159244594,338.1880000000001,4.243100000000004
+1820,1822,16400-63-8,C=C(CCl)Br,Training,1,1,30,0.5090586785319414,0.0,28.786999999999992,2.8473789230876716,42.1577218810798,155.422,2.1338
+1821,1823,1640-39-7,N=2c1ccccc1C(C=2C)(C)C,Training,0,1,62,0.551333530469035,12.36,52.23700000000003,2.6561868116567,347.77667463287764,159.23199999999997,3.0702000000000016
+1822,1824,16423-19-1,OC12(CCCCC2(C)(CCCC1(C))),Training,0,0,76,0.6100084709417158,20.23,54.53980000000005,2.2704553092843445,197.30115754722138,182.307,3.1178000000000017
+1823,1825,16430-32-3,O=C(OCc2c3ccccc3(cc1ccccc12))C,Training,1,1,94,0.5062261954373539,26.3,76.92400000000005,2.292867019084717,705.4003682979456,250.297,4.0561000000000025
+1824,1826,16452-01-0,O(c1cc(N)ccc1C)C,Training,1,1,54,0.5963360245749294,35.25,42.143400000000014,3.0906836464581975,232.69924244622516,137.182,1.58582
+1825,1827,1646-75-9,ON=CC(C)(C)SC,Training,0,1,48,0.3522548112410427,32.59,37.87250000000001,3.7141365611929857,90.42945954287094,133.216,1.588
+1826,1828,1649-18-9,O=C(c1ccc(F)cc1)CCCN3CCN(c2ncccc2)CC3,Training,0,0,126,0.7643942127070744,36.440000000000005,92.85450000000004,1.390702895771482,652.0719347946834,327.403,3.0058000000000016
+1827,1829,16495-13-9,O(Cc1ccccc1)CC2OC2,Training,1,1,64,0.6303634020514357,21.759999999999998,45.83800000000003,1.7163704105604403,228.85371218398433,164.20399999999995,1.6019999999999999
+1828,1830,16533-72-5,O=C(O)C1OC1(C(=O)O),Training,0,0,50,0.4665529846368397,87.13000000000001,23.932599999999994,2.415866093766993,144.34093004940024,132.071,-1.077
+1829,1831,165606-93-9,O=C1NC(=O)C(C1=C(Cl)Cl)(Cl)Cl,Training,1,1,66,0.4013860080879981,46.17,46.3187,3.265711215269558,291.8233452707281,248.88,1.5058999999999998
+1830,1832,16561-29-8,O=C(OC34(C(OC(=O)CCCCCCCCCCCCC)C(C)C2(O)(C(C=C(CO)CC1(O)(C(=O)C(=CC12)C))C3C4(C)(C))))C,Training,0,0,248,0.12043867486370408,130.36,167.3193999999997,1.5068193542281838,1154.7782418801366,616.8360000000001,5.752900000000007
+1831,1833,16568-02-8,O=CN(N=CC)C,Training,0,1,40,0.2745873140425011,32.67,27.992999999999988,3.3467484256733293,79.75898006442378,100.12099999999998,0.08029999999999993
+1832,1834,16582-03-9,n1c3cccc(N)c3(nc2cccc(N)c12),Training,1,1,78,0.43881967405074745,77.82,65.86880000000001,2.540731410431414,629.4788965680244,210.24,1.9473999999999998
+1833,1835,16596-38-6,NN(CC(C)C)CC(C)C,Training,1,0,62,0.47805449883993995,29.259999999999998,45.43640000000002,3.337430348629276,69.32677655889417,144.26199999999997,1.4740999999999995
+1834,1836,1663-39-4,O=C(OC(C)(C)C)C=C,Training,0,0,52,0.3950064255853093,26.3,36.041999999999994,3.7363942918127853,119.36806555425065,128.17099999999996,1.5141
+1835,1837,16650-32-1,Fc1ccc(F)c2cccnc12,Training,1,1,60,0.5840485195000186,12.89,41.65900000000002,2.946471324842402,385.2980911891212,165.142,2.513000000000001
+1836,1838,166546-20-9,n1c3cc(ccc3([nH]c1c2ccc(cc2)N(CCCl)CCCl))Cc4nc5cc(ccc5([nH]4))N6CCN(C)CC6,Training,0,1,202,0.22472905456195125,67.08,163.79239999999965,1.1810436469615,1545.197029997921,562.5490000000001,5.732800000000006
+1837,1839,166546-23-2,n1c3cc(ccc3([nH]c1c2ccc(cc2)N(CCCl)CCCl))CCCCCCc4nc5cc(ccc5([nH]4))N6CCN(C)CC6,Training,0,0,232,0.09816183039701276,67.08,186.8623999999995,0.965676007977064,1630.4879887879629,632.684,7.4876000000000085
+1838,1840,1666-13-3,c1ccc(cc1)[Se][Se]c2ccccc2,Training,1,1,70,0.7408835692827885,0.0,63.66000000000003,1.9574758959875322,330.55201670962913,312.13199999999995,0.9608
+1839,1841,16664-45-2,c1ccc3c(c1)ccc2c3(cc(cc2C)C),Training,1,1,78,0.4710734601666233,0.0,70.92800000000004,2.594492341076751,677.9984465766784,206.28799999999995,4.609840000000003
+1840,1842,16665-89-7,O=C(Nc1c(cccc1CC)CC)C,Training,0,1,76,0.7816497022346276,29.1,59.501700000000035,3.1155159773549155,308.8436560484995,191.27399999999994,2.769800000000001
+1841,1843,1668-19-5,O3c1ccccc1C(=CCCN(C)C)c2ccccc2C3,Training,0,0,108,0.8428637069733037,12.47,87.46600000000005,2.065949702723201,608.6208590133427,279.38300000000004,3.9624000000000033
+1842,1844,16683-64-0,c1ccc2cc3c(cc2(c1))cc5cccc4C=Cc3c45,Training,1,1,92,0.31322689934671355,0.0,87.88800000000005,2.079713049463817,1035.8853209972094,252.31599999999997,5.6300000000000034
+1843,1845,1669-70-1,O1CC1(c2ccc(cc2)Cl)C,Training,1,0,58,0.5876330332241791,12.53,44.75600000000002,2.3317889985327622,261.39615155843137,168.62299999999996,2.585400000000001
+1844,1846,16709-86-7,C=C[Si](C)(C)CCl,Training,0,Non Predicted,42,0.4014385889368453,0.0,38.39900000000001,3.575471150366868,68.48040587771368,134.682,2.1980000000000004
+1845,1847,1671-82-5,O=[N+]([O-])c1nccn1C,Training,1,1,48,0.40304106829436803,60.96,29.862399999999997,3.076663439987336,229.4715490331534,127.103,0.3282999999999998
+1846,1848,1672-88-4,O=C2NC(=O)CN2(N=CC=Cc1oc(cc1)[N+](=O)[O-]),Training,1,1,98,0.37207316814244373,118.05000000000001,63.133100000000006,1.9371782533733266,588.4954129043186,264.197,0.7385999999999999
+1847,1849,16757-80-5,c1ccc2c(c1)cc3ccc4cccc5cc(c2c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000004,2.2587069478404374,1132.5000637406122,266.34299999999996,6.045620000000004
+1848,1850,16757-81-6,c1ccc2c(c1)cc3ccc5c4c(ccc2c34)ccc5C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000004,2.2144030670666157,1132.5000637406122,266.34299999999996,6.045620000000004
+1849,1851,16757-82-7,c1ccc2c(c1)cc3ccc4cc(cc5ccc2c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000005,2.1895313526681774,1113.7500637406124,266.34299999999996,6.045620000000004
+1850,1852,16757-83-8,c1ccc2c(c1)cc3cc(c5cccc4ccc2c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000005,2.235132675121897,1132.5000637406122,266.34299999999996,6.045620000000004
+1851,1853,1679-02-3,c4cc3c5ccc2c(ccc1ccc(cc12)C)c5(ccc3c(c4)C),Training,0,1,114,0.27242887688888595,0.0,105.94000000000003,2.0074236188373527,1234.5183177891513,306.408,6.916240000000005
+1852,1854,1679-41-0,O=CC=C(C)Cl,Training,1,1,34,0.3623771436727785,17.07,25.673999999999992,3.405032612931118,71.61727061434749,104.536,1.3279
+1853,1855,168010-55-7,O=C1C=C3N(C(=O)N1)c2cc(F)c(cc2N3C4CC4)c5cc(nc(c5)C)C,Training,1,1,136,0.5940538236714327,72.16,100.71770000000001,1.9181765938062207,1338.4080930677987,364.38000000000017,3.095340000000001
+1854,1856,16804-85-6,c1ccc2c(c1)C=CC3CCCCC23,Training,1,1,72,0.5716577522791368,0.0,60.17500000000004,2.0501543579016777,362.0559891950519,184.28199999999993,3.987200000000003
+1855,1857,16813-36-8,O=NN1C(=O)NC(=O)CC1,Training,1,1,54,0.5074149021673122,78.84,30.656699999999997,2.5920264000885225,190.18683770125463,143.10199999999998,-0.39029999999999987
+1856,1858,16830-15-2,O=C(OC3OC(COC2OC(CO)C(OC1OC(C)C(O)C(O)C1(O))C(O)C2(O))C(O)C(O)C3(O))C68(CCC(C)C(C)C8(C5=CCC4C7(C)(CC(O)C(O)C(C)(CO)C7(CCC4(C)C5(C)CC6)))),Training,0,0,384,0.09710981355480351,315.21,231.49159999999927,0.9845521371069784,1820.7650634107567,959.1329999999994,-1.032799999999984
+1857,1859,1684-40-8,n2c1ccccc1c(N)c3c2CCCC3,Training,1,1,76,0.7064882384087372,38.91,62.797400000000025,2.359119565381604,517.1700342808027,198.26899999999995,2.695800000000001
+1858,1860,1686-14-2,O1C2CC3CC(C12(C))C3(C)(C),Training,0,0,62,0.4847388598069412,12.53,43.27300000000001,1.9803152559514365,216.15777938858872,152.237,2.2099
+1859,1861,1689-71-0,O2C(c1ccccc1)C2c3ccccc3,Training,0,1,74,0.669572877327074,12.53,59.451000000000036,1.8072004154913703,391.9105840848162,196.249,3.499200000000002
+1860,1862,1689-84-5,N#Cc1cc(c(O)c(c1)Br)Br,Training,0,0,56,0.7919221876452162,44.019999999999996,48.2218,3.348369660783097,306.6978379924635,276.91499999999996,2.78888
+1861,1863,1689-89-0,N#Cc1cc(c(O)c(c1)I)[N+](=O)[O-],Training,0,1,66,0.48486303420045346,87.16,52.193200000000004,3.437601005146849,410.9340611652992,290.016,1.7766800000000003
+1862,1864,16974-10-0,O=C(OCCCCCCC=CCCCCCC)C,Training,0,0,106,0.27733813179681116,26.3,77.61700000000006,3.05584878087341,209.1425000045842,254.41399999999993,5.026600000000005
+1863,1865,1698-60-8,O=C1C(=C(N)C=NN1c2ccccc2)Cl,Training,0,0,76,0.7933823099108368,60.910000000000004,59.25640000000001,2.660282009411021,536.1089189358535,221.64700000000005,1.4680999999999997
+1864,1866,17024-17-8,O=[N+]([O-])c2cccc1c3ccccc3(ccc12),Training,1,1,82,0.35644235437100646,43.14,68.10840000000003,2.5240969437060743,734.4562652641641,223.231,3.901200000000002
+1865,1867,17024-18-9,O=[N+]([O-])c3ccc2c(ccc1ccccc12)c3,Training,1,1,82,0.35644235437100646,43.14,68.10840000000003,2.407018933262109,734.4562652641641,223.231,3.901200000000002
+1866,1868,17024-19-0,O=[N+]([O-])c2ccc3ccc1ccccc1c3(c2),Training,1,1,82,0.35644235437100646,43.14,68.10840000000003,2.460462404889629,734.4562652641641,223.231,3.901200000000002
+1867,1869,17026-81-2,O=C(Nc1ccc(OCC)c(N)c1)C,Training,1,1,76,0.7185544979488906,64.35,56.32710000000002,2.8275242311374504,336.8939251082797,194.23399999999998,1.6259
+1868,1870,1703-58-8,O=C(O)CC(C(=O)O)C(C(=O)O)CC(=O)O,Training,1,0,90,0.4528996450560619,149.2,46.757200000000005,4.933499278619152,288.0,234.15999999999997,-0.6626000000000003
+1869,1871,17057-98-6,c1ccc3c(c1)c2cccc(c2C3C)C,Training,1,1,74,0.591273939129921,0.0,64.13200000000003,2.3745569580168677,523.3115615848764,194.27699999999996,4.127220000000002
+1870,1872,1705-85-7,c1ccc3c(c1)ccc4c2ccccc2c(cc34)C,Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.337122735750299,916.7400111490208,242.32099999999997,5.454620000000004
+1871,1873,170660-62-5,O=C1NC(=O)CC1=C(Cl)Cl,Training,1,1,54,0.440572812809232,46.17,36.49870000000001,2.934667918403483,229.80244996317307,179.98999999999998,0.7220999999999997
+1872,1874,170660-63-6,O=C1NC(=O)C(C1=C(Cl)Cl)Cl,Training,1,1,60,0.3705194498131358,46.17,41.5227,3.0801073740999434,256.4531449452373,214.435,0.9393999999999998
+1873,1875,17070-45-0,n2c1ccc(OC)cc1c(NCCCNCCCl)c3ccc(cc23)Cl,Training,1,1,132,0.33947284213338136,46.18,107.50740000000002,1.950397809088363,870.0319874567303,378.3030000000001,4.680400000000003
+1874,1876,1707-31-9,O=CN(O)c1ccc2ccccc2(c1),Training,1,1,70,0.4444707096766036,40.540000000000006,54.277500000000025,2.560015405879581,467.5491143053221,187.198,2.1917999999999997
+1875,1877,17075-03-5,Nc1cc4cccc3ccc2cccc1c2c34,Training,1,1,80,0.3470341741319264,26.02,74.55840000000003,2.504319902447551,845.7316720069384,217.271,4.166200000000002
+1876,1878,1709-39-3,O=S(=O)(c1ccc(N)cc1)N(CC)CC,Training,0,0,84,0.7899749939204441,63.4,60.96120000000003,3.10561710709777,407.5534582564168,228.31699999999995,1.2993000000000001
+1877,1879,1709-52-0,O=S(=O)(NC)c1ccc(N)cc1,Training,0,0,66,0.6469008404232072,72.19,47.09990000000001,3.1423171432689863,355.49769522287335,186.236,0.17689999999999972
+1878,1880,17096-47-8,O=[N+]([O-])OCCN([N+](=O)[O-])C,Training,1,1,64,0.3948744792744353,98.75,32.57079999999999,3.3876453290370208,159.05163237816976,165.10500000000002,-0.6817999999999997
+1879,1881,1711-06-4,O=C(c1cccc(c1)C)Cl,Training,1,1,52,0.5679905040929671,17.07,41.36250000000001,3.069899265759275,255.1894333808838,154.59599999999998,2.3740200000000007
+1880,1882,17135-78-3,c1ccc2cc3cc(ccc3(cc2(c1)))Cl,Training,1,1,72,0.476239910717608,0.0,66.46400000000003,2.4749364421790014,640.9571121386949,212.67899999999997,4.646400000000002
+1881,1883,17172-88-2,O=C(NCc1ccccc1)C(c2ccccc2)Br,Training,0,1,92,0.8614427334910806,29.1,76.39870000000003,1.9259496439299544,498.4167554874706,304.187,3.439000000000002
+1882,1884,17177-50-3,OCC(O)C1OC1,Training,1,0,42,0.42974195446208885,52.99,22.832599999999992,2.1041818259596177,59.95524697820139,104.105,-1.2616
+1883,1885,171866-15-2,O=C1c5ccccc5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(CO)CC4(OC3OC(C)C(O)C(O)C3I)),Training,1,1,192,0.14160799403181185,173.98,131.41779999999997,1.6553456560574673,1261.8864162419259,612.3690000000001,0.8706999999999991
+1884,1886,1719-53-5,CC[Si](CC)(Cl)Cl,Training,0,0,44,0.426668647381062,0.0,38.42200000000001,3.3604351426960575,47.65148445440323,157.11599999999999,2.9460000000000015
+1885,1887,17233-93-1,O=C(O)C(O)(C(O)C)C(C)C,Training,0,0,66,0.5384832913234884,77.76,39.104400000000005,4.671071448855426,142.51956340253025,162.18499999999997,-0.16110000000000047
+1886,1888,172374-57-1,O=C(Nc2ccc(Oc1ccc(cc1)NO)cc2)C,Training,1,1,98,0.736154351262516,70.59,72.67090000000002,2.0352565526846473,549.9086893985597,258.277,3.2384000000000004
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+1984,1987,18463-85-9,N(=Nc1ccc2ncsc2(c1))c3ccc(cc3)N(C)C,Training,1,1,100,0.648680380954643,40.85,84.56500000000004,1.8157608105708805,743.914318733081,282.37200000000007,4.777700000000004
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+1986,1989,18523-47-2,[N-]=[N+]=NCCC(=O)O,Training,1,1,44,0.3342744764756346,86.06000000000002,26.26579999999999,3.179419419547435,124.49022499567306,115.09199999999998,0.7714
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+2000,2003,1874-22-2,O=CC=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,62,0.29490516856594023,73.35,40.460400000000014,2.8367514842711845,325.90229599594517,167.11999999999998,1.3999
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+2049,2052,19202-92-7,O=C1OC2CC(C)C4C=CC(=O)C4(C)(C3OC(O)(C)C1(C)C23),Training,0,0,120,0.6856815843813248,72.83000000000001,76.49880000000003,1.9152618951794138,608.1705550180269,306.35800000000006,1.4428
+2050,2053,19213-09-3,O=C(Nc1ccc(O)cc1)CC(O)C,Training,0,0,76,0.632431419050224,69.56,53.03430000000003,2.5202495599147,305.6480789080516,195.21799999999996,1.1016
+2051,2054,19213-10-6,O=C(Nc1ccc(O)cc1)CC(=O)C,Training,0,0,74,0.5614603254438596,66.4,52.03450000000002,2.5613587849536317,342.88967288700354,193.20199999999994,1.3097999999999999
+2052,2055,19246-18-5,O=C(O)CNC(=O)C(N)CS,Training,1,0,64,0.39185786634080344,92.42,42.47390000000001,3.6043318631730097,161.80651988033324,178.21299999999997,-1.5556999999999992
+2053,2056,192-65-4,c1ccc3c(c1)cc4c2ccccc2c6cccc5ccc3c4c56,Training,1,1,110,0.21154764348306734,0.0,105.15800000000004,2.116314820694877,1388.6592859546317,302.37600000000003,6.890400000000003
+2054,2057,192705-52-5,O=C(Nc2c(O)cc4c1ccccc1c3cccc2c34)C,Training,1,1,102,0.5125776152518006,49.33,84.34650000000002,2.145034046559506,912.4805438722209,275.307,4.151200000000002
+2055,2058,192705-53-6,O=C(Nc2ccc4c1ccc(O)cc1c3cccc2c34)C,Training,1,1,102,0.5479415665131896,49.33,84.34650000000002,2.0841977720572746,912.480543872221,275.307,4.151200000000002
+2056,2059,192705-54-7,O=C(Nc1ccc3c4cc(O)ccc4(c2cccc1c23))C,Training,1,1,102,0.5479415665131896,49.33,84.34650000000002,2.0846396206696824,912.4805438722209,275.307,4.151200000000002
+2057,2060,1928-38-7,O=C(OC)COc1ccc(cc1Cl)Cl,Training,0,0,76,0.7548950599069326,35.53,53.97300000000003,2.6321748000640026,338.828993542009,235.06599999999997,2.5452000000000004
+2058,2061,1928-43-4,O=C(OCC(CC)CCCC)COc1ccc(cc1Cl)Cl,Training,0,0,118,0.5876459192683658,35.53,86.22200000000005,2.3297958463414745,449.14827114518977,333.255,5.131800000000005
+2059,2062,192-87-0,c1ccc5c(c1)ccc4ccc3c(c2ccccc2C3)c45,Training,0,1,98,0.3216223323659576,0.0,89.69600000000004,2.0406009745126235,1008.7771398986744,266.34299999999996,5.564200000000003
+2060,2063,192-97-2,c1ccc2c(c1)c5cccc4ccc3cccc2c3c45,Training,1,1,92,0.24345418372476169,0.0,87.65200000000004,2.3291505869732854,998.0049697160237,252.31599999999997,5.737200000000003
+2061,2064,1929-73-3,O=C(OCCOCCCC)COc1ccc(cc1Cl)Cl,Training,0,0,112,0.5134003431318568,44.760000000000005,78.64300000000004,2.162571399235717,423.63497228146275,321.19999999999993,3.7321000000000026
+2062,2065,1929-82-4,n1c(cccc1Cl)C(Cl)(Cl)Cl,Training,1,0,60,0.49082420476347627,12.89,48.48400000000001,3.059901692217984,255.00435022836655,230.909,3.5617
+2063,2066,19315-64-1,O=C(N(O)c1ccc(OCC)cc1)C,Training,1,1,76,0.5909074223723212,49.77000000000001,52.557500000000026,2.7715870204276314,307.64807890805156,195.21799999999996,1.8274
+2064,2067,19322-27-1,O=C1C(O)=C(OC1)C,Training,1,1,44,0.4946813128952599,46.53,26.287799999999994,2.864887658615284,157.05671753425597,114.1,0.3751999999999999
+2065,2068,19331-27-2,O=[N+]([O-])c1ccc2c(nsc2(c1))Cl,Training,1,1,66,0.5418468066415272,56.03,51.28440000000002,2.697231972696502,482.29731987688285,214.63299999999998,2.8579
+2066,2069,19337-19-0,O=C(C=Cc1ccccc1)c2ccc(cc2)NC(=O)C,Training,0,1,100,0.6785469933882977,46.17,80.55220000000004,2.0588451398560363,627.799396989072,265.312,3.541100000000002
+2067,2070,193-39-5,c1ccc2c(c1)c3ccc4ccc5cccc6cc2c3c4c56,Training,1,1,100,0.2883347622336107,0.0,94.57600000000004,2.0282017866463833,1211.2161722814699,276.338,6.2314000000000025
+2068,2071,193-40-8,n2c1ccccc1c4c6ccccc6(nc3c5ccccc5(c2c34)),Training,0,1,110,0.3421132641642169,25.78,98.98,2.0194153843848723,1204.4270102207227,304.3520000000001,5.583600000000003
+2069,2072,1934-20-9,O=S(=O)(O)c3ccc2c(ccc(O)c2(N=Nc1ccccc1))c3,Training,0,0,116,0.5554519797011201,99.32000000000001,86.04540000000001,2.129239660252922,999.2689010836856,328.349,4.207500000000002
+2070,2073,193-54-4,c1ccc2c(c1)c3ccc4C=Cc5ccc2c3c45,Training,1,1,82,0.349443574942703,0.0,77.30600000000004,2.1108796813308497,798.8358603865695,226.27799999999996,4.971000000000003
+2071,2074,19387-91-8,O=[N+]([O-])c1cnc(n1CCS(=O)(=O)CC)C,Training,1,1,90,0.5584635043283492,95.1,57.946200000000026,2.891985103589126,491.38174284533943,247.27599999999998,0.5344199999999997
+2072,2075,193-98-6,n1cc2ccc3cccc4ccc(c1)c2c34,Training,1,1,74,0.3938070724969092,12.89,67.94100000000003,2.5059556893606714,672.0164468827516,203.24399999999997,3.979000000000002
+2073,2076,194-03-6,n1cc3cccc4ccc2cccc1c2c34,Training,1,1,74,0.3938070724969092,12.89,67.94100000000003,2.505955689360671,672.0164468827516,203.24399999999997,3.979000000000001
+2074,2077,19406-51-0,O=[N+]([O-])c1cc(N)cc(c1C)[N+](=O)[O-],Training,1,1,74,0.4369034196011298,112.30000000000001,48.9002,3.472584005406869,380.39108874259836,197.14999999999998,1.3936199999999999
+2075,2078,19408-84-5,O=C(NCc1ccc(O)c(OC)c1)CCCCCCC(C)C,Training,1,1,124,0.6419992796126904,58.56,89.04550000000006,2.1770480308131175,457.6455324520555,307.43399999999997,4.013600000000003
+2076,2079,1943-79-9,O=C(Oc1ccccc1)NC,Training,0,1,58,0.6584875447006161,38.33,41.52570000000002,2.57930229200732,233.10719092921434,151.16499999999996,1.4047999999999998
+2077,2080,194479-75-9,n2c1ccc(cc1c(N)c3cc(ccc23)C)C,Training,1,1,84,0.5902590373261304,38.91,73.13540000000002,2.5297215862635376,669.646100234516,222.291,3.587040000000002
+2078,2081,194479-79-3,n2c1ccccc1c(N)c3cc(ccc23)I,Training,1,1,78,0.5079045761813207,38.91,76.37840000000001,2.5581440319024598,691.8927302408441,320.13300000000004,3.5748000000000015
+2079,2082,194590-84-6,O=C(Nc1cc(c(OC)cc1n2nc3c(n2)c(c(N)cc3Br)Cl)N(CCOC)CCOC)C,Training,1,1,178,0.37479878134945654,116.75999999999999,132.80809999999997,2.1914260312611398,1147.7206822940925,541.8340000000002,3.4848000000000026
+2080,2083,194-59-2,c1ccc5c(c1)ccc4[nH]c3ccc2ccccc2c3c45,Training,1,1,98,0.37416487112894065,15.79,90.81670000000005,2.1783019491015683,1041.9691570759296,267.331,5.627500000000003
+2081,2084,194-69-4,c1ccc5c(c1)ccc4c5(ccc3ccc2ccccc2c34),Training,1,1,102,0.29152582766624097,0.0,96.46600000000005,2.1127406018506547,1166.047817212129,278.35400000000004,6.299400000000004
+2082,2085,1947-37-1,O=C(O)CC(NC(=O)C(NC(=O)C(N)Cc2c[nH]c1ccccc12)CCSC)C(=O)NC(C(=O)N)Cc3ccccc3,Training,0,0,224,0.12310572781023532,209.5,160.3623999999998,1.6871613171189819,1397.527169003911,596.7100000000003,0.44790000000000446
+2083,2086,1948-33-0,Oc1ccc(O)c(c1)C(C)(C)C,Training,0,0,66,0.5808370712927261,40.46,48.47160000000004,3.231425013090014,284.3803204812324,166.21999999999997,2.3953000000000007
+2084,2087,1951-56-0,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NC(C)C,Training,1,1,86,0.4790404569406764,85.38,57.67510000000003,2.619814138754851,420.2084494332861,224.21599999999998,1.7255999999999998
+2085,2088,195-27-7,n3cc2cnc1ccccc1c2c4ccccc34,Training,0,1,84,0.4275381218352279,25.78,74.55000000000004,2.3809343150199185,810.811272164364,230.26999999999998,3.936200000000002
+2086,2089,1953-54-4,Oc1ccc2[nH]ccc2(c1),Training,0,0,50,0.5650833236885094,36.019999999999996,39.96350000000001,2.860781632079713,350.78507788066474,133.15,1.8735
+2087,2090,1955-45-9,O=C1OCC1(C)C,Training,1,0,40,0.41582799710368235,26.3,24.739999999999988,2.5901968417537016,104.64778179757933,100.11699999999999,0.5694
+2088,2091,19622-55-0,O=[N+]([O-])c2cnc(c1nnc(N)s1)n2C,Training,1,1,78,0.5863697225936367,112.75999999999999,53.1778,2.504366834186225,517.4243585933915,226.221,0.4289999999999998
+2089,2092,19655-56-2,n1cccc2cccc(c12)CC,Training,1,1,60,0.6199049022830792,12.89,51.12100000000002,2.7909670297392646,387.63117497912054,157.21599999999995,2.797200000000001
+2090,2093,196-77-0,c1cc2ccc3c6cccc5C=Cc(c4ccc(c1)c2c34)c56,Training,1,1,100,0.22802202618184747,0.0,96.58000000000004,2.094444481842587,1239.6703568882176,276.338,6.221000000000002
+2091,2094,19727-83-4,O=[N+]([O-])c1ccc2c(c1)NCC2,Training,1,1,62,0.5058502246136939,55.17,45.29010000000002,2.4508870366286897,335.82978715700074,164.16399999999996,1.5627999999999997
+2092,2095,1975-50-4,O=C(O)c1cccc(c1C)[N+](=O)[O-],Training,1,1,68,0.5545811672294876,80.44,44.79270000000001,3.3454419708109935,340.1568180287228,181.14699999999996,1.6014199999999998
+2093,2096,1975-52-6,O=C(O)c1cc(ccc1C)[N+](=O)[O-],Training,1,1,68,0.5545811672294876,80.44,44.79270000000001,3.267052212361692,372.4068180287228,181.14699999999996,1.60142
+2094,2097,19770-52-6,c1ccc3c(c1)cc4cc2ccccc2c5C=Cc3c45,Training,1,1,92,0.31322689934671355,0.0,87.88800000000005,2.1352986168844064,955.3853209972095,252.31599999999997,5.630000000000003
+2095,2098,19785-01-4,O(c1ccc(OC)c(C=CC)c1)C,Training,0,1,70,0.7081315785375943,18.46,54.25400000000003,3.0943748708609697,302.9586304882723,178.231,2.736900000000001
+2096,2099,1982-49-6,O=C(Nc1ccccc1)NC2CCCCC2(C),Training,0,0,92,0.8059405879765424,41.13,70.01640000000003,1.8444317603693572,363.74477608966475,232.3269999999999,3.3868000000000027
+2097,2100,1982-67-8,O=C(O)C(N)CCS(=O)(=N)C,Training,0,0,66,0.540267928382085,104.23999999999998,41.88130000000001,3.8174336696123663,234.11208517174683,180.229,-0.5350299999999997
+2098,2101,198-55-0,c1cc2cccc3c5cccc4cccc(c(c1)c23)c45,Training,1,1,92,0.24345418372476169,0.0,87.65200000000003,2.3176108221779406,917.0049697160238,252.31599999999997,5.737200000000003
+2099,2102,1985-51-9,O=C(OCC(C)(C)COC(=O)C(=C)C)C(=C)C,Training,0,0,96,0.5275523225154576,52.6,65.32700000000003,4.12140084250294,307.3286251704447,240.29899999999995,2.2512000000000008
+2100,2103,19866-61-6,[O-][n+]1ncc2ncccc2(c1),Training,0,0,54,0.3965176479850006,52.72,38.49800000000001,2.8289012156206956,388.09739939098534,147.137,0.2631999999999999
+2101,2104,19866-62-7,[O-][n+]1ncc2cccnc2(c1),Training,0,0,54,0.3965176479850006,52.72,38.49800000000001,2.8289012156206956,388.09739939098534,147.137,0.2631999999999999
+2102,2105,19881-18-6,O=[N+]([O-])c2ccc(Oc1ccc(N=C=S)cc1)cc2,Training,1,1,94,0.36321365959804375,64.73,74.29840000000002,2.1172018650580715,588.4428348078474,272.285,4.121400000000002
+2103,2106,19900-72-2,Nc1c(cc(cc1CC)Cc2cc(c(N)c(c2)CC)C)C,Training,0,1,112,0.8263582975094789,52.04,92.74480000000004,2.3842999163067713,599.6013090046888,282.431,4.183440000000003
+2104,2107,19952-47-7,n1c(N)sc2cccc(c12)Cl,Training,0,0,56,0.683602031328969,38.91,49.04240000000001,2.9003583079088235,396.23994574764356,184.65099999999998,2.5319000000000003
+2105,2108,199536-62-4,O=C1OCC(=C1Br)CBr,Training,1,1,50,0.5255623244824459,26.3,40.706,2.794946974007874,173.79680833403853,255.89299999999997,1.5871000000000002
+2106,2109,199536-64-6,O=C1OC(O)C(=C1Br)CBr,Training,1,1,56,0.5696103604986429,46.53,41.84580000000001,2.898471208485737,199.06974419231443,271.89199999999994,0.9055
+2107,2110,199536-65-7,O=C1OCC(=C1Cl)CBr,Training,1,1,50,0.48443957982576674,26.3,37.632000000000005,2.794946974007874,175.79680833403853,211.44199999999998,1.431
+2108,2111,199536-79-3,O=C1OCC(=C1Br)C(Br)Br,Training,1,1,56,0.5431779628509422,26.3,48.554,2.849348666115631,197.06974419231443,334.789,2.3081000000000005
+2109,2112,199536-82-8,O=C1OCC(=C1Cl)C(Br)Br,Training,1,1,56,0.5462416584843613,26.3,45.480000000000004,2.849348666115631,199.8246316944779,290.33799999999997,2.152
+2110,2113,199536-84-0,O=C1OCC(=C1Br)CCl,Training,1,1,50,0.48443957982576674,26.3,37.632000000000005,2.794946974007874,175.79680833403853,211.44199999999998,1.431
+2111,2114,19996-03-3,c1ccc3c(c1)c(c2ccccc2c3Cl)CCl,Training,1,1,84,0.4069065715974885,0.0,76.02100000000003,2.631771409903851,644.6757073698407,261.15099999999995,5.385200000000003
+2112,2115,20020-02-4,c1ccc2c(c1)c(c(c(c2Cl)Cl)Cl)Cl,Training,0,0,72,0.43872473802518025,0.0,63.98800000000002,3.021805296135276,458.43842469911027,265.95399999999995,5.4534
+2113,2116,20098-48-0,O=[N+]([O-])c1cc(c(c(c1)Cl)Cl)Cl,Training,1,1,64,0.4173619816787872,43.14,48.12640000000001,3.306535412749064,316.56023714834686,226.44599999999997,3.5549999999999997
+2114,2117,201-06-9,c1ccc2c(c1)cc4C=Cc3cccc2c34,Training,1,1,74,0.3687663697638187,0.0,70.38200000000003,2.3878085779888325,748.42172634161,202.25599999999997,4.4768000000000026
+2115,2118,2016-88-8,O=C(NC(=N)N)c1nc(c(nc1(N))N)Cl,Training,1,1,80,0.3043612043102547,156.79000000000002,55.24709999999998,3.092244563998155,431.73374089048275,229.631,-1.0823300000000007
+2116,2119,202-03-9,c1ccc2c(c1)cc4cccc3C=Cc2c34,Training,1,1,74,0.3687663697638187,0.0,70.38200000000003,2.3774583390109925,748.42172634161,202.25599999999997,4.476800000000002
+2117,2120,202-33-5,c1ccc2c(c1)ccc3c5C=Cc4cccc(cc23)c45,Training,1,1,92,0.2473325144876158,0.0,87.88800000000003,2.1297181588747494,1035.8853209972094,252.31599999999997,5.6300000000000034
+2118,2121,20268-51-3,O=[N+]([O-])c2c4ccccc4(cc1c3ccccc3(ccc12)),Training,0,1,100,0.2105485705949235,43.14,85.61440000000003,2.3299530750328077,1021.3866090742639,273.291,5.054400000000003
+2119,2122,20268-52-4,c1ccc4c(c1)ccc3c4(cc2ccccc2c3Cl),Training,1,1,90,0.277479611353171,0.0,83.97000000000003,2.318193083302064,922.3919838784873,262.739,5.799600000000003
+2120,2123,202-98-2,c1ccc5c(c1)cc4c3c5(ccc2cccc(c23)C4),Training,1,1,88,0.3321636886566955,0.0,81.76600000000003,2.166087978042771,976.4048921177148,240.30499999999998,5.050400000000003
+2121,2124,2031-67-6,O(CC)[Si](OCC)(OCC)C,Training,0,0,68,0.5789819165403256,27.69,46.49600000000002,3.790229816165348,80.66692585709745,178.30399999999997,1.6645999999999999
+2122,2125,20324-66-7,O=C1c3cc(cc(O)c3(C(=O)c2c(O)cc(O)c(O)c12))C,Training,1,1,106,0.368318365359742,115.06,71.1452,2.442310345762376,834.7879788164705,286.23900000000003,1.5928200000000006
+2123,2126,203-33-8,c1ccc3c(c1)cc4cccc5c2ccccc2c3c45,Training,1,1,92,0.3127510250214632,0.0,85.88400000000003,2.15215289471365,993.1157323868963,252.31599999999997,5.640400000000003
+2124,2127,203-64-5,c3cc2ccc1cccc4c1c2c(c3)C4,Training,1,1,70,0.3688296991172455,0.0,64.26000000000002,2.421956391580529,632.0421980027127,190.24499999999995,3.8972000000000016
+2125,2128,2039-87-4,C=Cc1ccccc1Cl,Training,0,0,46,0.5598684314828484,0.0,41.54300000000002,3.1479791300397526,215.56254955650078,138.59699999999998,2.9830000000000014
+2126,2129,20426-12-4,O=C(C=Cc1ccc(O)cc1)c2ccccc2,Training,0,0,84,0.6412736177915347,37.3,67.91330000000004,2.1119604930862836,524.6080948683215,224.25900000000001,3.2883000000000013
+2127,2130,2045-52-5,c1ccc(cc1)N(Cc2ccccc2)CCN(C)C,Training,0,0,100,0.7804840569145676,6.48,82.48800000000006,2.1023390727063194,465.13544259070454,254.37699999999998,3.2548000000000012
+2128,2131,20480-67-5,c1ccc2c(c1)CCC3CCCCC23,Training,0,1,74,0.5760444164000271,0.0,59.46200000000004,1.989291732760524,326.56512465051037,186.29799999999994,3.9066000000000027
+2129,2132,20496-16-6,c1ccc4c(c1)c2cccc3c2c4(ccc3CC),Training,0,1,86,0.4290052419457253,0.0,77.75600000000004,2.2345018001350607,736.8403635880815,230.30999999999995,5.0496000000000025
+2130,2133,2050-92-2,N(CCCCC)CCCCC,Training,0,0,68,0.5341051569369422,12.03,51.91970000000004,2.6909155266923976,53.89311688209827,157.301,2.9564000000000012
+2131,2134,20562-02-1,OCC9OC(OC8C(O)C(OC(OC6CC5=CCC4C(CCC3(C)(C4(CC2N1CC(C)CCC1C(C)C23)))C5(C)CC6)C8(OC7OC(C)C(O)C(O)C7(O)))CO)C(O)C(O)C9(O),Training,0,0,348,0.1477317918391238,240.68999999999997,214.91519999999932,0.952037721701933,1589.3986748282048,868.0710000000006,0.1552000000000081
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+2134,2137,20589-63-3,O=[N+]([O-])c3ccc2c5cccc4cccc(c1cccc3(c12))c45,Training,1,1,108,0.17366715134946126,43.14,94.30640000000004,2.210149310223193,1190.1824987418458,297.31300000000005,5.645400000000003
+2135,2138,20589-85-9,C(=C(C(Cl)Cl)Cl)Cl,Training,1,1,42,0.5432826596736214,0.0,35.28300000000001,3.5639645432732485,75.00409256226031,179.86100000000002,3.1091000000000006
+2136,2139,205-99-2,c1ccc3c(c1)cc5c2ccccc2c4cccc3c45,Training,1,1,92,0.3127510250214632,0.0,85.88400000000003,2.120569654932486,993.1157323868965,252.31599999999997,5.640400000000003
+2137,2140,20643-71-4,Oc3ccc2c(nc1occc1c2(OC))c3,Training,0,1,80,0.6776112456478687,55.49000000000001,59.73180000000003,2.5351544264320673,672.3862681270574,215.208,2.6952
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+2144,2147,2082-81-7,O=C(OCCCCOC(=O)C(=C)C)C(=C)C,Training,0,0,90,0.37831521556453657,52.6,60.78000000000003,3.413855766899512,261.39388572785725,226.27199999999996,2.0052000000000003
+2145,2148,20830-81-3,O=C1c5cccc(OC)c5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)C)CC4(OC3OC(C)C(O)C(N)C3)),Training,1,1,202,0.3051291560965149,185.84,130.34259999999998,1.6831341460477502,1358.3575083942706,527.5260000000002,1.0288999999999997
+2146,2149,2085-88-3,O1CC1(c2ccccc2)C,Training,1,1,52,0.5345181865615135,12.53,39.746000000000016,2.350638316663564,223.74339906009686,134.17799999999994,1.932
+2147,2150,20861-99-8,O1CC1c2ccc3ccccc3(c2),Training,1,1,64,0.5993313700470855,12.53,52.64100000000003,2.2050962162358245,443.57368245090146,170.21099999999998,2.911100000000001
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+2149,2152,20927-95-1,O=[N+]([O-])c2ccc3oc1ccccc1c3(c2),Training,1,1,78,0.4588339118278573,56.28,60.37440000000003,2.441228666577131,699.6227880794761,213.192,3.494200000000001
+2150,2153,20930-10-3,O=C(OC(C#CC)(c1ccccc1)c2ccccc2)NC3CCCCC3,Training,1,0,134,0.7894201780378419,38.33,103.60370000000006,1.9377057565774116,728.6051592449444,347.4580000000002,5.012400000000004
+2151,2154,20970-16-5,n1nc(NN)c2cccnc2(c1),Training,1,1,60,0.4646516791648335,76.72,45.14310000000001,2.7909670297392637,394.4237978552908,161.16799999999998,0.3103999999999999
+2152,2155,20983-67-9,O=[N+]([O-])c1ccc(cc1)Nc2ccc(cc2)Cl,Training,1,1,86,0.6599550499960726,55.17,67.83110000000002,2.1337521576418896,523.2068217496917,248.66899999999998,3.9918000000000013
+2153,2156,210245-96-8,OCC3OC(Oc2ccc(N=Nc1ccc(cc1)N(C)C)cc2)C(O)C(O)C3(O),Training,0,0,156,0.5361974682504619,127.34,105.78220000000005,1.6226402090164758,809.9711772621879,403.43500000000006,1.3466999999999996
+2154,2157,2106-54-9,O=C(O)C(F)(F)C(F)(C(F)(F)C(F)(C(F)(F)Cl)Cl)Cl,Training,0,0,114,0.5925347586647163,37.3,47.713800000000006,5.989640448872494,377.17078534845723,363.41499999999996,3.9823999999999993
+2155,2158,2107-76-8,O=C2Oc1cc(O)cc(O)c1C(=C2)C,Training,0,0,72,0.6204810517595596,70.67,50.550600000000024,3.0142112840201314,553.7859331372656,192.16999999999996,1.5126199999999996
+2156,2159,2113-57-7,c1ccc(cc1)c2cccc(c2)Br,Training,0,0,64,0.6945848540367181,0.0,59.578000000000024,2.4751856733635376,392.8790477621569,233.10799999999995,4.116100000000002
+2157,2160,21145-77-7,O=C(c1cc2c(cc1C)C(C)(C)C(C)CC2(C)C)C,Training,0,0,104,0.6616827347493545,17.07,81.01650000000005,2.7546318164475494,534.866419318812,258.4049999999999,4.792620000000005
+2158,2161,211-91-6,c1ccc5c(c1)ccc4cc3cccc2C=Cc(c23)c45,Training,1,1,92,0.2473325144876158,0.0,87.88800000000003,2.1582758133499533,1035.8853209972094,252.31599999999997,5.6300000000000034
+2159,2162,2122-77-2,OCCOc1cc(c(cc1Cl)Cl)Cl,Training,0,0,72,0.8244669791656941,29.46,54.05280000000002,2.8790673645768767,301.68576775728627,241.50099999999998,3.017900000000001
+2160,2163,21229-99-2,ONc1ccc(cc1)Sc2ccccc2,Training,1,1,76,0.7697675616548271,32.26,62.416200000000025,2.1139607477057156,413.39706969850045,217.293,3.6389000000000014
+2161,2164,21232-47-3,[O-][N+](=Nc1ccc(c(c1)Cl)Cl)c2ccc(c(c2)Cl)Cl,Training,0,0,98,0.3640959121283675,38.43,78.29940000000002,2.360725025179113,658.1727973002088,336.005,6.225900000000001
+2162,2165,21247-98-3,OCc4c5ccccc5(c1ccc2cccc3ccc4(c1c23)),Training,1,0,104,0.32954103958388603,20.23,93.57480000000005,2.227932205150175,1138.5980587215813,282.34200000000004,5.229500000000003
+2163,2166,212-54-4,c1ccc5c(c1)ccc4ccc3c2ccccc2Cc3c45,Training,1,1,98,0.3216223323659576,0.0,89.69600000000004,1.9732249212223056,1008.7771398986744,266.34299999999996,5.564200000000003
+2164,2167,21314-05-6,O=[N+]([O-])c1ccc(cc1)n3cnc2c(ncnc23)N,Training,1,1,94,0.5458519677222926,112.75999999999999,67.72680000000001,2.1396099849791006,764.4563880017397,256.22499999999997,1.3058999999999996
+2165,2168,21340-68-1,O=C(OC)C(Oc1ccc(cc1)c2ccc(cc2)Cl)(C)C,Training,0,0,110,0.788353455650856,35.53,83.61100000000005,2.156526880739244,615.4884096326963,304.773,4.337400000000003
+2166,2169,213-46-7,c1ccc5c(c1)ccc3c5(ccc2c4ccccc4(ccc23)),Training,1,1,102,0.2915258276662409,0.0,96.46600000000005,2.0413785020816704,1071.5478172121288,278.354,6.299400000000004
+2167,2170,21362-69-6,O(C)C6(OC2CCC3C4CCC1CC5C(CC1(C)C4(CCC23(C)))S5)(CCCC6),Training,0,0,158,0.3990152978955594,18.46,115.35800000000009,1.2343655169338694,630.0373833068998,404.66000000000025,6.424900000000007
+2168,2171,21388-97-6,O=C(OCc1cccc(c1)[N+](=O)[O-])C,Training,0,0,74,0.4174666573167121,69.44,48.56640000000002,2.732051484694785,361.5845163250598,195.17399999999998,1.6579
+2169,2172,21416-67-1,O=C1NC(=O)CN(C1)CC(N2CC(=O)NC(=O)C2)C,Training,0,1,104,0.5400927830602834,98.82,63.77440000000002,1.907792685909168,404.41112254140677,268.273,-2.708299999999996
+2170,2173,214-17-5,c4ccc5cc2c(ccc1c3ccccc3(ccc12))cc5(c4),Training,0,1,102,0.23019675559525427,0.0,96.46600000000005,2.021674669876966,1160.0478172121288,278.354,6.299400000000004
+2171,2174,21466-07-9,O=P(O)(O)Oc1c(cc(cc1Br)Br)c2cc(cc(c2(O))Br)Br,Training,0,0,118,0.41224414599179465,86.99000000000001,97.0149,2.77139057514304,789.5714627390927,581.7730000000001,5.580700000000003
+2172,2175,2148-31-4,O=C(O)C(NC(=O)C)CSC(=CCl)Cl,Training,1,1,80,0.7853316624151875,66.4,57.48750000000001,4.1062856056834836,257.3194622955766,258.126,1.5854000000000001
+2173,2176,21490-63-1,O1C(C)C1C,Training,1,0,30,0.3853608395723411,12.53,20.008999999999997,2.2034403442173716,36.91260938324327,72.107,0.7936
+2174,2177,2150-55-2,O=C(O)C1N=C(N)SC1,Training,0,0,50,0.5226350030994845,75.67999999999999,35.5042,2.573209706327754,167.9505705238371,146.171,-0.4988999999999997
+2175,2178,215226-70-3,O=CC(=C(C(=O)O)Cl)CCl,Training,1,1,56,0.40300136219752675,54.370000000000005,37.29880000000001,4.5889837618425995,185.33208472898127,182.98999999999998,1.0015999999999998
+2176,2179,215226-71-4,O=CC(=C(C(=O)O)Cl)C,Training,1,1,50,0.46525322351544224,54.370000000000005,32.25279999999999,4.471772749925975,171.041920831875,148.545,0.7827
+2177,2180,215226-73-6,O=C(O)C(=C(CCl)C(Cl)Cl)Cl,Training,1,1,64,0.6054761044210079,37.3,46.728800000000014,4.67962275875625,186.92143908728139,237.89700000000002,2.6064000000000007
+2178,2181,215226-74-7,O=C(O)C(=C(C(=O)O)Cl)CCl,Training,0,1,62,0.5222222522879892,74.6,38.8706,4.831555035985237,220.52230736518902,198.98899999999998,0.8873000000000001
+2179,2182,215245-16-2,N#CCCN(c1cc(NC(=O)C)c(cc1(OC))n2nc3c(n2)c(c(N)cc3Br)Cl)CC,Training,1,1,162,0.4620272316719686,122.08999999999999,124.96010000000004,2.2302084445634036,1188.7106777953807,506.7920000000002,4.125580000000003
+2180,2183,2154-67-8,O=C(O)C1=CC(N(O)C1(C)C)(C)C,Training,0,0,74,0.6452566377929927,60.769999999999996,47.50230000000003,3.170738037385574,278.5844015380891,185.22299999999998,1.2593999999999999
+2181,2184,2154-68-9,O=C(O)C1CC(N(O)C1(C)(C))(C)C,Training,0,0,76,0.6499624260255698,60.769999999999996,47.52630000000002,3.0015785287283747,235.01431330942617,187.239,1.3393
+2182,2185,215-58-7,c2ccc3cc4c5ccccc5(c1ccccc1c4(cc3(c2))),Training,1,1,102,0.23019675559525438,0.0,96.46600000000005,2.174067242281771,1072.2978172121288,278.354,6.299400000000003
+2183,2186,215-62-3,n1c5ccccc5(cc4c1c2ccccc2c3ccccc34),Training,1,1,102,0.2617854022427602,12.89,94.26100000000002,2.1740672422817715,1078.1666469437955,279.34200000000004,5.694400000000004
+2184,2187,2160-93-2,OCCN(CCO)C(C)(C)C,Training,0,0,68,0.6130608388131435,43.7,45.49760000000002,3.875658580581269,92.75540547235174,161.24499999999998,0.07149999999999967
+2185,2188,21626-89-1,O=C3c1ccccc1CN4C(=O)c2ccccc2CN34,Training,0,1,98,0.7316730054881672,40.620000000000005,72.63100000000003,1.8425469838360606,675.2616608169708,264.28399999999993,2.2134
+2186,2189,21638-36-8,O=C2NC(C)CN2(N=Cc1oc(cc1)[N+](=O)[O-]),Training,1,1,90,0.4805068834097903,100.98,57.65610000000001,2.0458585767844966,481.0953332700515,238.203,0.9354
+2187,2190,2164-17-2,O=C(Nc1cccc(c1)C(F)(F)F)N(C)C,Training,0,0,88,0.7928812498481534,32.34,54.14970000000002,2.8751990386596566,387.8956862132586,232.20499999999993,2.7989000000000015
+2188,2191,216-48-8,c1ccc2c(c1)ccc3c5cccc4C=Cc(cc23)c45,Training,1,1,92,0.31322689934671355,0.0,87.88800000000005,2.1350127479593017,1035.8853209972094,252.31599999999997,5.6300000000000034
+2189,2192,21655-84-5,n2ccc1c3ccccc3([nH]c1c2C),Training,1,1,68,0.5684270068624611,28.68,58.33670000000002,2.6327288472456116,607.8208026305191,182.22599999999997,3.0245200000000008
+2190,2193,21711-71-7,O=Nc1ccccc1c2ccccc2,Training,1,1,68,0.6516938030483792,29.43,57.33300000000003,2.5661770737511125,437.08453424031387,183.21,3.7515000000000027
+2191,2194,217-59-4,c1ccc3c(c1)c2ccccc2c4ccccc34,Training,1,1,84,0.36517781288626455,0.0,78.96000000000005,2.463012369730741,651.5360736465454,228.29399999999998,5.146200000000003
+2192,2195,2177-18-6,O=C(OC=C)C=C,Training,0,0,38,0.29064876032105746,26.3,26.48599999999999,3.356711224829561,94.25327665163482,98.101,0.8590999999999999
+2193,2196,21794-55-8,O=C1c4cccc(OC)c4(C(=O)c2c(O)c3c(c(O)c12)CC(O)(C(=O)C)CC3(O)),Training,1,1,150,0.4717127840227535,141.36,98.54220000000002,2.036880416888468,1116.3946715333773,398.3670000000002,1.1814999999999993
+2194,2197,2179-59-1,C=CCSSCCC,Training,0,Non Predicted,48,0.33383900884766726,0.0,45.404000000000025,2.6162930904179853,52.49022499567306,148.296,2.9638000000000018
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+2196,2199,218-02-0,n1ccc2c(c1)ccc3c4ccccc4(ccc23),Training,1,1,84,0.40324929163893447,12.89,76.75500000000004,2.3076388675027784,802.8244038631083,229.28199999999998,4.541200000000003
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+2198,2201,218-08-6,n1cccc2c1ccc3c4ccccc4(ccc23),Training,1,1,84,0.40324929163893447,12.89,76.75500000000004,2.3076388675027784,802.8244038631083,229.282,4.541200000000003
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+2206,2209,22008-60-2,O=CNC(C(=O)NC(C(=O)O)Cc1ccccc1)CCSC,Training,0,0,120,0.5497872328979173,95.50000000000001,85.69920000000005,2.692791112339322,495.57563123062533,324.4020000000001,0.6662000000000008
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+2247,2250,22506-53-2,O=[N+]([O-])c3ccc4c1cccc2c1c(ccc2[N+](=O)[O-])c4(c3),Training,1,1,106,0.4067617049069634,86.28,81.6868,2.121100708572098,994.8475196627456,292.25,4.303600000000002
+2248,2251,225366-91-6,Fc1ccc2ncccc2(c1(F)),Training,1,1,60,0.5840485195000186,12.89,41.659000000000006,2.9077745072579826,425.7980911891212,165.14199999999997,2.513000000000001
+2249,2252,2255-17-6,O=[N+]([O-])c1ccc(OP(=O)(OC)OC)cc1C,Training,1,1,94,0.4596368040107207,87.9,60.085900000000024,2.9896494871249075,466.5539249166925,261.16999999999996,2.682920000000001
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+2251,2254,22603-58-3,O=[N+]([O-])c1cc(c(c(c1(N))[N+](=O)[O-])C)[N+](=O)[O-],Training,1,1,90,0.4749481729674378,155.44000000000003,55.554599999999986,3.756255091963571,501.40572377620146,242.14699999999996,1.30182
+2252,2255,22608-53-3,O=P(OC)(SC)SC,Training,0,0,50,0.610726474842043,26.3,41.64550000000002,3.7910098125875016,86.43699516085105,172.211,2.4669000000000008
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+2286,2289,23246-96-0,O=C1OC3CCN2CC=C(COC(=O)C(O)(C(=C)CC1(=CC))CO)C23,Training,1,1,136,0.3932474725590208,96.3,88.44960000000002,1.9398456987707322,666.4774413288604,349.3830000000001,0.08529999999999976
+2287,2290,23250-39-7,n2c1ccccc1c(N)c3cc(ccc23)Cl,Training,1,1,78,0.597118193447206,38.91,68.67140000000003,2.5581440319024598,691.8927302408441,228.68200000000002,3.6236000000000015
+2288,2291,23282-20-4,O=C3C(=CC4OC2C(O)C(O)C(C)(C12(OC1))C4(CO)(C3(O)))C,Training,0,0,122,0.4188544549066065,119.75000000000001,71.75420000000003,1.9834441692781182,582.4400371025819,312.318,-1.866899999999999
+2289,2292,23355-64-8,O=[N+]([O-])c2cc(c(N=Nc1ccc(cc1Cl)N(CCO)CCO)c(c2)Cl)Cl,Training,1,1,144,0.3539401635817866,111.56,105.12900000000003,2.2874715738823665,834.5492969371484,433.6790000000002,4.761400000000004
+2290,2293,23355-97-7,O2C(c1ccccc1)C2C,Training,0,1,52,0.5359587787679255,12.53,39.73000000000002,2.2038147347065578,217.42969243757128,134.17799999999997,2.1464
+2291,2294,23434-96-0,O=C(OC)C(N)Cc1ccc(cc1)Cl,Training,0,0,76,0.7723460759810249,52.32,55.147400000000026,2.601411312406869,310.402966410215,213.66400000000002,1.3828
+2292,2295,23452-05-3,O=C2Oc1cc(O)cc(c1c3cc(OC)cc(O)c23)C,Training,0,0,102,0.5255869331801049,79.9,74.60860000000002,2.640657095285688,892.2742905385672,272.256,2.6744200000000005
+2293,2296,23511-78-6,C(CBr)C(Br)Br,Training,1,1,38,0.6825510684277248,0.0,40.05300000000001,2.6272148478988635,27.219280948873624,280.78499999999997,2.8873000000000006
+2294,2297,23564-05-8,O=C(OC)NC(Nc1ccccc1(NC(NC(=O)OC)=S))=S,Training,1,0,118,0.6037316575875216,100.72000000000001,89.96480000000001,2.7297769021233163,543.2439175521262,342.40200000000004,1.7922000000000002
+2295,2298,235760-36-8,O=[N+]([O-])c2c1nsnc1c(cc2C)C,Training,1,1,72,0.533015166031674,68.92,53.54340000000001,2.9315925771027724,520.5259032994917,209.23,2.2163399999999998
+2296,2299,235760-37-9,n1c2c(ns1)c(cc(c2(N))C)C,Training,1,1,62,0.6281788005245783,51.8,51.30140000000001,2.968394217607692,433.04074784352395,179.24799999999996,1.89034
+2297,2300,2358-84-1,O=C(OCCOCCOC(=O)C(=C)C)C(=C)C,Training,0,0,96,0.3638810601740942,61.830000000000005,62.36500000000003,3.359569854387089,276.01784906215136,242.27099999999996,1.2416000000000003
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+2301,2304,2363-23-7,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])SC,Training,1,1,74,0.43707348388644557,86.28,51.53180000000002,3.274414445393387,393.2762266208624,214.20199999999997,2.2249
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+2304,2307,23703-14-2,O1CC1Cc2ccc(cc2)c3ccccc3,Training,1,1,80,0.7080598669839787,12.53,65.32200000000003,1.8104235225780867,454.5534417002411,210.276,3.294900000000002
+2305,2308,2371-42-8,OC1(C)(CC2CCC1(C)C2(C)(C)),Training,0,0,70,0.589161276284615,20.23,49.85280000000003,2.4686245462083636,217.0440022382591,168.27999999999997,2.5836000000000006
+2306,2309,2373-51-5,CSCCl,Training,1,1,26,0.4465731001574195,0.0,24.234999999999996,1.9747448713915894,8.0,96.582,1.5457
+2307,2310,2373-98-0,Oc1cc(ccc1(N))c2ccc(N)c(O)c2,Training,1,1,82,0.4326071001734573,92.5,64.03240000000001,2.5020803743746223,489.037124074059,216.24,1.9291999999999996
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+2309,2312,2379-74-0,O=C2c1c(cc(cc1SC2=C4C(=O)c3c(cc(cc3S4)Cl)C)Cl)C,Training,0,1,120,0.506814016864605,34.14,99.779,1.8610157994777297,913.4986610583042,393.3160000000001,6.098840000000004
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+2311,2314,2381-16-0,c1ccc3c(c1)ccc2cc4cc(ccc4(cc23))C,Training,1,1,90,0.2837498834433012,0.0,83.69700000000003,2.2210630674285228,916.7400111490208,242.32099999999997,5.454620000000003
+2312,2315,2381-21-7,c1cc2ccc3ccc(c4ccc(c1)c2c34)C,Training,1,1,80,0.3669189647352123,0.0,74.88300000000004,2.4832549054106994,824.4948037056826,216.28299999999996,4.892420000000003
+2313,2316,2381-31-9,c1ccc4c(c1)ccc3cc2c(cccc2C)cc34,Training,1,1,90,0.2837498834433012,0.0,83.69700000000005,2.2590525379083606,916.7400111490208,242.32099999999997,5.454620000000003
+2314,2317,2381-39-7,c1ccc5c(c1)c2ccc3cccc4ccc(c2c34)c5C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000005,2.25770787410488,1116.7500637406124,266.34299999999996,6.045620000000004
+2315,2318,2381-40-0,n3c1cc(ccc1c(c4ccc2ccccc2c34)C)C,Training,1,1,96,0.3130929426158614,12.89,86.22900000000006,2.2875320562564787,967.2867569201644,257.33599999999996,5.158040000000003
+2316,2319,23815-63-6,O=C(O)C(N)CSc1ccc(cc1[N+](=O)[O-])[N+](=O)[O-],Training,1,1,102,0.4466310892561939,149.60000000000002,66.086,2.9734051071585985,534.6862726607866,287.25300000000004,1.0070000000000001
+2317,2320,23834-30-2,O=NN(C)CCN(C)C,Training,1,1,54,0.40256115142462845,35.910000000000004,36.979,3.158103291759522,84.27229264640108,131.179,0.1612
+2318,2321,2385-85-5,C13(C4(C2(C5(C(C1(C2(Cl)Cl)Cl)(C3(C(C45Cl)(Cl)Cl)Cl)Cl)Cl)Cl)Cl)Cl,Training,0,0,124,0.3172117317076842,0.0,97.54599999999998,2.077829675923021,574.6955361255153,545.5459999999998,6.222999999999999
+2319,2322,2386-87-0,O=C(OCC1CCC2OC2(C1))C3CCC4OC4(C3),Training,1,0,100,0.5660328760907571,51.36,62.96300000000005,1.2253013720397457,355.70315432217836,252.30999999999995,1.6645999999999999
+2320,2323,2386-90-5,O(C1CCC2OC12)C3CCC4OC34,Training,0,1,72,0.593974401527883,34.29,44.45100000000002,1.4108008260107772,218.32435737353333,182.21899999999997,0.8625999999999998
+2321,2324,2390-59-2,c1cc(ccc1C(c2ccc(cc2)N(CC)CC)=C3C=CC(C=C3)=[N+](CC)CC)N(CC)CC,Training,1,0,180,0.36370647913874704,9.49,150.65739999999983,2.084151834410877,963.3608517481711,456.69800000000026,6.800200000000009
+2322,2325,2393-18-2,O=C(O)C=Cc1ccc(N)cc1,Training,0,0,62,0.51083451916994,63.31999999999999,47.524200000000015,2.7720256132280023,300.8095034459553,163.176,1.3666
+2323,2326,239-35-0,c1ccc3c(c1)ccc4c2ccccc2sc34,Training,1,1,80,0.3916722982011528,0.0,76.83700000000005,2.3403062928852925,839.6614055948914,234.32299999999998,5.207700000000003
+2324,2327,2397-76-4,O=C(OCC(C)(C)C)C(=C)C,Training,0,0,64,0.4520597428214086,26.3,45.228000000000016,3.7263874196310534,162.89177158319703,156.22499999999997,2.1517999999999997
+2325,2328,2400-17-1,n2c1ccccc1c(NC)s2,Training,0,0,56,0.6993708877229697,24.92,49.16670000000002,2.7600048984601746,366.88449368949705,164.233,2.338
+2326,2329,2402-77-9,n1cccc(c1Cl)Cl,Training,1,0,42,0.5143628381850539,12.89,34.257000000000005,3.1348615113454477,166.5384734445621,147.99200000000002,2.3884000000000007
+2327,2330,2402-78-0,n1c(cccc1Cl)Cl,Training,0,0,42,0.5143628381850539,12.89,34.257000000000005,3.077660437970554,170.2884734445621,147.99200000000002,2.3884000000000007
+2328,2331,2403-27-2,O=C(C=Cc1ccccc1)c2ccc(cc2)Br,Training,0,0,84,0.6057610586489278,17.07,73.94850000000002,2.118858712905589,526.6080948683215,287.156,4.345200000000002
+2329,2332,2403-28-3,O=C(C=Cc1ccc(cc1)c2ccccc2)c3ccccc3,Training,0,0,106,0.47215288264980537,17.07,91.68450000000003,1.738977687057901,769.1557182757713,284.358,5.249700000000004
+2330,2333,24072-75-1,n2c1cc(c(cc1sc2N)Cl)Cl,Training,0,0,62,0.7383881969774914,38.91,54.052400000000006,2.825866007367726,399.1441508912841,219.09599999999998,3.1853000000000007
+2331,2334,24085-03-8,Oc1ccc(cc1CO)C(O)CN(Cc2ccccc2)C(C)(C)C,Training,1,1,130,0.7612958715027922,63.93,95.59440000000005,2.1659781039843757,649.678691503487,329.4400000000001,3.218600000000002
+2332,2335,24085-06-1,O=C(Oc1ccc(cc1COC(=O)C)C(=O)C)C,Training,1,1,96,0.46328529431895,69.67,63.22550000000003,3.0432856796545007,490.15501276609626,250.24999999999991,1.8776
+2333,2336,24085-08-3,O=C(c1ccc(O)c(c1)CO)CN(Cc2ccccc2)C(C)(C)C,Training,1,1,128,0.7987385650011551,60.77,94.96510000000005,2.18365680313341,689.7753034689551,327.42400000000004,3.3679000000000023
+2334,2337,24096-53-5,O=C2N(c1cc(cc(c1)Cl)Cl)C(=O)CC2,Training,0,0,78,0.7118590099339056,37.38,58.18900000000002,2.441532558858985,408.79857075425326,244.0769999999999,2.6468000000000007
+2335,2338,24099-25-0,n3c1occc1c(OC)c4ccc(OCC2OC2(C)(C))c(OC)c34,Training,0,1,126,0.6669364872862791,66.25000000000001,89.06600000000006,1.7984655967250538,914.5493998000126,329.3520000000001,3.554400000000002
+2336,2339,24143-08-6,O=C(NC1=NC(=NOC1)c2oc(cc2)[N+](=O)[O-])C,Training,1,1,94,0.6034957940386759,119.33000000000001,59.10310000000001,2.216730914166583,559.0591558312447,252.186,0.41419999999999974
+2337,2340,2415-85-2,O=C(Nc1ccc(cc1)C)CC(=O)C,Training,0,0,74,0.7416579046219026,46.17,55.106700000000025,2.5613587849536317,340.81009353303034,191.22999999999993,1.91262
+2338,2341,24167-40-6,OCc4ccc1c3c(nn1CCN(CC)CC)c2ccc(cc2Sc34)Cl,Training,1,1,136,0.5222579773122773,41.290000000000006,108.01280000000003,1.860929597703354,965.3349648366242,387.93600000000004,4.655400000000005
+2339,2342,2416-94-6,Oc1c(ccc(c1C)C)C,Training,0,0,54,0.579935465772167,20.23,42.31780000000001,3.3421538077705124,224.150333363576,136.194,2.3174600000000005
+2340,2343,2417-77-8,c1ccc3c(c1)cc2ccccc2c3CBr,Training,1,1,78,0.43646308796574596,0.0,74.08500000000002,2.562614287594415,601.7040048216327,271.1569999999999,4.887900000000002
+2341,2344,24191-98-8,OC5c4cc1OCOc1c3c2ccccc2CC(c34)N(C)C5,Training,1,1,112,0.8111351015565127,41.93,82.03580000000004,1.8954305214082579,786.1420031962217,295.3380000000001,2.6583000000000006
+2342,2345,24225-71-6,O=C(N(Nc2ccc3c1ccccc1Cc3(c2))c5ccc6c4ccccc4Cc6(c5))C,Training,1,1,150,0.35703876343210844,32.34,126.15070000000001,1.3089518031596585,1354.9762189082562,402.4970000000002,6.209000000000005
+2343,2346,2422-79-9,c1ccc4c(c1)ccc3cc2ccccc2c(c34)C,Training,1,1,90,0.2837498834433012,0.0,83.69700000000005,2.3341305116332856,916.7400111490208,242.32099999999997,5.454620000000003
+2344,2347,24245-98-5,O=[N+]([O-])c2cccc1nscc12,Training,1,1,60,0.4989745387229236,56.03,46.274400000000014,2.8189069531314526,437.653925895611,180.188,2.2045000000000003
+2345,2348,24245-99-6,O=[N+]([O-])c1ccc2nscc2(c1),Training,1,1,60,0.4989745387229236,56.03,46.27440000000001,2.676772326608393,437.653925895611,180.188,2.2044999999999995
+2346,2349,24246-00-2,O=[N+]([O-])c2cccc1csnc12,Training,1,1,60,0.49897453872292347,56.03,46.274400000000014,2.8189069531314526,437.653925895611,180.18799999999996,2.2045000000000003
+2347,2350,2425-85-6,O=[N+]([O-])c3cc(ccc3(N=Nc1c(O)ccc2ccccc12))C,Training,1,1,114,0.4106332093057893,88.09,87.62220000000003,2.1125834566296704,935.5149521443175,307.309,5.177420000000003
+2348,2351,24260-08-0,O=C1C=C(NC(=O)C)C(=O)C=C1(OCC),Training,1,0,80,0.6678655175883731,72.47,51.622700000000016,2.8330908119760703,378.88362704179656,209.20099999999996,0.07859999999999978
+2349,2352,24279-91-2,O=C(OCC(OC)C=1C(=O)C(=C(C(=O)C=1N2CC2)C)N3CC3)N,Training,1,1,124,0.5150391014379719,101.71000000000001,79.21840000000002,1.9922066973676975,643.497789349035,321.3330000000001,-0.5921999999999983
+2350,2353,2431-50-7,C=C(C(CCl)Cl)Cl,Training,1,1,42,0.5434495702944464,0.0,35.354000000000006,3.3434170589539596,69.33515884998701,159.443,2.5851000000000006
+2351,2354,24316-91-4,N#[N+]c1nc[nH]c1(C(=O)N),Training,1,0,50,0.5335165168258816,99.92,31.849600000000002,3.1686969367298308,294.8417497819427,138.10999999999996,-0.006820000000000104
+2352,2355,2431-96-1,O=C(N(CC)CC)Cc1ccccc1,Training,0,0,76,0.7133510509163976,20.310000000000002,58.07400000000004,2.5656015873548803,277.6330203302586,191.27400000000003,2.0975
+2353,2356,24325-70-0,O=[N+]([O-])c2ccc(C=Cc1ccc(cc1)C)cc2,Training,1,1,90,0.4599673088119517,43.14,73.20340000000003,2.1329911792252636,568.4475261916773,239.274,4.073620000000003
+2354,2357,2432-99-7,O=C(O)CCCCCCCCCCN,Training,0,0,84,0.5337925343232628,63.31999999999999,58.24320000000004,2.884064614706359,137.24922110379617,201.30999999999995,2.5406
+2355,2358,2435-76-9,[N-]=[N+]=C1C=NC(=O)NC1(=O),Training,1,1,50,0.34214759491318986,94.93,30.657099999999993,3.0370241963809956,272.98217866627283,138.08599999999998,-1.0222
+2356,2359,24367-94-0,O=C(Nc1ccc(cc1)Cc2ccc(N)cc2)C,Training,0,1,92,0.8104369334510548,55.120000000000005,74.40610000000002,2.056698887808123,529.4249890908638,240.30599999999995,2.8180000000000014
+2357,2360,24370-25-0,O=C(N)Nc1nc2ccccc2([nH]1),Training,1,1,66,0.6064048089616324,83.80000000000001,49.299800000000005,2.4362078334405046,415.09568206815914,176.179,1.0535
+2358,2361,2437-56-1,C=CCCCCCCCCCCC,Training,0,0,78,0.3257941482060202,0.0,62.041000000000054,2.7919988397452453,94.21143267166842,182.35099999999997,5.093300000000005
+2359,2362,24385-10-2,O=C1c4cccc(OC)c4(C(=O)c2c(O)c3c(c(O)c12)CC(O)(C(=O)CO)CC3(O)),Training,1,1,156,0.3757386534272321,161.59,99.95400000000002,2.006206605382451,1134.0274572955639,414.3660000000002,0.15389999999999965
+2360,2363,2438-88-2,O=[N+]([O-])c1c(c(c(OC)c(c1Cl)Cl)Cl)Cl,Training,0,0,82,0.4654661907787782,52.370000000000005,59.688400000000016,3.6628018257037738,405.72885338831924,290.91700000000003,4.2170000000000005
+2361,2364,24400-01-9,O=[N+]([O-])c3ccc(c2nc1ccccc1c(NCCCN(C)C)c23)C,Training,1,1,130,0.3186212767227781,71.3,102.30110000000005,2.2019876271259573,937.4993397242349,338.4110000000001,3.9682200000000023
+2362,2365,24424-99-5,O=C(OC(=O)OC(C)(C)C)OC(C)(C)C,Training,0,0,88,0.4618020515296314,61.83000000000001,53.55300000000004,4.041791025469495,217.51881261899078,218.24899999999994,2.8732000000000015
+2363,2366,2444-36-2,O=C(O)Cc1ccccc1Cl,Training,0,0,58,0.7370308543728599,37.3,42.791800000000016,2.8574541535636215,270.54949758389114,170.59499999999997,1.9671
+2364,2367,24463-15-8,OCc1ccc2ccc3cccc4ccc1c2c34,Training,1,1,86,0.49024448410288,20.23,76.06880000000004,2.3960659705844036,845.3562009804832,232.28199999999998,4.076300000000002
+2365,2368,24463-19-2,c1ccc3c(c1)cc2ccccc2c3CCl,Training,1,1,78,0.41567367522619864,0.0,71.01100000000002,2.562614287594415,601.7040048216327,226.70599999999996,4.7318000000000024
+2366,2369,244-63-3,n1ccc3c(c1)[nH]c2ccccc23,Training,1,1,62,0.5489485570430717,28.68,53.59970000000001,2.6424382599070015,515.8499381135529,168.19899999999998,2.716100000000001
+2367,2370,24471-48-5,OCc1cc2ccc3cccc4ccc(c1)c2c34,Training,1,1,86,0.49024448410287996,20.23,76.06880000000004,2.345195741352167,797.3562009804833,232.28199999999998,4.0763000000000025
+2368,2371,244775-76-6,O=C(ON(OCCC)C(=O)c1ccccc1)C,Training,1,1,92,0.7508905133681764,55.839999999999996,60.620500000000035,2.7484796174950237,377.35183546338794,237.25500000000002,1.9485
+2369,2372,2449-49-2,c1ccc(cc1)C(N(C)C)C,Training,0,0,60,0.6233820704291835,3.24,48.54400000000004,2.767917781307444,203.3725789018201,149.23699999999997,2.3092000000000006
+2370,2373,24496-65-9,n1cc4c5ccccc5(cc3ccc2cccc1c2c34),Training,1,1,92,0.27513954991473816,12.89,85.44700000000005,2.2308401762301724,1075.449826045032,253.30399999999997,5.132200000000003
+2371,2374,24519-27-5,N#CC1=C(C#N)SCCS1,Training,0,0,50,0.5523021705779386,47.58,43.16800000000001,2.884636787842561,217.45388105272013,168.246,1.7251599999999998
+2372,2375,2453-44-3,O=C(C=Cc1ccccc1)c2ccc(cc2)c3ccccc3,Training,0,0,106,0.47215288264980537,17.07,91.68450000000003,1.7544488099335116,769.1557182757713,284.358,5.249700000000004
+2373,2376,24549-06-2,Nc1c(cccc1CC)C,Training,1,1,54,0.5864506499226729,26.02,44.96940000000002,3.14303948130643,228.16991743324434,135.20999999999998,2.13962
+2374,2377,24554-26-5,O=CNc1nc(cs1)c2oc(cc2)[N+](=O)[O-],Training,1,1,82,0.4985767822462024,98.27000000000001,56.1571,2.274112946065218,532.880744675396,239.212,1.8796
+2375,2378,2457-47-8,n1cc(cc(c1)Cl)Cl,Training,0,0,42,0.5498499562311868,12.89,34.25700000000001,3.077660437970554,170.2884734445621,147.99200000000002,2.3884000000000007
+2376,2379,2458-12-0,O=C(O)c1ccc(c(N)c1)C,Training,1,0,58,0.5939754757329645,63.31999999999999,42.550700000000006,3.1515496683060507,294.1435742307893,151.165,1.27542
+2377,2380,24602-86-6,O1C(C)CN(CCCCCCCCCCCCC)CC1C,Training,0,0,126,0.44673993731947287,12.47,92.91000000000008,1.819881568195735,221.6062431575414,297.52699999999993,5.406600000000006
+2378,2381,2461-42-9,O(c1cccc2ccccc12)CC3OC3,Training,1,1,76,0.710252706783344,21.759999999999998,59.183000000000035,1.9343076282363667,469.4245768914959,200.23699999999997,2.617400000000001
+2379,2382,2461-43-0,O(c1ccccc1Cc2ccccc2)CC3OC3,Training,1,1,92,0.7491608895896618,21.759999999999998,70.92500000000004,1.7317140391437156,503.515226919435,240.302,3.0550000000000015
+2380,2383,2465-27-2,N=C(c1ccc(cc1)N(C)C)c2ccc(cc2)N(C)C,Training,1,1,104,0.8620350872186727,30.330000000000005,87.46870000000006,2.2190020999743023,527.1371109583483,267.37600000000003,3.234770000000002
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+2382,2385,2467-03-0,Oc1ccc(cc1)Cc2ccccc2(O),Training,0,0,76,0.7820224254390317,40.46,59.01960000000003,2.221797193855133,446.34806165346157,200.23700000000002,2.6886000000000014
+2383,2386,24684-41-1,c1ccc2c(c1)ccc3c2c(cc4c3CCC4)C,Training,0,1,88,0.48876015607153755,0.0,78.21600000000004,2.2637105360218,765.6843805196504,232.3259999999999,4.7901200000000035
+2384,2387,24684-42-2,O=C4c3c2ccc1ccccc1c2c(cc3CC4)C,Training,1,1,92,0.5361667709880622,17.07,78.84250000000004,2.279572290798192,843.0530656994204,246.30899999999994,4.430320000000003
+2385,2388,24684-49-9,O=C3c2cc(c1c4ccccc4(c(OC)cc1c2CC3))C,Training,1,1,104,0.6141629973560317,26.3,85.39450000000005,2.2650766873484467,906.4677704705265,276.335,4.438920000000003
+2386,2389,24684-56-8,O=C3c2cc(c1c4ccccc4(ccc1c2CC3(O)))C,Training,1,1,98,0.6303801657373395,37.3,80.23230000000004,2.209803326735075,877.3502963384358,262.308,3.4011200000000024
+2387,2390,24698-43-9,O=S(=O)(OCC(C)C)c1ccccc1,Training,1,1,78,0.7203436472913438,43.370000000000005,54.417800000000035,2.770213615145437,367.6134012182655,214.286,2.0479000000000003
+2388,2391,24752-66-7,O=C(NCc1ccccc1)C(C)Cl,Training,0,0,70,0.7376530299910611,29.1,53.60370000000003,2.398383565524446,271.5130516555259,197.665,1.9300999999999997
+2389,2393,2475-45-8,O=C1c3c(N)ccc(N)c3(C(=O)c2c(N)ccc(N)c12),Training,1,1,100,0.4444898225677832,138.22,77.39859999999999,2.461802657327663,666.7462922813075,268.276,0.7908000000000002
+2390,2394,2475-46-9,O=C1c3ccccc3(C(=O)c2c(ccc(NC)c12)NCCO),Training,1,1,112,0.6852237901719327,78.43,84.87120000000003,2.2480595520146864,768.4945217028386,296.3260000000001,1.9078999999999993
+2391,2395,24777-14-8,Oc1ccc(cc1(OC))c3nc(c2ccccc2)c([nH]3)c4ccccc4,Training,1,1,128,0.5407150301398119,58.14,103.1125,1.8911261291325496,967.7138235865135,342.398,5.124900000000004
+2392,2396,2478-38-8,O=C(c1cc(OC)c(O)c(OC)c1)C,Training,0,0,76,0.7460177818557394,55.760000000000005,51.21530000000003,3.3153826691682906,332.13478538484,196.20199999999997,1.6119999999999999
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+2395,2399,2481-94-9,N(=Nc1ccc(cc1)N(CC)CC)c2ccccc2,Training,0,1,98,0.692851856886076,27.96,80.62100000000005,2.086339079358203,513.4501262125178,253.349,4.9482000000000035
+2396,2400,2489-77-2,N(C(N(C)C)=S)C,Training,0,0,42,0.45249692321264945,15.27,35.3447,3.3530759537985286,70.09004635215048,118.20499999999998,0.05230000000000001
+2397,2401,24903-46-6,n3ccc4ccc2cc5ccc1ccccc1c5(cc2c4(c3)),Training,1,1,102,0.26178540224276026,12.89,94.26100000000004,2.0509694788679025,1081.1666469437955,279.342,5.6944000000000035
+2398,2402,24903-48-8,n4ccc5ccc3cc2c(ccc1ccccc12)cc3c5(c4),Training,1,1,102,0.26178540224276026,12.89,94.26100000000004,2.019425486081905,1076.6666469437955,279.342,5.6944000000000035
+2399,2403,2491-52-3,O=[N+]([O-])c2ccc(N=Nc1ccccc1)cc2,Training,1,1,84,0.45124873238942653,67.86,63.71440000000003,2.141749011360421,535.437016291632,227.22300000000004,4.010200000000002
+2400,2404,24930-41-4,n2c1ccccc1c3ccc5cccc4ccc2c3c45,Training,1,1,92,0.27513954991473816,12.89,85.44700000000005,2.2308401762301724,1075.449826045032,253.30399999999997,5.132200000000003
+2401,2405,24934-91-6,O(CC)P(OCC)(=S)SCCl,Training,0,0,68,0.5187715686345127,18.46,55.84800000000003,3.908471949775869,120.66966981975612,234.70999999999998,3.213400000000002
+2402,2406,2493-84-7,O=C(O)c1ccc(OCCCCCCCC)cc1,Training,0,1,100,0.6703496754936857,46.53,72.27230000000004,2.135099982889189,343.2612760189044,250.3379999999999,4.124100000000004
+2403,2407,24953-56-8,n1nc(OC)c2ccccc2(c1),Training,0,0,60,0.6356552607915211,35.010000000000005,46.090000000000025,2.7909670297392637,395.15559777115004,160.176,1.6383999999999999
+2404,2408,24954-53-8,O=C(ON(C(=O)NC)C(=O)NC)NC,Training,0,1,80,0.45129155924855807,99.77000000000001,46.291100000000014,4.475972227168676,225.98600339321575,204.186,-0.7617999999999998
+2405,2409,24961-39-5,c1ccc4c(c1)ccc3c4(cc2ccccc2c3CBr),Training,1,1,96,0.22765176281395233,0.0,91.59100000000005,2.300527217114131,937.9563134380708,321.217,6.041100000000004
+2406,2410,24966-35-6,O=C(NC)N(O)C(=O)NC,Training,0,1,58,0.314511389089264,81.67000000000002,32.536899999999996,3.9400179889077265,130.68324254705823,147.134,-0.6436000000000002
+2407,2411,2498-75-1,c3ccc4cc2c(ccc1cc(ccc12)C)cc4(c3),Training,1,1,90,0.2837498834433012,0.0,83.69700000000003,2.2224786767238656,916.7400111490208,242.32099999999997,5.454620000000004
+2408,2412,2498-76-2,c3ccc4cc2c(ccc1ccc(cc12)C)cc4(c3),Training,1,1,90,0.2837498834433012,0.0,83.69700000000003,2.247182671771032,916.7400111490208,242.32099999999997,5.454620000000004
+2409,2413,2498-77-3,c3ccc4cc2c(ccc1cccc(c12)C)cc4(c3),Training,1,1,90,0.2837498834433012,0.0,83.69700000000003,2.288164726178113,916.7400111490208,242.32099999999997,5.454620000000004
+2410,2414,2499-95-8,O=C(OCCCCCC)C=C,Training,0,0,64,0.3348650134513954,26.3,45.298000000000016,3.0128585388016287,118.731140660285,156.225,2.2959000000000005
+2411,2415,25003-82-1,n3ccc4cc2c(ccc1ccccc12)cc4(c3),Training,1,1,84,0.31841665410737346,12.89,76.75500000000002,2.268265813130303,871.8244038631084,229.28199999999998,4.541200000000003
+2412,2416,25057-89-0,O=C1c2ccccc2(NS(=O)(=O)N1C(C)C),Training,0,0,86,0.8018889091426249,66.48,60.29000000000002,2.6065559005204846,536.7500531426354,240.28399999999996,1.2075
+2413,2417,25058-17-7,OP(O)Oc1ccc(cc1)C(c2ccc(OP(O)O)cc2)(C)C,Training,0,0,124,0.5934906504114901,99.38000000000001,88.98320000000002,2.1943902184960926,569.9202906086183,356.25100000000003,3.193100000000002
+2414,2418,25074-67-3,o2c1ccccc1c3ccc(cc23)Cl,Training,1,0,68,0.531560836348283,13.14,58.730000000000025,2.566841134269145,609.8208026305191,202.64,4.239400000000002
+2415,2419,25081-31-6,O=NN(CC(=O)O)CC(=O)O,Training,1,1,62,0.4019120414337759,107.27,32.639599999999994,3.8531250010011684,163.32123112606797,162.101,-0.8610000000000002
+2416,2420,2508-20-5,O=Nc2ccc3c1ccccc1Cc3(c2),Training,1,1,72,0.5446964715511566,29.43,60.139000000000024,2.221286544526275,545.9822585532199,195.22099999999998,3.655700000000002
+2417,2421,25082-33-1,n2ccc3ccc1cc4ccccc4(cc1c3(c2)),Training,1,1,84,0.31841665410737346,12.89,76.75500000000002,2.268265813130303,871.8244038631086,229.28199999999998,4.541200000000003
+2418,2422,2508-23-8,O=C(N(O)c1ccc2ccccc2(c1))C,Training,1,1,76,0.568690699900492,40.540000000000006,58.89450000000003,2.5122035135906957,507.7032081711418,201.225,2.581900000000001
+2419,2423,25125-72-8,c1ccc(cc1)C3NC3(c2ccccc2),Training,1,1,74,0.7307057401652806,21.94,61.501700000000035,1.8072004154913701,391.9105840848162,195.265,3.0722000000000014
+2420,2424,25148-26-9,c1ccc3c(c1)c(c2ccccc2c3CCl)C,Training,1,1,84,0.4129411868962604,0.0,75.74800000000003,2.631771409903851,641.2790663039684,240.73299999999995,5.040220000000002
+2421,2425,25148-68-9,Nc1ccccc1(NC),Training,1,1,48,0.5510029484996731,38.05,40.401100000000014,3.0065240073265844,195.86256853719752,122.17099999999999,1.3105
+2422,2426,25152-84-5,O=CC=CC=CCCCCC,Training,0,0,62,0.247394576935257,17.07,48.48600000000003,3.1548561659412027,133.8082034586482,152.237,2.878000000000001
+2423,2427,2516-93-0,O=C(O)COCCCC,Training,0,0,54,0.5648370720626691,46.53,33.36279999999999,2.8288681349096856,80.37215811651096,132.15900000000002,0.8877000000000002
+2424,2428,2517-43-3,OCCC(OC)C,Training,0,0,44,0.5613868084500069,29.46,28.173799999999986,2.8318199660707837,37.06139398862029,104.149,0.40369999999999995
+2425,2429,2517-98-8,O=C(OCc3c1ccccc1c(c2c4ccccc4(ccc23))C)C,Training,1,1,118,0.27660304526442664,26.3,99.16700000000006,2.1809401076781785,1093.2169605226784,314.38400000000007,5.517720000000004
+2426,2430,2520-60-7,O=C1CCCC1CC=C(C)C,Training,0,0,62,0.5558966742364874,17.07,46.39600000000002,2.371671030083734,175.31179861284463,152.237,2.711900000000001
+2427,2431,2523-37-7,c1ccc3c(c1)c2ccccc2C3C,Training,1,1,68,0.577836995669327,0.0,59.39500000000003,2.358276060638899,437.4019131322054,180.24999999999997,3.818800000000002
+2428,2432,2524-03-0,O(C)P(OC)(=S)Cl,Training,0,0,44,0.5736866146758027,18.46,34.156,3.605378627989909,87.69058447171099,160.56199999999998,1.7425
+2429,2433,2528-36-1,O=P(Oc1ccccc1)(OCCCC)OCCCC,Training,0,0,108,0.4572367586312284,44.760000000000005,76.39650000000005,2.5914128917982353,366.29217101740784,286.308,4.806900000000004
+2430,2434,25316-40-9,O=C1c5cccc(OC)c5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)CO)CC4(OC3OC(C)C(O)C(N)C3)),Training,1,1,208,0.23526258168565614,206.07,131.7544,1.686263209970168,1376.5187409654486,543.5250000000002,0.0012999999999993017
+2431,2435,2531-84-2,c1ccc3c(c1)ccc2cc(ccc23)C,Training,1,1,72,0.4656830848993307,0.0,66.19100000000003,2.545878518715751,635.6567221133736,192.26099999999997,4.301420000000002
+2432,2436,253-52-1,n1ncc2ccccc2(c1),Training,0,0,48,0.5412819114011972,25.78,39.53800000000002,2.8880516016579914,278.23446335792846,130.14999999999998,1.6298
+2433,2437,253-53-2,n1ncc2ccncc2(c1),Training,0,0,48,0.5355010476666257,38.67,37.33300000000001,2.8880516016579914,279.82809140136175,131.13799999999998,1.0248
+2434,2438,253-73-6,n1ncc2cccnc2(c1),Training,0,0,48,0.5355010476666257,38.67,37.33300000000001,2.8880516016579914,279.82809140136175,131.13799999999998,1.0248
+2435,2439,2540-82-1,O=CN(C(=O)CSP(OC)(OC)=S)C,Training,0,1,82,0.5192128575880584,55.84,59.59500000000003,4.109305020933432,252.21605924781636,257.27299999999997,0.8516999999999999
+2436,2440,25413-02-9,O=C(OCC)CNC(=O)C(C)Br,Training,1,0,70,0.571038265862248,55.4,48.03170000000002,3.542976317921822,170.03442356294346,238.081,0.4490999999999999
+2437,2441,25413-64-3,O=NN(CCC)CCCC,Training,1,1,60,0.42252463101609594,32.67,42.567000000000014,3.294531737146327,85.67529210449095,144.218,2.1799
+2438,2442,2541-69-7,c1ccc4c(c1)ccc3c4(cc2ccccc2c3C),Training,1,1,90,0.2837498834433012,0.0,83.69700000000005,2.318193083302064,916.7400111490208,242.32099999999997,5.454620000000004
+2439,2443,2550-75-6,C1(=C(C2(C(CCl)C(CCl)C1(C2(Cl)Cl)Cl)Cl)Cl)Cl,Training,0,0,98,0.536467272364742,0.0,78.75700000000002,2.716115159554925,356.4570923448172,397.77099999999996,5.5419
+2440,2444,25584-83-2,O=C(OCC(O)C)C=C,Training,0,0,52,0.4349506369348388,46.53,32.83679999999998,3.2725014723788193,106.87060032410332,130.14299999999997,0.09639999999999982
+2441,2445,25590-58-3,O=[N+]([O-])[C-]C,Training,0,0,29,0.19401730466341127,43.14,15.911400000000002,2.8473789230876716,42.91260938324327,73.051,0.3217899999999999
+2442,2446,25635-22-7,O=C(OCC)c2cccc1cccnc12,Training,0,0,76,0.7002305868417755,39.19,57.69950000000003,2.5551545743663597,488.45103080120373,201.225,2.4115
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+2445,2449,2564-83-2,ON1C(C)(C)CCCC1(C)C,Training,0,1,66,0.5834257053816999,23.47,45.634500000000024,2.7623132262307584,135.6417228439527,157.257,2.4187000000000003
+2446,2450,25703-79-1,O=C(OCC(O)C)C(=C)C,Training,0,0,58,0.4627900749426472,46.53,37.4538,3.502986511184309,137.78664559481845,144.16999999999996,0.4864999999999999
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+2448,2452,257948-44-0,O=[N+]([O-])c2ccc3c4nc1ccccc1c5c6ccccc6(nc(c3(c2))c45),Training,1,1,126,0.22346410175238152,68.92,105.63440000000003,1.908603268623385,1441.4686877244278,349.3490000000001,5.491800000000003
+2449,2453,25799-70-6,O=[N+]([O-])c3ccc(OC)c2nc1ccccc1c(NCCCN(C)C)c23,Training,1,1,136,0.30173670474688213,80.53,104.11610000000005,2.226712257144393,956.3156549078509,354.4100000000002,3.668400000000002
+2450,2454,25834-80-4,Nc1ccc(cc1)Cc2ccc(N)c(c2)Cc3ccc(N)cc3,Training,1,0,116,0.6441705434314563,78.06,98.1752,1.805858992908597,790.1207016270149,303.40900000000005,3.6148000000000016
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+2452,2456,2586-60-9,O=S(=O)(O)c5cc(O)c6c(N=Nc1ccc(cc1)c4ccc(N=Nc2c(N)ccc3cc(cc(O)c23)S(=O)(=O)O)cc4)c(N)ccc6(c5),Training,1,1,242,0.054627462636098925,250.67999999999998,179.90959999999987,1.2240185493481999,2359.75154981083,684.7120000000002,7.559800000000006
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+2457,2461,25917-90-2,O=[N+]([O-])c1cc(N)c(OC)cc1(N),Training,1,1,70,0.3999143041427396,104.41,48.4732,3.2813215562876055,351.0811582766401,183.167,0.7678
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+2465,2469,26049-69-4,O=[N+]([O-])c1oc(cc1)c2nc(NN(C)C)sc2,Training,1,1,90,0.6646972449526384,84.44,63.780100000000026,2.2094661702871075,533.838287963671,254.271,2.1997999999999998
+2466,2470,26049-70-7,O=[N+]([O-])c1ccc(cc1)c2nc(NN)sc2,Training,1,1,82,0.4825992368331361,94.08,62.01450000000001,2.3036154351173055,508.482466596508,236.256,2.0039
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+2468,2472,26078-25-1,O=C2Oc1cc(NCC)c(cc1C(=C2)C)C,Training,0,0,84,0.7863683894487061,42.24,66.12170000000002,2.736929613753668,584.2376673642669,217.26799999999997,2.841640000000001
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+2470,2474,26091-73-6,O=C3Oc4cc1occc1c(OCC2OC2(C)(C))c4(C=C3),Training,0,0,108,0.5465179006847264,65.11,76.70300000000005,1.8235177977314345,886.4502183828415,286.28299999999996,3.0954000000000015
+2471,2475,26093-31-2,O=C2Oc1cc(N)ccc1C(=C2)C,Training,0,0,66,0.48923655034723423,56.230000000000004,51.633400000000016,2.9445242725786405,513.8039395673064,175.18699999999998,1.68362
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+2487,2491,26538-44-3,O=C1OC(C)CCCC(O)CCCCCc2cc(O)cc(O)c12,Training,0,0,128,0.6380402391746317,86.99000000000001,86.67890000000004,2.214095020924336,540.4586369247522,322.401,3.290800000000003
+2488,2492,26541-51-5,O=NN1CCSCC1,Training,1,1,46,0.4926212811282644,32.67,34.693,2.2166579722077144,82.10749561002055,132.18800000000002,0.7166000000000001
+2489,2493,26541-56-0,O=C(ON(c1ccc(cc1)c2ccccc2)C(=O)C)C,Training,1,1,102,0.78652319055313,46.61,76.80400000000004,2.2657629261415737,605.3789283498221,269.3,3.1846000000000014
+2490,2494,2657-25-2,O=C(C=Cc1ccccc1)c2ccc(O)cc2,Training,0,0,84,0.6412736177915347,37.3,67.91330000000002,2.1188587129055887,524.6080948683215,224.25900000000001,3.2883000000000013
+2491,2495,26651-23-0,O=S(=O)(O)c4ccc1ccc2cccc3ccc4(c1c23),Training,1,1,98,0.42618547268213897,54.370000000000005,79.96060000000004,2.3888023962102074,1049.3914065691013,282.32000000000005,3.830700000000002
+2492,2496,26675-46-7,FC(F)OC(C(F)(F)F)Cl,Training,0,0,62,0.47287129526793736,9.23,22.784999999999997,3.7348237213155926,101.55641063961481,184.49099999999999,2.3528000000000002
+2493,2497,26676-89-1,O=C2OC1C(O)COC1(O)C2(O)Cc4c[nH]c3ccccc34,Training,0,1,116,0.553778193363766,112.01000000000002,73.74110000000003,1.7623769005211334,757.32555849951,305.286,-0.5534000000000001
+2494,2498,26741-53-7,O(c1ccc(cc1C(C)(C)C)C(C)(C)C)P2OCC4(CO2)(COP(Oc3ccc(cc3C(C)(C)C)C(C)(C)C)OC4),Training,0,0,228,0.32393548702112,55.38000000000001,169.02099999999953,1.3691352003561066,1101.1752510742103,604.7050000000002,9.868199999999996
+2495,2499,2675-77-6,O(c1cc(c(OC)cc1Cl)Cl)C,Training,1,0,66,0.7414561071184836,18.46,49.56600000000002,3.164874105084725,256.88150377072884,207.05599999999998,3.010600000000002
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+2497,2501,2687-25-4,Nc1cccc(c1(N))C,Training,1,1,48,0.5071584204162337,52.04,40.00380000000001,3.2478347337367026,197.9061775999341,122.171,1.1594200000000001
+2498,2502,2687-40-3,O=C(Nc2ccc(Oc1ccc(cc1)[N+](=O)[O-])cc2)C,Training,1,1,102,0.683157673637438,81.47,73.91610000000001,2.0560477675416062,620.6270925467023,272.26,3.345500000000002
+2499,2503,2687-41-4,O=C(Nc2ccc(Oc1ccc(N)cc1)cc2)C,Training,1,1,92,0.8129811262092046,64.35,71.67410000000002,2.0566988878081234,532.7253791161852,242.278,3.0195000000000016
+2500,2504,26921-17-5,OC(COc1nsnc1N2CCOCC2)CNC(C)(C)C,Training,0,0,120,0.790985307512128,79.74000000000001,82.19850000000005,1.815875286791508,429.2960174181891,316.427,0.5024999999999997
+2501,2505,2693-46-1,Nc2ccc4c1ccccc1c3cccc2c34,Training,1,1,80,0.4413478987641275,26.02,72.79040000000002,2.302037773130904,727.3150785276883,217.271,4.069400000000002
+2502,2506,26946-33-8,O=[N+]([O-])c1cc(N)ccc1Cc2ccc(N)cc2[N+](=O)[O-],Training,1,1,108,0.5022295084035406,138.32,77.82360000000001,2.480200875140889,668.6063538201123,288.26300000000003,2.2581999999999995
+2503,2507,2698-41-1,N#CC(C#N)=Cc1ccccc1Cl,Training,1,0,62,0.6365903422378779,47.58,50.655000000000015,3.1359523239446565,405.2862656494693,188.61699999999996,2.7705600000000006
+2504,2508,27032-78-6,O=C1NC(=O)NCN1,Training,1,0,44,0.3773478911564581,70.23,25.066100000000002,2.4515934319435493,118.49022499567306,115.092,-1.0337
+2505,2509,27046-19-1,O=C1NP(=O)(OCC1)N(CCCl)CCCl,Training,1,1,88,0.6084824721623999,58.64000000000001,59.331200000000024,2.6977433218888183,270.9609120943884,275.07199999999995,1.4105999999999999
+2506,2510,27093-62-5,c1ccc2c(c1)ccc4c2c3c5ccccc5(ccc3n4C),Training,1,1,104,0.34607551567622735,4.93,95.43700000000005,2.2096362708893267,1085.2778354773475,281.358,5.637900000000004
+2507,2511,27108-42-5,O=C(ON)NC,Training,1,1,36,0.38319825492728415,64.35,19.728099999999998,2.98816088213427,47.50977500432694,90.082,-0.7839
+2508,2512,27113-22-0,O=C(CCc1ccc(O)c(OC)c1)CCCCCCC,Training,0,0,112,0.650296874228629,46.53,81.36280000000006,2.2659914729260335,412.69618538684995,278.39199999999994,4.2630000000000035
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+2512,2516,27343-29-9,O=C3c2cc(c1c4ccccc4(ccc1c2CCC3))C,Training,1,1,98,0.5294952218525127,17.07,83.45950000000005,2.2137093750472294,858.394048751053,260.33599999999996,4.820420000000003
+2513,2517,27354-18-3,O=C1c3ccccc3(C(=O)c2c(cccc12)NC(C)C),Training,1,1,100,0.7730823410813444,46.17,78.50770000000003,2.2281634928215266,716.6799853762478,265.312,3.282300000000001
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+2515,2519,2746-81-8,O=C(OCCN1CCN(CC1)CCCN4c2ccccc2Sc3ccc(cc34)C(F)(F)F)CCCCCC,Training,0,0,208,0.21340139673913955,36.02,146.22999999999982,1.231303515299503,1057.6041196836643,549.7030000000001,6.829400000000009
+2516,2520,2752-54-7,O=C(O)C(NC(=O)COc1ccc(cc1Cl)Cl)CC(C)C,Training,0,0,116,0.8037479859938591,75.63000000000001,80.97850000000004,2.5426671484493273,519.6955133164573,334.19900000000007,2.987700000000001
+2517,2521,27532-75-8,c1ccc3c(c1)cc2ccc(cc2c3C)C,Training,1,1,78,0.4710734601666233,0.0,70.92800000000004,2.5581440319024598,677.9984465766784,206.28799999999995,4.609840000000003
+2518,2522,27554-26-3,O=C(OCCCCCC(C)C)c1ccccc1(C(=O)OCCCCCC(C)C),Training,0,0,158,0.27108565447365673,52.60000000000001,113.61900000000009,2.388879530306986,526.7228097510647,390.5640000000003,6.433000000000007
+2519,2523,2757-90-6,O=C(O)C(N)CCC(=O)NNc1ccc(cc1)CO,Training,1,1,104,0.43618444998706546,124.67999999999999,68.97540000000001,2.3093031061793448,433.10556551577343,267.285,-0.18589999999999923
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+2522,2526,27602-80-8,O(c1ccc(cc1(OC))CC2OC2)C,Training,1,1,76,0.6826782871148175,30.990000000000002,52.99000000000003,2.1643079404466787,318.30872454975145,194.22999999999996,1.6451
+2523,2527,27729-95-9,O=C(c1ccccc1)C3OC3(c2ccc(OC)cc2),Training,1,0,96,0.6215522497314957,38.83,71.38050000000004,1.717974375007471,574.7028578552715,254.28499999999997,3.0180000000000016
+2524,2528,27729-98-2,O=C(c1ccccc1)C3OC3(c2ccc(F)cc2),Training,0,1,90,0.6109052956345439,29.6,64.78650000000002,1.7458884376146175,562.8072898380785,242.24899999999997,3.148500000000001
+2525,2529,27730-00-3,O=C(c1ccccc1)C3OC3(c2ccc(cc2)Br),Training,0,0,90,0.6378624785160687,29.6,72.52850000000002,1.7458884376146175,562.8072898380785,303.155,3.7719000000000023
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+2527,2531,27758-60-7,NN(c1ccc(cc1)C)c2ccc(cc2)C,Training,1,0,82,0.610922705516324,29.259999999999998,68.68440000000002,2.275318789867306,411.598944223399,212.296,3.315240000000002
+2528,2532,27762-78-3,O=C(C(O)O)C(OCC)C,Training,1,0,60,0.5167725554042628,66.76,34.32059999999999,3.705193450094498,110.31544376215959,148.158,-0.7088000000000001
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+2530,2534,27833-64-3,N=2c4ccccc4(Oc1ccc(cc1C=2N3CCN(C)CC3)Cl),Training,0,1,118,0.7369928778519519,28.07,93.23500000000004,1.8381648390067984,766.612056859587,327.81500000000005,3.7714000000000034
+2531,2535,2784-27-2,O=C1NC(=O)C(N1)(c2ccccc2)c3ccc(O)cc3,Training,0,1,100,0.7217147453460007,78.43,72.00320000000002,2.214393667663825,667.2777983730039,268.272,1.4751999999999998
+2532,2536,2784-86-3,O=C(Nc2ccc3c1ccccc1Cc3(c2(O)))C,Training,0,1,90,0.641345316341622,49.33,70.65250000000002,2.1221089116885192,646.9370156452684,239.27399999999997,2.921800000000001
+2533,2537,2784-94-3,O=[N+]([O-])c1cc(ccc1(NC))N(CCO)CCO,Training,1,1,100,0.48239771419078603,98.87,69.02770000000002,3.0769376627792084,405.2748404749571,255.27399999999994,0.42750000000000005
+2534,2538,279242-17-0,O=Nc1ccc(cc1)c2ccc(cc2)C(C)(C)C,Training,1,1,92,0.6741816510528421,29.43,76.03300000000004,2.3085196292012125,532.804798075736,239.31799999999998,5.049000000000004
+2535,2539,27946-19-6,O=C(NCc1ccccc1)C(c2ccccc2)Cl,Training,1,0,92,0.8391495099815115,29.1,73.32470000000004,1.9259496439299544,498.4167554874706,259.736,3.2829000000000024
+2536,2540,27969-93-3,Oc2ccc3ccccc3(c2(N=Nc1c(cccc1C)C)),Training,0,1,104,0.6101593506431456,44.95,85.70480000000003,2.1366545026354493,817.4910923576194,276.339,5.577640000000003
+2537,2541,27975-19-5,O=C(O)C4(C)(CCCC1(C)(C4(CCC23(CC(=O)C(C)(CCC12)C3)))),Training,0,0,128,0.7771841110494584,54.37,87.92980000000006,1.7555807250547988,583.4358604704929,318.4570000000001,4.443100000000004
+2538,2542,2798-25-6,O=C1c3c(O)cc(OC)cc3(Oc2c(O)ccc(O)c12),Training,1,1,102,0.4637045581175527,100.13000000000001,71.53640000000001,2.6114297338263213,893.6745460339985,274.228,2.0715999999999997
+2539,2543,280-57-9,N12(CCN(CC1)CC2),Training,0,0,46,0.42118438219503695,6.48,32.87999999999999,2.0315872925159697,61.50977500432693,112.176,-0.3824000000000001
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+2541,2545,2814-77-9,O=[N+]([O-])c3ccc(N=Nc1c(O)ccc2ccccc12)c(c3)Cl,Training,1,1,114,0.38981261933049044,88.09,87.89520000000003,2.038115378630728,941.0018204455731,327.7270000000001,5.522400000000004
+2542,2546,2815-45-4,O1CC12(CCC(CC2)C(C)(C)C),Training,0,0,70,0.5064976080049504,12.53,50.09600000000003,1.8973667404364885,163.93335895602462,168.27999999999997,2.9917000000000016
+2543,2547,28164-57-0,O=C3C=CC(=O)c4c(O)c(C1=CC(=O)c2c(O)cc(cc2(C1(=O)))C)c(cc34)C,Training,0,0,138,0.7938572461475192,108.74000000000001,100.12660000000001,1.9808569256266815,1210.2632795464344,374.3480000000001,3.112440000000001
+2544,2548,28166-06-5,[N-]=[N+]=Nc1ccc(F)c(c1)[N+](=O)[O-],Training,1,1,66,0.23096799248031832,91.9,41.86040000000001,3.2590787550702984,399.62076708767637,182.11399999999998,2.675700000000001
+2545,2549,28289-54-5,c1ccc(cc1)C2=CCN(C)CC2,Training,0,0,68,0.6300528582023182,3.24,56.53300000000004,2.1878552451550224,300.16033227962595,173.25899999999993,2.405500000000001
+2546,2550,2832-19-1,O=C(NCO)CCl,Training,0,0,42,0.37662607414344734,49.33,25.948499999999996,3.002590528674132,65.95524697820139,123.539,-0.7088000000000003
+2547,2551,28322-02-3,O=C(Nc1cccc3c1c2ccccc2C3)C,Training,1,1,84,0.6739434898699771,29.1,68.98770000000003,2.1896751549513014,601.6208569648081,223.27499999999998,3.2162000000000015
+2548,2552,2832-40-8,O=C(Nc2ccc(N=Nc1cc(ccc1(O))C)cc2)C,Training,1,1,102,0.8238898599683054,74.05,77.76550000000003,2.1471969013252448,648.6682438497095,269.30400000000003,4.074420000000002
+2549,2553,28342-33-8,O=C3c5c(OC)c(OC)ccc5(c2ccc1cc4OCOc4(cc1c2N3C)),Training,1,1,136,0.5095491922100782,58.92000000000001,103.42800000000005,2.010253902105367,1305.68602302594,363.36900000000014,3.5908000000000024
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+2551,2555,2835-39-4,O=C(OCC=C)CC(C)C,Training,0,0,58,0.4413586779330932,26.3,40.61100000000001,3.3404385429524037,116.42599881712918,142.19799999999998,1.7617
+2552,2556,2835-68-9,O=C(N)c1ccc(N)cc1,Training,0,0,52,0.5473422654963029,69.11,39.3723,3.003400684579818,240.2879489264805,136.154,0.3677
+2553,2557,2835-95-2,Oc1cc(N)ccc1C,Training,1,1,48,0.5103360477769769,46.25,37.256200000000014,3.1716780304409156,220.15617759993404,123.15499999999999,1.28282
+2554,2558,2835-97-4,Oc1cccc(c1(N))C,Training,0,1,48,0.40297528147681455,46.25,37.25619999999999,3.2478347337367026,199.9061775999341,123.155,1.28282
+2555,2559,2835-98-5,Oc1cc(ccc1(N))C,Training,1,1,48,0.40297528147681455,46.25,37.2562,3.1716780304409156,220.15617759993404,123.15499999999999,1.28282
+2556,2560,28361-96-8,O=C(O)C(N)CSCCCl,Training,1,1,60,0.4777384625029485,63.31999999999999,43.65620000000001,3.214876896824448,111.82107314610522,183.66,0.37030000000000035
+2557,2561,2837-89-0,FC(C(F)(F)F)Cl,Training,0,0,44,0.35334876064599263,0.0,16.804000000000002,3.541196965079901,55.20035947603792,136.47500000000002,2.0831
+2558,2562,28434-86-8,O(c1ccc(N)c(c1)Cl)c2ccc(N)c(c2)Cl,Training,1,1,88,0.8112065441071609,61.269999999999996,71.80280000000002,2.24918229304757,508.6970467453647,269.131,3.950100000000001
+2559,2563,2846-29-9,OOC2C=C1CC(O)CCC1(C)C3CCC4(C)(C(CCC4(C23))C(C)CCCC(C)C),Training,1,0,172,0.2813972815924836,49.69,121.9376000000001,1.5643869092348786,642.0194362953911,418.66200000000026,6.856800000000009
+2560,2564,2849-98-1,O=C(OCCCCC)C(=C)C,Training,0,0,64,0.34660761243015925,26.3,45.298000000000016,3.248575931419231,138.49815939454103,156.225,2.2959000000000005
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+2563,2567,2855-13-2,NCC1(C)(CC(N)CC(C)(C)C1),Training,0,0,72,0.626159402652027,52.04,52.768800000000034,2.695676570431627,165.22151457063651,170.29999999999998,1.4888000000000001
+2564,2568,28553-12-0,O=C(OCCCCCCC(C)C)c1ccccc1(C(=O)OCCCCCCC(C)C),Training,0,0,170,0.21007569490575018,52.60000000000001,122.8530000000001,2.3220024108637647,553.8060883770335,418.6180000000004,7.2132000000000085
+2565,2569,28564-83-2,O=C1C(O)=C(OCC1(O))C,Training,1,1,56,0.49103427209913,66.76,32.294599999999996,2.88200596437796,193.9244971645878,144.126,-0.2639
+2566,2570,28622-66-4,OC2C=Cc1c3ccccc3(ccc1C2(O)),Training,1,1,80,0.702855616017261,40.46,63.94860000000004,2.3424763800312483,571.9570917536973,212.248,2.260900000000001
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+2570,2574,2867-47-2,O=C(OCCN(C)C)C(=C)C,Training,1,0,64,0.44343244393626924,29.54,44.32700000000001,3.3972180387789788,152.1710478569335,157.213,0.6672999999999998
+2571,2575,286-75-9,O1C2CCC3OC3(CCC12),Training,0,0,56,0.47051975341513974,25.06,35.79,1.6665800794235246,123.33658100079684,140.182,1.0952
+2572,2576,286-99-7,O1C2CCCCCCCCCCC12,Training,0,0,76,0.5206870505609021,12.53,54.831000000000046,1.6570465580221716,128.05990292969187,182.307,3.6684000000000028
+2573,2577,2872-48-2,O=C1c3ccccc3(C(=O)c2c(N)c(OC)cc(N)c12),Training,1,1,100,0.6539288909842176,95.41,75.12580000000001,2.39050314982751,765.9542098555299,268.272,1.635
+2574,2578,2873-97-4,O=C(C=C)NC(C)(C)CC(=O)C,Training,0,0,68,0.6391631108293446,46.17,47.716700000000024,4.114410949466164,206.57407497429568,169.224,1.0463
+2575,2579,2876-22-4,n1c3ccccc3(nc2c1cccc2(N)),Training,1,1,72,0.4422537585998289,51.8,61.456400000000016,2.5325611743067444,646.485643536684,195.225,2.3651999999999993
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+2577,2581,2876-24-6,O=[N+]([O-])c2cccc1nc3ccccc3(nc12),Training,1,1,82,0.3624355213624682,68.92,63.698400000000035,2.4747546727156635,739.9847966621533,225.207,2.6912000000000003
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+2579,2583,28804-88-8,c1ccc2c(c1)ccc(c2C)C,Training,0,0,60,0.5476492453414697,0.0,53.422000000000025,2.9077745072579817,413.30786619344804,156.22799999999995,3.456640000000002
+2580,2584,2880-49-1,O=C2Oc3c(OCC1OC1(C)(C))c4occc4(cc3(C=C2)),Training,0,0,108,0.5465179006847264,65.11,76.70300000000003,1.8341738671302197,886.4502183828415,286.283,3.0954000000000015
+2581,2585,2880-58-2,O=C1C=CC(=O)C(OC)=C1,Training,0,1,52,0.48678538304410673,43.370000000000005,34.245999999999995,2.8896580555696265,235.23577433564375,138.122,0.2246999999999999
+2582,2586,288-32-4,n1cc[nH]c1,Training,0,0,26,0.4683433019217652,28.68,18.587699999999998,3.1250000000000004,61.369930610534254,68.079,0.40969999999999995
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+2585,2589,28860-95-9,O=C(O)C(NN)(C)Cc1ccc(O)c(O)c1,Training,1,0,88,0.27902660017928366,115.81,56.83950000000002,2.9481602618515157,407.80554480729563,226.23200000000003,-0.05310000000000026
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+2587,2591,28920-43-6,O=C(OCC2c3ccccc3(c1ccccc12))Cl,Training,1,1,90,0.7557996823533961,26.3,70.92200000000003,2.0600615734642145,561.4475261916774,258.70399999999995,4.174300000000002
+2588,2592,28921-94-0,O=C1OC(C=CC)C(O)C=C1,Training,0,0,60,0.43911252968122694,46.53,39.84080000000001,2.6725495358039995,205.3827102814694,154.165,0.4050000000000001
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+2590,2594,28995-89-3,O=[N+]([O-])c2cc1cc(cc(c1c(c2)[N+](=O)[O-])[N+](=O)[O-])[N+](=O)[O-],Training,1,1,112,0.6109182515949824,172.56,70.5656,3.0309712571393645,794.865614636012,308.16200000000003,2.4726000000000017
+2591,2595,290-37-9,n1ccncc1,Training,0,0,30,0.4525571430979931,25.78,22.031999999999993,3.000000000000001,77.47078006212229,80.08999999999999,0.4765999999999999
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+2613,2617,298-02-2,O(CC)P(OCC)(=S)SCSCC,Training,0,0,80,0.37479709013917767,18.46,68.12700000000004,3.8459343998916413,155.81664443119072,260.38599999999997,3.727700000000003
+2614,2618,2980-32-7,O=C1c3c(O)cc(O)cc3(Oc2c(O)ccc(O)c12),Training,1,1,96,0.36184263009030476,111.13000000000001,66.64920000000002,2.685517223988609,877.8008533754268,260.20099999999996,1.7685999999999997
+2615,2619,298-12-4,O=CC(=O)O,Training,1,0,28,0.3292675030726765,54.370000000000005,13.6998,3.204805417886435,55.91340299823497,74.035,-0.7301
+2616,2620,298-18-0,O1CC1C2OC2,Training,1,1,34,0.41216492932960364,25.06,19.479999999999997,1.9155467020454342,53.94833690207419,86.09,-0.21599999999999997
+2617,2621,2984-50-1,O1CC1CCCCCC,Training,0,0,54,0.4087700508683697,12.53,38.499,1.7060432961664131,66.96788691072805,128.215,2.355600000000001
+2618,2622,29852-26-4,c1ccc5c(c1)cc2c4c5(ccc3cccc(cc2CCl)c34),Training,1,0,104,0.1888098175126323,0.0,97.20900000000003,2.210651866930115,1154.3480587215813,300.788,6.4760000000000035
+2619,2623,298-81-7,O=C1Oc2c(OC)c3occc3(cc2(C=C1)),Training,1,0,80,0.5863590335117103,52.58,58.80800000000002,2.596039059902241,720.5360957899312,216.192,2.5478000000000005
+2620,2624,299-11-6,n2c1ccccc1[n+](c3ccccc23)C,Training,1,1,72,0.3967534077617541,16.77,60.42500000000003,2.5979683595627105,590.1543647116672,195.245,2.2124999999999995
+2621,2625,29927-08-0,n2c1cc(c(cc1sc2N)C)C,Training,1,1,62,0.6727908954042201,38.91,53.50640000000001,2.825866007367726,392.26631033270655,178.25999999999996,2.4953400000000006
+2622,2626,29964-84-9,O=C(OCCCCCCCC(C)C)C(=C)C,Training,0,0,94,0.3359230833988581,26.3,68.31300000000005,3.157736087145381,206.78088106981613,226.35999999999996,4.102300000000004
+2623,2627,29975-16-4,n1nc2n(c1)c4ccc(cc4(C(=NC2)c3ccccc3))Cl,Training,0,0,102,0.691129049070368,43.07,82.15400000000002,1.9961465411984811,836.4931314625342,294.745,3.271700000000002
+2624,2628,299-75-2,O=S(=O)(OCC(O)C(O)COS(=O)(=O)C)C,Training,1,1,98,0.49590241519042405,127.20000000000002,53.60520000000003,4.049666013861819,356.24447258666214,278.30400000000003,-2.3393999999999986
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+2626,2630,2998-23-4,O=C(OCCCCC)C=C,Training,0,0,58,0.3327359348571791,26.3,40.681000000000004,3.033873494743956,107.82521876648651,142.19799999999998,1.9058
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+2628,2632,30039-44-2,O=C(OCc1ccc(cc1)[N+](=O)[O-])CC,Training,1,1,80,0.43196932627680157,69.44,53.18340000000003,2.5686873822106304,358.19006718030624,209.20099999999996,2.048
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+2631,2635,301-12-2,O=S(CC)CCSP(=O)(OC)OC,Training,1,0,80,0.6419752286288123,52.60000000000001,57.63290000000004,3.7437098947519436,200.81093255154832,246.28999999999996,1.8890999999999998
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+2633,2637,302-17-0,OC(O)C(Cl)(Cl)Cl,Training,1,0,44,0.4090497087455616,40.46,28.515599999999996,3.541196965079901,56.44547197387445,165.403,0.6672999999999998
+2634,2638,3022-61-5,O=C2c1c(O)cccc1C(C(=O)C)c3cccc(O)c23,Training,1,1,100,0.8322111368227759,74.6,72.17010000000002,2.4033477153666447,690.6372465421787,268.268,2.3631000000000015
+2635,2639,30235-27-9,n1cccc(c1)c2nc(N)sc2,Training,0,1,60,0.7220418511824791,51.8,49.75740000000001,2.4450102492957595,368.801815146904,177.232,1.7872999999999999
+2636,2640,3025-42-1,O=[N+]([O-])c2ccc(N=Nc1ccc(cc1)N(CC)CC)c(c2)Cl,Training,1,1,120,0.3975028260697819,71.1,92.28540000000004,2.1544749101608796,712.5202167690674,332.79100000000005,5.509800000000004
+2637,2641,3025-52-3,O=[N+]([O-])c2ccc(N=Nc1ccc(cc1)N(CC)CC)cc2,Training,1,1,114,0.43423671571422856,71.1,87.27540000000005,2.078246277348618,646.8509531428243,298.34600000000006,4.856400000000004
+2638,2642,3025-77-2,O=[N+]([O-])c3ccc(N=Nc1c(N)ccc2ccccc12)cc3,Training,1,1,108,0.3265283687172554,93.88,85.63280000000002,1.984529940076556,872.9531310009171,292.29800000000006,4.745600000000002
+2639,2643,30269-02-4,O=[N+]([O-])c1ccc2ccc3ccc(N)c4ccc1c2c34,Training,1,1,96,0.24308985444215497,69.16,81.21280000000003,2.3810541321428658,991.8945192678593,262.268,4.074400000000002
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+2641,2645,302-84-1,O=C(O)C(N)CO,Training,0,0,42,0.3942403492047702,83.55,22.697,3.3434170589539596,72.58027134782354,105.093,-1.6094
+2642,2646,3029-19-4,O=Cc1ccc2ccc3cccc4ccc1c2c34,Training,1,1,84,0.3497333879144199,17.07,75.53350000000003,2.4348318688991455,874.0516954402777,230.266,4.396500000000002
+2643,2647,3031-73-0,OOC,Training,1,1,20,0.31061534304923694,29.46,9.6378,1.6329931618554523,2.7548875021634682,48.041,0.10579999999999995
+2644,2648,3031-74-1,OOCC,Training,1,1,26,0.35368629093854076,29.46,14.254800000000001,1.9747448713915894,6.0,62.068,0.49589999999999995
+2645,2649,3032-55-1,O=[N+]([O-])OCC(C)(CO[N+](=O)[O-])CO[N+](=O)[O-],Training,0,1,98,0.3948507580314836,157.11,46.94620000000002,4.374032781357757,259.4575760265511,255.13899999999998,-0.3824000000000003
+2646,2650,303-34-4,O=C(OC2CCN1CC=C(COC(=O)C(O)(C(OC)C)C(O)(C)C)C12)C(=CC)C,Training,1,1,164,0.34566714827131406,105.53,106.04960000000005,2.0790922679526362,693.6334033463125,411.4950000000002,0.9587999999999999
+2647,2651,3034-42-2,O=[N+]([O-])c1cncn1C,Training,1,1,48,0.40304106829436803,60.96,29.86239999999999,3.076663439987336,229.4715490331534,127.103,0.32829999999999987
+2648,2652,303-45-7,O=Cc1c(O)c(O)c(c2cc(c(c(O)c12)c3c(O)c4c(C=O)c(O)c(O)c(c4(cc3C))C(C)C)C)C(C)C,Training,0,0,198,0.13123576853848415,155.51999999999998,145.30579999999978,2.274743429153193,1554.0159185858968,518.5620000000002,6.3822400000000075
+2649,2653,303-47-9,O=C1OC(C)Cc2c1c(O)c(cc2Cl)C(=O)NC(C(=O)O)Cc3ccccc3,Training,0,0,146,0.6611706059916431,112.92999999999999,100.7343,1.8938777186922464,943.4572524278772,403.81800000000015,2.5727
+2650,2654,303-98-0,O=C1C(OC)=C(OC)C(=O)C(=C1C)CC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)CCC=C(C)C,Training,0,0,350,0.05146269158447895,52.6,274.72499999999934,2.305932923242136,1844.232906471872,863.3649999999994,17.853899999999975
+2651,2655,304-20-1,n1nc(NN)c2ccccc2(c1),Training,1,1,60,0.480554166108739,63.83,47.34810000000001,2.7909670297392637,393.68492278413083,160.17999999999998,0.9154
+2652,2656,304-28-9,O=C(Nc2ccc3c1ccc(cc1Cc3(c2))NC(=O)C)C,Training,1,1,106,0.7571530455272678,58.2,83.29140000000002,1.9321298118485675,686.9504822215296,280.327,3.1746000000000016
+2653,2657,30461-65-5,O=C4c5c(O)cccc5(Oc2c4(c(O)cc1OC3OC=CC3(c12))),Training,1,0,114,0.6205866466698432,89.13000000000001,80.70160000000001,2.001461638565419,1078.0568386656842,310.261,2.703400000000001
+2654,2658,304-81-4,[O-][n+]2c3ccccc3(nc1ccccc12),Training,1,1,72,0.31329041520755835,39.83,58.20900000000003,2.5979683595627105,595.2405310388475,196.209,2.0214
+2655,2659,3048-64-4,C=CC2CC1C=CC2(C1),Training,0,0,48,0.4659588542605679,0.0,39.041000000000004,2.1861434650976657,155.42124551085624,120.19499999999996,2.3846000000000007
+2656,2660,30489-67-9,n1c(N)n(c2cc3ccccc3(cc12))C,Training,1,1,74,0.6006295308009416,43.839999999999996,62.63240000000001,2.5279983293006643,652.3207036761831,197.24099999999999,2.3087
+2657,2661,305-03-3,O=C(O)CCCc1ccc(cc1)N(CCCl)CCCl,Training,1,1,106,0.7110607782360152,40.54,80.66880000000005,2.5541826860485153,375.5372835152444,304.217,3.377900000000002
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+2659,2663,30517-66-9,O=C4c5c(O)cccc5(Oc2c4(c(O)cc1OC3OCCC3(c12))),Training,0,0,116,0.6202064501190726,89.13000000000001,81.04560000000002,1.9803563674953109,1034.8435188267151,312.2770000000001,2.5798000000000005
+2660,2664,3054-60-2,OC2COC(Nc1ccc(cc1)C)C(O)C2(O),Training,1,0,94,0.5766301170392113,81.95,62.56210000000004,2.0125673930467984,367.2733074876539,239.27100000000002,-0.1540800000000001
+2661,2665,30560-19-1,O=C(NP(=O)(OC)SC)C,Training,0,0,60,0.668589141165655,55.400000000000006,41.947200000000024,4.0741188846199865,163.8856389575664,183.16899999999998,1.24
+2662,2666,3060-89-7,O=C(Nc1ccc(cc1)Br)N(OC)C,Training,0,0,76,0.8287384573846017,41.57000000000001,57.93270000000002,2.6048709716587592,313.0929223461078,259.10299999999995,2.4742000000000006
+2663,2667,3062-57-5,O=[N+]([O-])c2ccc3[nH]c1c(cccc1[N+](=O)[O-])c3(c2),Training,1,1,94,0.5621795038812433,102.07,69.11350000000002,2.427971579292772,837.4733379661393,257.205,3.137500000000001
+2664,2668,3070-86-8,O=C(Nc2ccc(Oc1ccc(cc1)NC(=O)C)cc2)C,Training,0,1,108,0.9038493264283735,67.43,81.56540000000004,2.005140967129116,576.0765942666073,284.315,3.3957000000000015
+2665,2669,3074-00-8,O=C1c5cccc4ccc3ccc2cccc1c2c3c45,Training,0,1,92,0.36627909528524133,17.07,82.39250000000004,2.2902835564488617,976.8803726268145,254.28799999999998,4.6906000000000025
+2666,2670,30747-87-6,O=[N+]([O-])c1ccc2c(c1)c(ns2)Cl,Training,1,1,66,0.5418468066415272,56.03,51.28440000000001,2.7248123838460145,482.29731987688285,214.63299999999998,2.8579
+2667,2671,3077-85-8,O=[N+]([O-])c2ccc3[nH]c1ccccc1c3(c2),Training,1,1,78,0.49689660898295873,58.93,62.45910000000003,2.441228666577131,700.3776755816397,212.208,3.229300000000001
+2668,2672,3081-61-6,O=C(O)C(N)CCC(=O)NCC,Training,0,1,70,0.5142732688390981,92.41999999999999,43.528900000000014,3.5370599065713137,170.0344235629434,174.20000000000002,-0.6853999999999998
+2669,2673,30835-61-1,O=C3c2cc(OC)c1c4ccccc4(cc(c1c2CC3)C),Training,1,1,104,0.6141629973560317,26.3,85.39450000000004,2.2954380062080473,906.4677704705265,276.33500000000004,4.438920000000003
+2670,2674,30835-65-5,O=C3c2ccc1c4ccccc4(cc(c1c2CC3)C),Training,1,1,92,0.5361667709880622,17.07,78.84250000000003,2.252485343499163,843.0530656994204,246.30899999999994,4.430320000000003
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+2674,2678,3096-63-7,ONc1c(cccc1C)C,Training,1,1,54,0.5808157166070326,32.26,41.325200000000024,3.1694511920127173,212.44924244622518,137.18199999999996,2.10454
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+2678,2682,31120-85-1,O=C(OC(C)C)c1ccccc1(OP(=O)(OCC)NC(C)C),Training,1,0,124,0.5778859029351768,73.86,85.12570000000007,3.0495345127413187,544.4892736416222,329.333,3.7732000000000028
+2679,2683,31125-05-0,O=Nc1ccc(cc1)C(=O)C,Training,1,1,56,0.47798932055537213,46.5,41.90150000000002,3.0008866459978685,276.6484617329528,149.14899999999997,2.2871000000000006
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+2681,2685,3113-72-2,O=C(O)c1cc(ccc1[N+](=O)[O-])C,Training,1,1,68,0.5545811672294876,80.44,44.79270000000001,3.3486590713152182,372.4068180287228,181.14699999999996,1.6014199999999998
+2682,2686,311-45-5,O=[N+]([O-])c1ccc(OP(=O)(OCC)OCC)cc1,Training,1,1,100,0.4311769103145355,87.9,64.58290000000002,2.8092988239678784,436.1860559450845,275.19699999999995,3.154700000000002
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+2684,2688,3118-97-6,Oc2ccc3ccccc3(c2(N=Nc1ccc(cc1C)C)),Training,1,0,104,0.6101593506431456,44.95,85.70480000000003,2.086499155734178,837.741092357619,276.339,5.577640000000003
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+2687,2691,312304-89-5,O=NN(COC(=O)C)CCCCCl,Training,1,1,76,0.1589463178427814,58.970000000000006,49.08800000000003,3.5056644741149965,165.81664443119075,208.64499999999995,1.5093999999999999
+2688,2692,31272-21-6,O=C(c1ccccc1(F))c2c(nn(c2(N))C)C,Training,1,1,88,0.8026277627914209,60.91,62.18990000000001,2.554328826950858,589.4318316437203,233.24599999999998,1.6808200000000002
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+2690,2694,313-67-7,O=C(O)c2cc1OCOc1c3c4cccc(OC)c4(cc(c23)[N+](=O)[O-]),Training,1,1,126,0.4419555038718953,108.13000000000002,87.74270000000006,2.3353582522775107,1073.9532352833235,341.2750000000001,3.336700000000002
+2691,2695,313-80-4,n1ccc2ccc4cccc3ccc1c2c34,Training,1,1,74,0.3938070724969092,12.89,67.94100000000003,2.505955689360671,672.0164468827516,203.24399999999997,3.979000000000002
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+2693,2697,314084-63-4,Nc1c(cc(cc1CC)c2ccccc2)CC,Training,0,1,88,0.7831245265765522,26.02,75.04640000000003,2.55968583505436,475.1836701904021,225.335,4.0606000000000035
+2694,2698,31430-15-6,O=C(OC)Nc1nc2cc(ccc2([nH]1))C(=O)c3ccc(F)cc3,Training,0,0,116,0.7276819332353759,84.07999999999998,81.9539,1.9119920914556303,887.2267814529613,313.288,3.111300000000001
+2695,2699,31438-22-9,O=[N+]([O-])c2cccc1c3ccccc3([nH]c12),Training,1,1,78,0.49689660898295873,58.93,62.45910000000002,2.535467545905305,700.3776755816397,212.208,3.229300000000001
+2696,2700,314-40-9,O=C1NC(=C(C(=O)N1C(C)CC)Br)C,Training,0,0,78,0.8781961394589669,54.86,58.76170000000002,3.529081535871466,447.1056682573319,261.11899999999997,1.5785199999999997
+2697,2701,31464-26-3,N#CCCN(c2ccc(N=Nc1ccccc1)cc2)C,Training,1,0,100,0.7488617650182048,51.75,80.56000000000004,2.0160387708903116,596.6240408476585,264.332,4.451880000000004
+2698,2702,315-22-0,O=C1OC3CCN2CC=C(COC(=O)C(O)(C)C(O)(C)C1C)C23,Training,0,1,128,0.4622749072833422,96.3,79.31160000000003,1.9654078757442552,566.9177689624566,325.36100000000005,-0.3925999999999994
+2699,2703,3153-55-7,Oc1cc4c3c(c1(OC))c2ccccc2CC3N(C)CC4,Training,1,1,108,0.8712951655529809,32.7,82.87380000000005,2.0961607790987955,723.3985326278214,281.3550000000001,3.1529000000000007
+2700,2704,31551-45-8,O=C1c3cc(ccc3(c2ccc(cc12)[N+](=O)[O-]))[N+](=O)[O-],Training,1,1,98,0.5256209929890866,103.35,68.6193,2.2060943130874358,731.84367938417,270.2,2.714400000000002
+2701,2705,31555-54-1,O=C1OC(C(=C1Cl)Cl)=C(Cl)Cl,Training,1,1,60,0.6018948608921224,26.3,43.556000000000004,3.15041542083487,274.20700504797264,233.86499999999998,2.8791
+2702,2706,3160-37-0,O=C(C=Cc1ccc2OCOc2(c1))C,Training,0,0,72,0.669064970496893,35.53,52.28000000000003,2.2452664748461393,393.51915935780187,190.19799999999998,2.0175
+2703,2707,316-14-3,c1ccc2cc3c(cc2(c1))c4ccccc4(cc3C),Training,1,1,90,0.2837498834433012,0.0,83.69700000000003,2.304422514048355,916.7400111490208,242.32099999999997,5.454620000000004
+2704,2708,316-42-7,O(c1cc2c(cc1(OC))C(NCC2)CC4CC5c3cc(OC)c(OC)cc3CCN5(CC4(CC)))C,Training,0,0,190,0.6056838132410554,52.190000000000005,138.06269999999995,1.428827640262003,1053.4626672680454,480.64900000000034,4.943400000000005
+2705,2709,31647-36-6,c1ccc5c(c1)cc2c4c5(ccc3cccc(cc2C)c34),Training,1,1,98,0.23641815777600877,0.0,92.38900000000004,2.2473061361713116,1132.5000637406122,266.343,6.045620000000004
+2706,2710,316-49-4,c3ccc4cc2c(ccc1c2(cccc1C))cc4(c3),Training,1,1,90,0.2837498834433012,0.0,83.69700000000005,2.259927400012315,916.7400111490208,242.32099999999997,5.454620000000004
+2707,2711,31688-71-8,O=C(OCc3c1ccccc1c(c2ccccc23)C)C,Training,1,1,100,0.5073833916746482,26.3,81.66100000000006,2.365990789325114,745.9818834003047,264.324,4.364520000000002
+2708,2712,31698-14-3,N=C1N=C2OC3C(O)C(OC3(N2(C=C1)))CO,Training,0,0,86,0.5326902884382276,100.59000000000002,49.500300000000024,1.9860772805447264,474.06705661543674,225.20399999999998,-1.62583
+2709,2713,3173-53-3,O=C=NC1CCCCC1,Training,0,0,50,0.3867877282414881,29.43,34.994499999999995,2.3077431618204156,120.87784055857759,125.171,1.6549
+2710,2714,3173-72-6,O=C=Nc1cccc2c(N=C=O)cccc12,Training,0,1,76,0.5648001280908225,58.86,59.511000000000024,2.8520757325521386,579.2588610105929,210.19199999999995,2.774400000000001
+2711,2715,3175-89-1,OC3c5ccccc5(c1c4OCOc4(cc2c1C3(N(C)CC2))),Training,1,1,112,0.8111351015565127,41.93,82.03580000000004,1.9065287130534152,786.1420031962215,295.3380000000001,2.6583000000000006
+2712,2716,3179-47-3,O=C(OCCCCCCCCCC)C(=C)C,Training,0,0,94,0.3161269796952439,26.3,68.38300000000005,3.0969350573475625,196.91202231123458,226.35999999999993,4.246400000000004
+2713,2717,3179-90-6,O=C1c3c(O)ccc(O)c3(C(=O)c2c(ccc(NCCO)c12)NCCO),Training,1,1,136,0.3537278122749707,139.12,94.2296,2.2602122930052095,821.7354360228301,358.3500000000001,0.6815999999999998
+2714,2718,31969-03-6,Oc2ccc3ccccc3(c2(N=Nc1cccc(c1C)C)),Training,0,0,104,0.6101593506431456,44.95,85.70480000000003,2.111743296650787,837.741092357619,276.339,5.577640000000003
+2715,2719,3198-41-2,n1c3c(N)cccc3(cc2c1CCCC2),Training,1,1,76,0.660891742072791,38.91,62.797400000000025,2.306624081917049,517.1700342808027,198.2689999999999,2.695800000000001
+2716,2720,320-51-4,FC(F)(F)c1cc(N)ccc1Cl,Training,0,0,66,0.6331815080954198,26.02,40.866400000000006,3.2314250130900137,295.19322947353925,195.57100000000003,2.9410000000000007
+2717,2721,32066-79-8,N#[N+]c1ccc(cc1)C,Training,1,1,44,0.4819768655872518,28.15,35.923,3.0560383962272613,230.08821798626082,119.14699999999998,2.4796000000000005
+2718,2722,320-67-2,O=C1N=C(N=CN1C2OC(CO)C(O)C2(O))N,Training,1,0,94,0.4262474653048269,143.72000000000003,53.71380000000002,2.3196952658217853,463.4739146948157,244.207,-3.1679999999999997
+2719,2723,3208-16-0,o1cccc1CC,Training,0,0,38,0.5195790437613876,13.14,28.085999999999988,2.7626083414437685,118.73595983423269,96.129,1.842
+2720,2724,321-14-2,O=C(O)c1cc(ccc1(O))Cl,Training,0,0,58,0.6786070990602081,57.53,40.07610000000001,3.2322088703054925,295.73720227422257,172.56699999999998,1.7437999999999998
+2721,2725,32116-25-9,O=C(c1ccc([nH]1)[N+](=O)[O-])C,Training,1,1,58,0.39368322687600094,76.0,37.451600000000006,2.994170560413119,274.03096961035277,154.125,1.1255
+2722,2726,32157-71-4,O=C(c1ccc(cc1)Br)C3OC3(c2ccccc2),Training,0,0,90,0.6378624785160687,29.6,72.52850000000004,1.748522067538629,562.8072898380785,303.155,3.7719000000000023
+2723,2727,321-60-8,Fc1ccccc1c2ccccc2,Training,0,0,64,0.6172445494970527,0.0,51.83600000000003,2.5360704460016144,392.8790477621569,172.202,3.492700000000002
+2724,2728,3228-99-7,C(C(CCl)(CCl)CCl)Cl,Training,0,1,56,0.6253123565908154,0.0,45.313000000000024,3.824684203207495,51.84847143196431,209.931,2.9280000000000017
+2725,2729,32306-29-9,O=P(Oc1noc(c1)c2ccccc2)(OCC)OCC,Training,0,1,108,0.7216693645923103,70.79,73.42550000000004,2.145092887186004,573.4572684472485,297.24700000000007,3.901500000000003
+2726,2730,3237-50-1,O=C1NC(=O)C(O)(O)C(=O)N1,Training,0,1,60,0.2229068109247061,115.73000000000002,28.85,2.930240445198694,222.86697267391025,160.08499999999998,-2.9667
+2727,2731,32425-83-5,O=C3c2c4ccc1ccccc1c4(ccc2CC3),Training,1,1,86,0.532686615120052,17.07,74.10550000000003,2.231377424381633,799.1737532532246,232.28199999999995,4.121900000000003
+2728,2732,32433-28-6,O=C(Nc2ccnc1ccccc12)C,Training,0,1,70,0.741315224108568,41.99,56.046700000000016,2.58753091711869,474.1761553969986,186.214,2.1932
+2729,2733,3244-54-0,O=[N+]([O-])c2ccc3[nH]c1ccc(cc1c3(c2))[N+](=O)[O-],Training,1,1,94,0.5621795038812433,102.07,69.11350000000002,2.371822246494393,769.223337966139,257.205,3.137500000000001
+2730,2734,3244-90-4,O(CCC)P(OCCC)(OP(OCCC)(OCCC)=S)=S,Training,0,0,128,0.3869910773401839,46.150000000000006,94.62700000000007,4.902321546670488,298.53948727292124,378.43300000000005,5.158400000000005
+2731,2735,32451-61-9,O=C(N)Nc2cccc1cccnc12,Training,0,1,70,0.7133226779132285,68.01,54.949100000000016,2.58753091711869,476.2557347509718,187.202,1.7254
+2732,2736,3252-43-5,N#CC(Br)Br,Training,1,0,28,0.5433359319399053,23.79,27.255,2.939447246323328,53.1585154960715,198.845,1.62588
+2733,2737,32534-81-9,O(c1ccc(cc1Br)Br)c2cc(c(cc2Br)Br)Br,Training,0,0,94,0.3482687048868971,9.23,91.45800000000001,2.3669730660402717,597.2619082804617,564.691,7.291400000000002
+2734,2738,32588-76-4,O=C1c4c(C(=O)N1CCN2C(=O)c3c(C2(=O))c(c(c(c3Br)Br)Br)Br)c(c(c(c4Br)Br)Br)Br,Training,0,0,166,0.1800569738870534,74.76,145.21799999999993,1.6532425455289328,1115.8506931440754,951.4719999999998,7.678800000000001
+2735,2739,326-61-4,O=C(OCc1ccc2OCOc2(c1))C,Training,0,1,74,0.6687027050877427,44.760000000000005,48.035000000000025,2.086887066455094,359.1396728870035,194.18599999999995,1.4784
+2736,2740,3268-49-3,O=CCCSC,Training,0,0,36,0.3912828365702852,17.07,29.062999999999988,2.488403771876112,36.529325012980806,104.17399999999999,0.9384
+2737,2741,3268-87-9,O1c3c(Oc2c1c(c(c(c2Cl)Cl)Cl)Cl)c(c(c(c3Cl)Cl)Cl)Cl,Training,0,0,116,0.24684494980100555,18.46,93.11199999999997,2.32088843639644,697.8417983917849,459.754,8.8118
+2738,2742,32692-19-6,O=[N+]([O-])c1ccc2NCCc2(c1),Training,1,1,62,0.5058502246136939,55.17,45.29010000000002,2.4508870366286906,335.82978715700074,164.164,1.5628
+2739,2743,32740-01-5,n2c1c4ccccc4(ccc1c(c3cccc(c23)C)C),Training,1,1,96,0.3130929426158614,12.89,86.22900000000004,2.326137962039809,967.2867569201643,257.33599999999996,5.158040000000003
+2740,2744,32766-75-9,O=C(N(O)c2ccc3c1ccccc1Cc3(c2))CCCCCCCCCCCCC,Training,1,1,162,0.1792171319003645,40.540000000000006,125.03450000000008,1.3329174145040696,814.260406872429,407.5980000000004,7.681100000000007
+2741,2745,32784-82-0,O=S(=O)(OCCCNCCCOS(=O)(=O)C)C,Training,1,1,104,0.4195279789262815,98.77000000000001,63.69530000000004,3.25283021737464,350.2384663681842,289.375,-0.6913999999999987
+2742,2746,32795-84-9,c1ccc4c(c1)ccc3c4(cc2ccccc2c3Br),Training,1,1,90,0.27975744822474413,0.0,86.66000000000004,2.318193083302064,922.3919838784873,307.18999999999994,5.908700000000003
+2743,2747,327-97-9,O=C(OC1CC(O)(C(=O)O)CC(O)C1(O))C=Cc2ccc(O)c(O)c2,Training,0,0,136,0.23408527976084326,164.75,82.51880000000001,2.0588836855958705,698.8458476325025,354.3110000000001,-0.6459000000000004
+2744,2748,32828-84-5,c2cc1cccc3c1c(c2)CC(N(C)C)C3,Training,1,1,82,0.7007985178873964,3.24,68.83100000000003,2.197564371532601,487.1960315170763,211.30799999999994,2.8686000000000016
+2745,2749,3290-92-4,O=C(OCC(COC(=O)C(=C)C)(COC(=O)C(=C)C)CC)C(=C)C,Training,1,0,134,0.3461236904929484,78.9,90.04300000000003,5.106512542083464,469.6340396756941,338.4000000000001,2.7407000000000012
+2746,2750,32959-60-7,n1c(oc2ccccc12)c3ccccc3C,Training,0,0,78,0.6088199043422198,26.03,64.18200000000003,2.232723706244156,606.7853140522719,209.248,3.8032200000000023
+2747,2751,3296-90-0,OCC(CO)(CBr)CBr,Training,1,1,56,0.7336538778499481,40.46,44.19260000000003,3.824684203207495,55.84847143196431,261.941,0.7471999999999999
+2748,2752,329-71-5,O=[N+]([O-])c1ccc(c(O)c1)[N+](=O)[O-],Training,1,1,68,0.5485201907500785,106.51000000000002,41.41560000000001,3.2021054375890703,375.28740254995904,184.10699999999997,1.2086
+2749,2753,330-54-1,O=C(Nc1ccc(c(c1)Cl)Cl)N(C)C,Training,1,0,76,0.7936220369870916,32.34,59.16770000000002,2.781208374094021,352.66523279752516,233.09799999999998,3.0869000000000018
+2750,2754,33069-62-4,O=C(OC3C5C6(OC(=O)C)(COC6(CC(O)C5(C(=O)C(OC(=O)C)C4=C(C)C(OC(=O)C(O)C(NC(=O)c1ccccc1)c2ccccc2)CC3(O)C4(C)C)(C))))c7ccccc7,Training,0,0,328,0.12978619445124503,221.28999999999996,217.69009999999932,1.3874476640402011,2280.346269552865,853.918,3.735700000000004
+2751,2755,33089-36-0,O1CCOCCOCCOCCOCCOCCOCC1,Training,0,0,126,0.6293993006236126,64.61000000000001,75.73300000000006,2.004545454545455,111.52287839349825,308.37100000000004,0.1162000000000023
+2752,2756,33100-27-5,O1CCOCCOCCOCCOCC1,Training,0,0,90,0.578436159103995,46.150000000000006,54.09500000000004,2.008928571428571,72.37779644494512,220.26499999999993,0.08300000000000085
+2753,2757,3311-98-6,O=C(Nc1ncc([N+](=O)[O-])s1)NCCCl,Training,1,1,82,0.47959272024726257,97.16,56.50980000000001,2.496414495224041,369.0139094637522,250.667,1.4116
+2754,2758,331-39-5,O=C(O)C=Cc1ccc(O)c(O)c1,Training,0,0,68,0.47162133314166776,77.76,46.441400000000016,2.915115080665927,354.632376249924,180.159,1.1956
+2755,2759,33175-34-7,ONc1ccc(c(c1)Cl)Cl,Training,0,0,54,0.6476069612306075,32.26,41.87120000000001,3.0436180591142796,239.18946744189822,178.018,2.7945
+2756,2760,33203-82-6,n1c3ccc(cc3([o+]c2cc(ccc12)N(CC)CC))N(CC)CC,Training,1,1,126,0.4737543498696397,30.67,103.04400000000007,2.108630779493942,771.7764141966586,324.4480000000001,4.954500000000006
+2757,2761,33229-34-4,O=[N+]([O-])c1cc(ccc1(NCCO))N(CCO)CCO,Training,1,1,112,0.3659022624624745,119.10000000000001,75.05650000000003,3.0346742293695286,435.10101282974176,285.29999999999995,-0.21000000000000008
+2758,2762,33237-74-0,c1ccc(cc1)N(CCCN(CC)CC)C3Cc2ccccc2C3,Training,0,0,128,0.7109023456343512,6.48,103.83100000000007,1.6966368802021723,593.8768583615254,322.49600000000004,4.392300000000004
+2759,2763,3328-25-4,OOC23(C=CC1C4CCC(C(C)CCCC(C)C)C4(C)(CCC1C3(C)(CCC(O)C2))),Training,1,1,172,0.2813972815924836,49.69,121.93760000000009,1.5499423585941914,644.0194362953911,418.66200000000026,6.856800000000009
+2760,2764,33301-41-6,O=S(=O)(OC1CN(C1)C(c2ccccc2)c3ccccc3)C,Training,1,1,116,0.7947798406720921,46.61000000000001,86.01680000000006,1.800717031036949,670.5839744596865,317.41,2.436400000000001
+2761,2765,333-27-7,O=S(=O)(OC)C(F)(F)F,Training,1,1,56,0.4179078759416589,43.370000000000005,21.983799999999995,4.572693101514354,177.72476622436804,164.10399999999998,0.48240000000000005
+2762,2766,3333-52-6,N#CC(C)(C)C(C#N)(C)C,Training,0,0,54,0.5537173382009433,47.58,38.788000000000004,4.707410205372751,176.27793097483527,136.19799999999998,2.08596
+2763,2767,3333-62-8,O=C1Oc3cc(ccc3(C=C1c2ccccc2))n4nc5ccc6ccccc6(c5(n4)),Training,0,0,142,0.3747834107600744,60.92,117.849,1.5012122969117416,1614.6828748841917,389.4140000000001,5.347100000000004
+2764,2768,3333-66-2,n2c1ccccc1c(c4c2c3ccccc3c(c4C)C)Cl,Training,1,1,102,0.2940982579399464,12.89,91.23900000000003,2.389517548466925,1018.2248613404705,291.78099999999995,5.811440000000004
+2765,2769,333-41-5,n1c(OP(OCC)(OCC)=S)cc(nc1C(C)C)C,Training,0,1,108,0.7176158745437983,53.47,79.02300000000004,2.9903765648588534,458.28775961477083,304.35200000000003,3.5847200000000026
+2766,2770,33372-39-3,O=[N+]([O-])c3ccc(c2nc1ccccc1c(n2)N(CCO)CCO)s3,Training,1,1,130,0.4896364222318539,112.62,95.89000000000004,2.1488305412095476,892.7270296964859,360.39500000000015,2.0574999999999997
+2767,2771,33389-36-5,O=[N+]([O-])c3ccc(c2nc1ccccc1c(n2)NCCO)s3,Training,1,1,112,0.5541118939340449,101.18,85.08090000000004,2.1026178850826374,833.8209433745825,316.34200000000004,2.6707000000000005
+2768,2772,33399-00-7,O=P(OC(=CBr)c1ccc(cc1Cl)Cl)(OCC)OCC,Training,0,0,112,0.4205316782402748,44.760000000000005,85.30950000000003,3.0473402647740437,526.1886493139231,404.0240000000002,5.884400000000004
+2769,2773,3340-94-1,n3c1ccccc1c(c4ccc2ccccc2c34)C,Training,1,1,90,0.31760721028739625,12.89,81.49200000000005,2.318193083302064,922.3919838784873,243.309,4.849620000000003
+2770,2774,33419-42-0,O=C5OCC6C(OC1OC2COC(OC2(C(O)C1(O)))C)c3cc7OCOc7(cc3C(c4cc(OC)c(O)c(OC)c4)C56),Training,0,0,226,0.4298292584463983,160.83,138.34539999999993,1.3182370054389014,1352.5325604550394,588.5620000000004,1.3386000000000007
+2771,2775,334-22-5,N(CCCl)CCCl,Training,1,1,44,0.4566051829554821,12.03,34.3097,2.447472887876344,28.870765403276856,142.029,1.0535999999999999
+2772,2776,33424-05-4,O1CC1c4cc2ccccc2c3ccccc34,Training,1,1,82,0.44469816361662023,12.53,70.14700000000005,2.2182769487641973,710.873873443436,220.271,4.064300000000003
+2773,2777,3342-98-1,OC4c3c5ccc1ccccc1c5(cc2ccc(c(c23)C4)C),Training,1,1,106,0.35393870406765676,20.23,92.36080000000004,2.0848554859390336,1075.5665119847029,284.358,5.044120000000003
+2774,2778,3343-64-4,O=C(O)C(N)CCSCCCC,Training,0,0,72,0.5957142254508015,63.31999999999999,52.46120000000003,3.1387008363962456,130.22626787690945,191.29599999999996,1.3216999999999999
+2775,2779,33448-26-9,c2cc1cccc3c1c(c2)CC(NC)C3,Training,1,1,76,0.7404319109669695,12.03,64.20370000000003,2.2660046067679422,460.91490176882564,197.28099999999995,2.5264000000000006
+2776,2780,334-48-5,O=C(O)CCCCCCCCC,Training,0,0,72,0.5706831499634679,37.3,50.24580000000004,2.86138733944056,110.40620687739316,172.26799999999997,3.211700000000002
+2777,2781,3351-28-8,c1ccc2c(c1)ccc3c4cccc(c4(ccc23))C,Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.2938872818722986,916.7400111490208,242.32099999999997,5.454620000000004
+2778,2782,3351-30-2,c1ccc4c(c1)ccc3c4(ccc2cccc(c23)C),Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.322309365322016,916.7400111490208,242.32099999999997,5.454620000000004
+2779,2783,3351-31-3,c1ccc4c(c1)ccc3c4(ccc2ccc(cc23)C),Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.2802168469713417,916.7400111490208,242.32099999999997,5.454620000000004
+2780,2784,3351-32-4,c1ccc2c(c1)ccc3c4ccc(cc4(ccc23))C,Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.2553383038441868,916.7400111490208,242.32099999999997,5.454620000000004
+2781,2785,335-76-2,O=C(O)C(F)(F)C(F)(F)C(F)(F)C(F)(F)C(F)(F)C(F)(F)C(F)(F)C(F)(F)C(F)(F)F,Training,0,0,186,0.42166913720490123,37.3,53.26679999999999,6.947593504737034,700.9672783863867,514.078,5.715700000000002
+2782,2786,33611-88-0,O=[N+]([O-])c4cc2cccc3c1ccccc1c(c23)c4[N+](=O)[O-],Training,1,1,106,0.4067617049069634,86.28,81.68680000000003,2.2969063324710137,994.8475196627456,292.25,4.303600000000002
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+2784,2788,336629-39-1,O=C(Nc1ccc(cc1)[N+](=O)[O-])C(=NNc2cc(OC)c(cc2(OCCC))c3cc(OCCC)c(cc3(OC))NN=C(C(=O)Nc4ccc(cc4)[N+](=O)[O-])C(=O)C)C(=O)C,Training,1,0,314,0.029287217904349284,264.32,223.4835999999995,1.7191185105465516,2165.202877601358,826.8200000000002,6.756000000000007
+2785,2789,3366-61-8,O=C(Nc1ccc(cc1)c2ccc(N)cc2)C,Training,1,1,86,0.7734530045083772,55.120000000000005,70.59410000000003,2.2272486529018245,514.9234028495391,226.27899999999997,2.8942000000000005
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+2787,2791,33685-60-8,O=[N+]([O-])c3c1ccccc1c(c2ccccc23)[N+](=O)[O-],Training,0,1,98,0.4014238921067948,86.28,74.76280000000003,2.6915389747944456,744.556590099838,268.228,3.809400000000003
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+2789,2793,33704-61-9,O=C1C2=C(CCC1)C(C)(C)C(C)C2(C)C,Training,0,0,84,0.5898325536516168,17.07,62.61000000000005,2.596666247526767,344.35020121146897,206.32899999999998,3.738100000000003
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+2791,2795,3375-84-6,O=C1OC(C)CN1CC(O)C,Training,0,1,64,0.6261442081694899,49.769999999999996,39.1968,2.406038098057098,157.76467590036683,159.185,0.20790000000000003
+2792,2796,33804-48-7,O=C(N(c2ccc(N=Nc1ccc(cc1)N(C)C)cc2)C)C,Training,1,1,114,0.7956619266479069,48.27,90.47100000000005,2.08047976785174,660.0632227181491,296.374,4.150700000000003
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+2802,2806,3397-62-4,n1c(nc(nc1N)Cl)N,Training,0,0,48,0.5226778091958509,90.71,33.6618,3.165670309917317,172.96531218488838,145.55300000000003,-0.31060000000000015
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+2807,2811,3414-62-8,ONc3ncnc1c3(ncn1C2OC(CO)C(O)C2(O)),Training,1,1,108,0.41318618223827663,145.78000000000003,63.74160000000003,2.031040564897432,619.1041595594359,283.244,-1.7611000000000003
+2808,2812,3416-21-5,O3C4c6ccccc6(c2cc1ccc(c5c1c(c2C34)CC5)C),Training,1,1,106,0.5268132000654355,12.53,88.09600000000005,1.795976259707734,982.8539662822283,284.358,5.039820000000003
+2809,2813,341-69-5,O(CCN(C)C)C(c1ccccc1)c2ccccc2C,Training,0,0,106,0.7932087270574181,12.47,83.97000000000006,2.228710246066691,521.9512484609888,269.38800000000003,3.662620000000003
+2810,2814,3420-97-1,O=Nc1ccc(OCC)cc1,Training,1,1,58,0.6222318601118172,38.66,43.066000000000024,2.738600183558637,230.35230342705088,151.165,2.4832
+2811,2815,34237-98-4,Nc1ccc(cc1Br)c2ccc(N)c(c2)Br,Training,1,1,82,0.7688029775523931,52.04,76.1028,2.5020803743746223,489.037124074059,342.034,4.043000000000001
+2812,2816,34244-14-9,c1cc2ccc3ccc(c4ccc(c1)c2c34)Cl,Training,1,1,80,0.36652505176063144,0.0,75.15600000000002,2.4832549054106994,829.9816720069383,236.70099999999996,5.237400000000003
+2813,2817,34250-70-9,O=C(Nc1c2ccccc2(ns1))C,Training,1,0,66,0.7525624649902932,41.99,53.923700000000025,2.5139618271787234,449.56635705517834,192.24299999999997,2.2547000000000006
+2814,2818,34256-82-1,O=C(N(c1c(cccc1CC)C)COCC)CCl,Training,0,1,100,0.5865813805439714,29.540000000000003,75.25600000000004,3.1439293404994157,406.78050687332427,269.77199999999993,3.1232200000000017
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+2816,2820,34331-95-8,c1ccc3c(c1)c(c2ccccc2c3CBr)C,Training,1,1,84,0.42577984609768493,0.0,78.82200000000005,2.631771409903851,641.2790663039684,285.18399999999997,5.196320000000003
+2817,2821,343-94-2,NCCc2c[nH]c1ccccc12,Training,0,0,62,0.6890236514433123,41.81,51.05710000000002,2.548405447239308,375.97395690943733,160.21999999999997,1.6691
+2818,2822,344-07-0,Fc1c(F)c(F)c(c(F)c1(F))Cl,Training,0,0,66,0.3446243756972763,0.0,31.242000000000004,3.6035674514745475,230.20322477240757,202.509,3.0355
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+2821,2825,34430-24-5,O=[N+]([O-])[C-]CCC,Training,0,0,41,0.23104956125855938,43.14,25.14539999999999,2.8219389370591843,62.710134480364864,101.105,1.1019899999999998
+2822,2826,34430-26-7,O=[N+]([O-])[C-]CCCC,Training,0,0,47,0.18301878017815745,43.14,29.76239999999999,2.8223545542480317,72.82892142331043,115.132,1.49209
+2823,2827,34522-72-0,Fc1cc(F)c2cccnc2(c1),Training,1,1,60,0.5840485195000186,12.89,41.65900000000001,2.8920650451735157,425.7980911891212,165.14199999999997,2.513
+2824,2828,34549-30-9,OCC(CO)(CCBr)CCBr,Training,1,1,68,0.7282738170395255,40.46,53.426600000000036,3.9578420903496463,86.4413633679148,289.99499999999995,1.5274
+2825,2829,345667-01-8,ONc1ccc(cc1C(C)(C)C)c2ccccc2,Training,1,1,94,0.7611083250527281,32.26,75.98720000000003,2.5346560826092195,526.5383784787243,241.334,4.452200000000003
+2826,2830,345667-02-9,ONc1ccc(cc1)c2ccc(cc2)C(C)(C)C,Training,1,1,94,0.7611083250527281,32.26,75.98720000000003,2.2822252424614575,506.28837847872444,241.33399999999997,4.452200000000003
+2827,2831,345667-60-9,O=[N+]([O-])c2ccc(C=Cc1ccc(cc1)CC)cc2,Training,1,1,96,0.4621795244010657,43.14,77.84440000000004,2.103648778709698,583.1509276194483,253.301,4.327600000000003
+2828,2832,34592-47-7,O=C(O)C1NCSC1,Training,0,0,46,0.516853152557854,49.33,31.884499999999996,2.34993673877678,100.2114326716684,133.172,-0.26649999999999996
+2829,2833,34627-78-6,O=C(OC(C=C)c1ccc2OCOc2(c1))C,Training,1,0,84,0.5783182171548034,44.760000000000005,57.269000000000034,2.248142138427544,425.02697890859474,220.22399999999996,2.2055
+2830,2834,3468-63-1,O=[N+]([O-])c3ccc(N=Nc1c(O)ccc2ccccc12)c(c3)[N+](=O)[O-],Training,1,1,124,0.41524910882163574,131.23000000000002,89.53960000000004,2.102755418826355,1032.208852862142,338.2790000000001,4.777200000000002
+2831,2835,34798-80-6,O=C(C)C2(c1ccccc1)(CCNCC2),Training,0,0,80,0.7950256489416386,29.1,60.90470000000004,2.3807014689747916,338.8134025296912,203.28499999999994,1.8967999999999998
+2832,2836,34801-16-6,O=[N+]([O-])c2ccc(c1nc(N)sc1)s2,Training,1,1,72,0.6302790130432874,82.05,56.49380000000001,2.3789367851448926,476.74321621577474,227.27,2.362
+2833,2837,34834-67-8,O=C2N(C)C(c1cnccc1)CC2(O),Training,0,0,74,0.6979648622782105,53.43000000000001,50.371800000000036,2.2557833873318645,339.2350518659593,192.218,0.34569999999999995
+2834,2838,34866-46-1,O=C(N)Nc1cc(ccc1(O))C(O)CNC(C)(C)C,Training,0,0,106,0.5298721770697152,107.61000000000001,74.02840000000003,2.8008085285565527,454.93693078110016,267.329,1.3043000000000002
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+2836,2840,35001-52-6,O=C(Nc1cc(ccc1(OCC))C(C)(C)C)C(=O)Nc2ccccc2CC,Training,0,0,144,0.7624962830474821,67.42999999999999,109.39040000000004,2.211984613614189,822.547869747465,368.47700000000003,4.522400000000004
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+2854,2858,3531-19-9,O=[N+]([O-])c1cc(c(N)c(c1)Cl)[N+](=O)[O-],Training,1,1,74,0.46048765977830153,112.30000000000001,49.173199999999994,3.4275044779343173,419.7827981926746,217.568,1.7386
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+2856,2860,354-33-6,FC(F)C(F)(F)F,Training,0,0,44,0.4274299240598743,0.0,12.059000000000001,3.541196965079901,51.5907190016011,120.02000000000001,1.8137999999999999
+2857,2861,3544-23-8,N(=Nc1ccc(N)c(OC)c1)c2ccccc2,Training,1,1,86,0.6416510035182101,59.97,68.02440000000001,2.2174679536859547,523.4427135502981,227.26700000000002,3.692800000000001
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+2866,2870,357204-48-9,O=C(ON(OCc1ccccc1)C(=O)c2ccccc2)c3cccc(c3)[N+](=O)[O-],Training,1,1,146,0.4653570168789269,98.97999999999999,102.35440000000006,1.7986302282842264,1007.949496646449,392.36700000000013,3.940800000000004
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+2873,2877,35945-34-7,N#Cc2cc(ccc2(N=Nc1ccc(cc1)N(CC)CC))[N+](=O)[O-],Training,1,1,122,0.4360029440353431,94.89,91.99040000000007,2.2192149677944903,789.6184677998755,323.3560000000001,4.728080000000004
+2874,2878,3602-55-9,O=C1C=CC(=O)C(=C1)C(C)(C)C,Training,1,0,64,0.5101777780888513,34.14,46.69200000000002,3.049827077200848,287.45066529943955,164.20399999999998,1.6668999999999998
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+2877,2881,36097-31-1,O=C(Nc1ccccc1)N(C)CCO,Training,0,0,76,0.7577880173853148,52.57000000000001,55.17650000000003,2.488276459712176,287.4332893900388,194.23399999999992,1.1426
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+2879,2883,36133-88-7,O=C(NCc1nc(no1)c2oc(cc2)[N+](=O)[O-])C,Training,1,1,94,0.6317245327862523,124.30000000000001,56.17510000000001,2.1296482633319536,587.302241922186,252.186,0.8738999999999995
+2880,2884,36164-42-8,O=C(Nc1ccc2cccnc2(c1))C,Training,1,0,70,0.741315224108568,41.99,56.04670000000002,2.4574956097268665,479.42615539699864,186.21399999999997,2.1932
+2881,2885,36167-69-8,n2c1ccc(nc1c(NCCCNCCCl)c3ccc(cc23)Cl)OC,Training,1,1,132,0.3510062475254667,59.07000000000001,105.30240000000002,1.950397809088363,872.4388476883603,379.2910000000001,4.075400000000002
+2882,2886,36239-01-7,O=C(OCN([N+](=O)[O-])C)C,Training,1,1,58,0.23611340867153066,72.67999999999999,31.39039999999999,3.490729660390813,146.1930175513852,148.118,-0.36949999999999994
+2883,2887,3626-29-7,O=C(O)c6cc(N=Nc1ccc(cc1)c5ccc(N=Nc3ccc(N=Nc2ccc(O)c(c2)C(=O)O)c4cc(ccc34)S(=O)(=O)O)cc5)ccc6(O),Training,1,1,258,0.06674593343919066,243.58999999999995,188.30079999999978,1.2194209814042476,2571.8640387654973,716.6880000000004,9.807299999999996
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+2885,2889,362-74-3,O=C(OC2C(OC1COP(=O)(O)OC12)n4cnc3c(ncnc34)NC(=O)CCC)CCC,Training,0,0,174,0.4477364154219202,163.98999999999998,108.20900000000005,1.6778534072247129,1061.164564428972,469.3910000000003,1.6899999999999993
+2886,2890,363-03-1,O=C1C=CC(=O)C(=C1)c2ccccc2,Training,0,1,68,0.6232375323128592,34.14,53.57300000000002,2.4463425669148093,438.6493505372241,184.19400000000002,1.778
+2887,2891,363-49-5,O=C(Nc2ccc3c1ccc(O)cc1Cc3(c2))C,Training,1,0,90,0.685593258182944,49.33,70.65250000000003,2.0320603277172054,646.9370156452684,239.27399999999997,2.921800000000001
+2888,2892,364-74-9,O=[N+]([O-])c1cc(F)ccc1(F),Training,1,1,58,0.46331559245773185,43.14,33.01240000000001,3.232208870305491,300.6337992264623,159.09099999999998,1.873
+2889,2893,3648-20-2,O=C(OCCCCCCCCCCC)c1ccccc1(C(=O)OCCCCCCCCCCC),Training,0,0,194,0.12416155836458759,52.60000000000001,141.46099999999993,2.192177577970452,585.4474294249493,474.7260000000005,9.061800000000002
+2890,2894,36504-65-1,O2C3C=Cc1c4ccc6cccc5ccc(cc1C23)c4c56,Training,1,1,98,0.3209377030611985,12.53,86.79400000000005,1.9293448697935045,1057.7529486519609,268.31500000000005,5.050700000000003
+2891,2895,36504-66-2,O5C6C=Cc4cc1ccc2cccc3ccc(c1c23)c4C56,Training,1,1,98,0.3209377030611985,12.53,86.79400000000004,1.9411204898846355,1057.7529486519607,268.315,5.050700000000003
+2892,2896,36504-67-3,O5C6c4cc1ccc2cccc3ccc(c1c23)c4CCC56,Training,1,1,100,0.32446042310378925,12.53,86.08100000000005,1.8962427345633022,1014.476941776831,270.33099999999996,4.970100000000003
+2893,2897,36504-68-4,O2C3c1c4ccc6cccc5ccc(cc1CCC23)c4c56,Training,1,1,100,0.32446042310378925,12.53,86.08100000000005,1.911866915067656,1014.476941776831,270.33099999999996,4.970100000000003
+2894,2898,36508-80-2,O=C2N(C)C(c1ccc[n+]([O-])c1)CC2,Training,0,0,74,0.4832687844600109,47.25,50.147000000000034,2.2753657261659144,364.89456038916694,192.21799999999993,0.6132999999999998
+2895,2899,36519-91-2,O1CC1Cc2ccc(cc2)Cl,Training,1,1,58,0.6177046422698095,12.53,44.89600000000002,2.0569493532450323,238.24457522403964,168.623,2.2813000000000008
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+2897,2901,36712-34-2,O=[N+]([O-])c1ccc(cc1)c2ccc(cc2[N+](=O)[O-])[N+](=O)[O-],Training,1,1,106,0.6275067780099787,129.42000000000002,71.84120000000001,2.544803976035857,741.1580255098045,289.20300000000003,3.0782000000000016
+2898,2902,36712-35-3,O=[N+]([O-])c2ccc(c1ccccc1[N+](=O)[O-])c(c2)[N+](=O)[O-],Training,1,1,106,0.6275067780099787,129.42000000000002,71.84120000000001,2.724955968119385,758.4080255098044,289.20300000000003,3.0782000000000016
+2899,2903,3671-71-4,O=C(c1ccccc1)N(O)c3ccc4c2ccccc2Cc4(c3),Training,1,1,112,0.4429330952858189,40.540000000000006,89.72200000000002,1.6700788299439981,887.1533399926374,301.3450000000001,4.293800000000003
+2900,2904,3671-78-1,O=C(Nc2ccc3c1ccccc1Cc3(c2))c4ccccc4,Training,1,1,106,0.5765732171262522,29.1,89.07920000000003,1.6126210668149272,852.5910284338705,285.346,4.510100000000002
+2901,2905,367-25-9,Fc1ccc(N)c(F)c1,Training,1,1,48,0.5281563260400823,26.02,30.770400000000002,3.1716780304409156,222.29788705001033,129.10900000000004,1.5470000000000002
+2902,2906,3675-13-6,O=CC=CC=O,Training,1,1,32,0.34670800328788237,34.14,21.267999999999994,3.1730886052733203,63.61727061434749,84.074,-0.0596000000000001
+2903,2907,36791-04-5,O=C(N)c1ncn(n1)C2OC(CO)C(O)C2(O),Training,0,1,94,0.44284203167437103,143.72000000000003,51.549300000000024,2.1949092649276896,421.8029666398912,244.20700000000002,-3.0114999999999994
+2904,2908,3682-19-7,O=C1NNC(=O)c2cc(ccc12)[N+](=O)[O-],Training,1,1,76,0.5109297460194259,108.86000000000001,51.843799999999995,2.937217082742359,654.7197482526674,207.14499999999998,0.12459999999999949
+2905,2909,36840-85-4,O=C(OCCCCCOC(=O)C=C)C=C,Training,0,0,84,0.34828591396576025,52.6,56.163000000000025,3.179545418264533,208.74242061785375,212.24499999999998,1.6151
+2906,2910,36848-41-6,O=[N+]([O-])c2cccc1nc3c(nc12)cccc3[N+](=O)[O-],Training,0,1,98,0.4015305561084459,112.06,70.35280000000003,2.459544552531063,804.3400089999907,270.204,2.5994
+2907,2911,3688-53-7,O=C(N)C(=Cc1oc(cc1)[N+](=O)[O-])c2occc2,Training,1,1,92,0.5032004884930001,112.51,61.13580000000001,2.387729946381407,609.1769101426211,248.194,1.8067
+2908,2912,3688-79-7,O=C2c1ccccc1c4ccc(OC)c3cccc2c34,Training,1,1,96,0.5156167523496115,26.3,79.36850000000003,2.2330339617055226,862.4212630678671,260.292,4.059800000000002
+2909,2913,3689-24-5,O(CC)P(OCC)(OP(OCC)(OCC)=S)=S,Training,1,0,104,0.5694547378804272,46.150000000000006,76.15900000000005,4.786871873258736,251.64012554421817,322.32499999999993,3.5980000000000025
+2910,2914,3694-52-8,O=[N+]([O-])c1cccc(N)c1(N),Training,1,1,58,0.35337020873087255,95.17999999999999,41.9212,3.2735808215375433,297.8789117242989,153.141,0.7592000000000001
+2911,2915,3695-86-1,N#CC(=Cc1occc1)C(=O)OC,Training,0,0,66,0.38839254921154426,63.230000000000004,44.314000000000014,2.9131640243275507,356.71157507857816,177.15899999999996,1.3595799999999998
+2912,2916,3697-24-3,c1ccc2c(c1)ccc3c4ccccc4(cc(c23)C),Training,1,1,90,0.3593465920364741,0.0,83.69700000000005,2.3547447512611055,916.7400111490208,242.32099999999997,5.454620000000004
+2913,2917,3697-30-1,c1ccc4c(c1)ccc3c4(cc2ccccc2c3CC),Training,1,0,96,0.30213405224171713,0.0,88.33800000000005,2.300527217114131,932.2283742957517,256.34799999999996,5.708600000000004
+2914,2918,371-40-4,Fc1ccc(N)cc1,Training,1,1,42,0.5030676848790229,26.02,30.8124,3.0324555320336755,147.38833891467198,111.119,1.4079000000000002
+2915,2919,37151-16-9,O=[N+]([O-])c1ccc(cc1)c2nc(N)c3ncn(c3(n2))C4OC(CO)C(O)C4(O),Training,1,1,146,0.33851572984010814,182.67999999999998,94.8352,1.7771745750970078,1038.0307767774661,388.3400000000001,-0.4047999999999998
+2916,2920,3717-88-2,O=C(OCCN1CCCCC1)c2cccc3C(=O)C(=C(Oc23)c4ccccc4)C,Training,0,0,150,0.6030824294043329,59.75,113.23050000000002,1.6279871806745367,1065.4259886007674,391.46700000000016,4.411120000000004
+2917,2921,3722-54-1,O=C1c3cc(OC)ccc3(Oc2cc(OC)cc(OC)c12),Training,1,1,108,0.6927274118934313,57.900000000000006,79.64600000000004,2.468160708295535,879.0896348662403,286.283,2.9720000000000013
+2918,2922,372-47-4,Fc1cnccc1,Training,0,0,36,0.47397196118629864,12.89,24.194999999999997,3.0214653097240864,138.00750422530467,97.09199999999997,1.2207000000000001
+2919,2923,372-48-5,Fc1ncccc1,Training,1,0,36,0.443381981599025,12.89,24.194999999999997,3.0214653097240864,138.00750422530467,97.09199999999998,1.2207000000000001
+2920,2924,3731-39-3,N(=Nc1ccccc1C)c2ccc(cc2)N(C)C,Training,0,1,92,0.7257720205006495,27.96,76.12400000000004,2.166546894519141,541.9201015887005,239.322,4.476420000000004
+2921,2925,37350-58-6,OC(COc1ccc(cc1)CCOC)CNC(C)C,Training,0,0,108,0.7135696186852984,50.72,76.66250000000005,2.2856958192566497,337.7488527229999,267.36899999999997,1.6131999999999997
+2922,2926,3736-59-2,O=Cc1c(O)cc2C(=O)c3ccccc3(C(=O)c2(c1(O))),Training,0,1,98,0.6550583668206563,91.67,68.46610000000001,2.395674016069848,789.0911492837129,268.22399999999993,1.6857000000000002
+2923,2927,3740-52-1,O=C(O)Cc1ccccc1[N+](=O)[O-],Training,1,1,68,0.5611140460569849,80.44,44.436200000000014,3.0435273546341013,347.7521927396972,181.14699999999996,1.2219
+2924,2928,3741-15-9,O=[N+]([O-])c2ccnc1ccccc12,Training,1,1,64,0.49121081405272493,56.03,48.39740000000002,2.8309756583676706,462.6262845243794,174.159,2.143
+2925,2929,37515-51-8,Oc1cc3c4ccccc4(ccc3(c2ccccc12)),Training,1,1,90,0.4382001128928585,20.23,80.62480000000005,2.3371227357502993,922.391983878487,244.29299999999998,4.8518000000000026
+2926,2930,37574-47-3,O4C5c3cccc2ccc1c6ccccc6(cc(c1c23)C45),Training,1,1,98,0.3123610476679649,12.53,85.52700000000003,2.002786888436936,1077.2526737358062,268.31499999999994,5.272200000000003
+2927,2931,37597-20-9,O=NN2Cc1cc(OC)c(OC)cc1CC2,Training,1,1,86,0.7308666729976836,51.13000000000001,59.455000000000034,2.3731666829156373,406.46130294683195,222.24399999999994,1.7433
+2928,2932,3764-01-0,n1c(nc(cc1Cl)Cl)Cl,Training,0,1,48,0.4559778282498503,25.78,37.062000000000005,3.165670309917317,174.5749526593252,183.42499999999998,2.4368
+2929,2933,3778-73-2,O=P1(OCCCN1(CCCl))(NCCCl),Training,1,1,84,0.6057206690801091,41.57,59.19120000000003,2.545008652689994,215.86647567444427,261.089,1.884
+2930,2934,3778-76-5,O=C(OCC)NNc1nncc2ccccc12,Training,1,1,88,0.7875741856184144,76.14,63.318400000000025,2.15722700748329,524.3652871830817,232.24300000000002,1.7027999999999996
+2931,2935,37797-31-2,O=C(OCc2ccc(N=Nc1ccc(cc1)COC(=O)C)cc2)C,Training,1,1,124,0.5877217601311469,77.32,88.00000000000004,1.9222324832481656,658.1889096401045,326.35200000000003,4.228200000000003
+2932,2936,37841-91-1,O=CC2=CC1CC(C)(C)CC1C3(C)(CC23(C=O)),Training,1,0,92,0.6859877395779812,34.14,65.36300000000004,2.0696733857763654,434.202773745811,232.32299999999995,2.7730000000000015
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+3012,3016,40321-98-0,O=C(O)c1ccccc1(C(=O)OCC(CC)CCC(=O)C),Training,0,0,114,0.7449747417821954,80.66999999999999,77.37980000000003,2.6448891983174247,521.1535503309102,292.33099999999996,2.937000000000001
+3013,3017,40321-99-1,O=C(O)c1ccccc1(C(=O)OCC(CC)CCC(O)C),Training,0,0,116,0.720163254037412,83.83,78.37960000000004,2.6254170180123126,481.3106093186474,294.3469999999999,2.7288000000000014
+3014,3018,40568-90-9,c1ccc2c(c1)cc3ccc4ccc(c5ccc2c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000005,2.2149901622360453,1132.5000637406122,266.34299999999996,6.045620000000004
+3015,3019,40580-89-0,O=NN1CCCCCCCCCCCC1,Training,1,1,88,0.6177251057840955,32.67,63.53800000000005,2.202270189577049,147.70110897739715,212.33699999999993,3.884400000000003
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+3017,3021,406-90-6,FC(F)(F)COC=C,Training,1,0,48,0.5115206773772702,9.23,22.203999999999994,3.239280745266341,75.84283310353014,126.077,1.7087999999999999
+3018,3022,4074-88-8,O=C(OCCOCCOC(=O)C=C)C=C,Training,0,0,84,0.33352608204515666,61.830000000000005,53.13100000000002,3.179545418264533,209.96724699955357,214.21699999999998,0.46140000000000003
+3019,3023,4075-79-0,O=C(Nc1ccc(cc1)c2ccccc2)C,Training,1,1,80,0.8107896420472547,29.1,66.18170000000003,2.2286771259481672,473.84834508395556,211.26399999999998,3.312000000000001
+3020,3024,4080-31-3,C(=CCl)C[N+]23(CN1CN(CN(C1)C2)C3),Training,1,1,78,0.6118376030598358,9.72,54.83940000000003,1.8009625314016358,230.2533564975087,215.70799999999997,0.24750000000000005
+3021,3025,40809-41-4,O=C(O)c1ccccc1(C(=O)OCC(CC)CCCC(=O)O),Training,0,0,120,0.6802171046843025,100.89999999999999,78.95160000000004,2.5725838033408888,537.1924980458598,308.33,2.822700000000001
+3022,3026,4081-23-6,O=P3(Oc1ccccc1)(Oc2ccccc2CO3),Training,1,0,92,0.7723513300471464,44.760000000000005,66.53550000000003,1.840599454716951,596.9500562921345,262.20099999999996,3.782700000000002
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+3024,3028,4097-53-4,O=[N+]([O-])c1cc(cc(c1(O))[N+](=O)[O-])c2ccccc2,Training,1,0,96,0.6739654421543468,106.51000000000002,66.85160000000002,2.701779007958392,619.4193606605909,260.205,2.8756000000000013
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+3026,3030,41044-12-6,O=C1Oc4cc(ccc4(C=C1c3nc2ccccc2n3C))N(CC)CC,Training,0,0,132,0.5194357369616716,51.27,105.75300000000006,1.8838553846761381,1153.0583636570266,347.4180000000001,4.192900000000003
+3027,3031,4106-66-5,o2c1ccccc1c3ccc(N)cc23,Training,1,1,68,0.5435062048857787,39.16,58.13240000000002,2.566841134269145,609.8208026305191,183.20999999999998,3.1682000000000015
+3028,3032,41069-00-5,O=C(c1ccc(cc1)[N+](=O)[O-])C3OC3(c2ccccc2),Training,1,1,100,0.3700172548600079,72.74,71.48290000000003,1.7321537992578662,651.3335479985868,269.256,2.917600000000001
+3029,3033,41093-60-1,O=C(O)C6(C)(CCCC3(C)(C6(CCC45(CC(=C)C(OC2OC(CO)C(O)C(O)C2(OC1OC(CO)C(O)C(O)C1(O)))(CCC34)C5)))),Training,0,0,256,0.13360437536739223,215.82999999999998,154.1723999999999,1.2633802319950873,1150.0998412766792,642.7390000000001,-0.19659999999999744
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+3031,3035,41267-76-9,O=C4Oc1c(cc3c2c1CCCN2CCC3)C(=C4)C,Training,1,0,98,0.6786752537711285,33.45,76.07600000000004,2.14843218216759,727.5868447946721,255.3169999999999,2.8002200000000013
+3032,3036,4130-42-1,Oc1c(cc(cc1C(C)(C)C)CC)C(C)(C)C,Training,0,0,96,0.7555008014361783,20.23,74.88480000000006,3.532746224395205,367.5089597076869,234.38299999999995,4.549600000000004
+3033,3037,41340-19-6,O=C(O)CC2(OCCc1c3cccc(c3([nH]c12))C)CC,Training,0,0,106,0.9027520317032155,62.32,76.91350000000003,2.2419032847848714,673.656976043899,273.33200000000005,3.1290200000000015
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+3035,3039,41340-36-7,OCCc2c[nH]c1c2(cccc1CC),Training,0,0,74,0.7630091684568289,36.019999999999996,58.46650000000003,2.5728492707436605,430.8143917393495,189.25799999999998,2.2651000000000003
+3036,3040,41372-08-1,O=C(O)C(N)(C)Cc1ccc(O)c(O)c1,Training,0,1,82,0.5430485662212738,103.78,53.70380000000002,2.905062365401662,387.0088201517134,211.217,0.44229999999999997
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+3038,3042,4164-28-7,O=[N+]([O-])N(C)C,Training,1,1,36,0.32891720919294704,46.38,20.681399999999996,3.2575861612334887,60.568425030288566,90.082,-0.2603000000000001
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+3040,3044,4176-53-8,Nc3cccc2c3(ccc1ccccc12),Training,1,1,72,0.42835853156085796,26.02,65.86640000000003,2.604862793652033,640.957112138695,193.249,3.5752000000000015
+3041,3045,41830-80-2,N=C2C=C1Oc4cc(N)ccc4(N=C1c3ccccc23),Training,1,1,96,0.28985384155839844,75.9,78.40410000000003,2.252352199223143,987.7199343023485,261.28400000000005,3.147470000000001
+3042,3046,41840-28-2,O=C(OC(C)(C)C)Sc1nc(cc(n1)C)C,Training,0,0,88,0.4286273099349934,52.08,63.59700000000003,2.6985289284088463,379.21130294683195,240.32799999999997,3.1206400000000016
+3043,3047,4189-44-0,O=S(=O)=C(N)N,Training,1,0,36,0.3469371810393848,86.17999999999999,22.301600000000008,4.577015932104095,142.38689879982147,108.12200000000001,-2.1296999999999997
+3044,3048,41934-47-8,O=C2Oc1cc(ccc1C(=C2)C(F)(F)F)N(CC)CC,Training,0,0,108,0.8069342762025506,33.45,71.04700000000003,2.6816981388804457,672.1538432415462,285.265,3.658000000000002
+3045,3049,4196-87-6,O=C(OCC(C)(COC(=O)c1ccccc1)COC(=O)c2ccccc2)c3ccccc3,Training,0,0,164,0.3642436595819625,78.9,118.28050000000002,1.659158369807619,896.9837198543373,432.47200000000015,4.563700000000004
+3046,3050,42011-48-3,O=C(Nc1nc(cs1)c2oc(cc2)[N+](=O)[O-])C(F)(F)F,Training,1,1,106,0.6941317680961265,98.27000000000001,61.15509999999999,2.160895353103964,663.4420486944024,307.20899999999995,2.8121
+3047,3051,420-12-2,C1CS1,Training,1,0,18,0.3713348592881099,0.0,17.325,2.25,7.509775004326937,60.120999999999995,0.7332000000000001
+3048,3052,42017-89-0,O=C(O)C(Oc1ccc(cc1)C(=O)c2ccc(cc2)Cl)(C)C,Training,0,0,114,0.8513366731464941,63.6,83.66930000000005,2.1649159842212513,687.6038065906843,318.7560000000001,3.8130000000000024
+3049,3053,42028-27-3,O=C3c2cc(c1c4ccccc4(ccc1c2CC3))CC,Training,1,1,98,0.5802939290928683,17.07,83.48350000000005,2.243741937584163,858.394048751053,260.33599999999996,4.684300000000003
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+3052,3056,4213-45-0,n2c1ccc(OC)cc1c(NC(C)CCCN(CCCl)CCCl)c3ccc(cc23)Cl,Training,1,1,162,0.26048904432253056,37.39,131.00969999999998,1.8331745309945562,976.7176826826178,468.8560000000002,6.410200000000005
+3053,3057,42135-22-8,O=C2c1ccccc1c3cc(ccc23)[N+](=O)[O-],Training,1,1,82,0.47223352411865877,60.209999999999994,61.96490000000001,2.3060677186103664,661.4641928515115,225.20299999999997,2.8062000000000014
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+3064,3068,42471-28-3,O=NN(C(=O)NCc1cnc(nc1(N))C)CCCl,Training,1,1,98,0.4674057392137994,113.57,66.63810000000001,2.5859259492175055,441.0660789259025,272.6959999999999,0.79902
+3065,3069,42509-80-8,n1c(nn(c1Cl)C(C)C)OP(OCC)(OCC)=S,Training,1,0,104,0.7205332551239114,58.400000000000006,73.58200000000004,2.8750624593190346,430.6923928886501,313.747,3.1887000000000016
+3066,3070,4251-89-2,n3c1ccccc1c(NCCCN(CC)CCCl)c4ccc2ccccc2c34,Training,1,1,144,0.17515620549492486,28.160000000000004,122.69570000000003,1.696610238872509,1093.0194075555046,391.946,5.903900000000005
+3067,3071,42522-72-5,O=S5(=O)(OC2(c3cc(c(O)c(c3(Oc1c2(cc(c(O)c1Br)Br)))Br)Br)c4ccccc45),Training,1,0,154,0.27191651021658925,93.06000000000002,121.68239999999996,2.0206220615298705,1323.0025047370834,683.9499999999999,6.264300000000003
+3068,3072,42576-02-3,O=C(OC)c2cc(Oc1ccc(cc1Cl)Cl)ccc2[N+](=O)[O-],Training,1,1,114,0.46494316098711624,78.67,80.97190000000005,2.3990201584291246,748.008210141674,342.13400000000007,4.480500000000002
+3069,3073,42579-28-2,O=NN1C(=O)NC(=O)C1,Training,1,1,48,0.372225193241249,78.84,26.0397,2.6804971445437227,177.1417863019849,129.075,-0.7804
+3070,3074,42583-46-0,O=C5Oc3c(c(OC)cc2OC4OC1OC1C4(c23))C6=C5C(=O)CC6,Training,1,1,122,0.5786735826746706,87.5,78.59050000000003,1.7401157871167452,1004.3917482730516,328.2760000000001,1.4877
+3071,3075,4261-14-7,n3cnc1c(ncn1Cc2ccccc2)c3N,Training,1,1,84,0.7163691478973193,69.62,65.27940000000002,2.045660609742777,644.3096877170763,225.25500000000002,1.4567999999999999
+3072,3076,4261-16-9,[O-][n+]3cnc1c(ncn1Cc2ccccc2)c3(N),Training,1,1,90,0.5283194589833697,83.67,66.44440000000002,2.062975315958964,692.259193818939,241.254,0.6952000000000003
+3073,3077,42713-66-6,O=NN(C(=O)N)CCCC(N)C(=O)O,Training,1,1,80,0.38509785648266925,139.07999999999998,46.92960000000001,3.7699302877696113,231.87139393909507,204.186,-0.7593999999999996
+3074,3078,4273-73-8,O=C(OC)C(=CC=CC(=CC=CC=C(C=CC=C(C=CC1=C(C)CCCC1(C)C)C)C)C)C,Training,0,0,178,0.20103538914342686,26.3,143.93599999999986,2.646571223401024,950.8822785288182,446.67500000000035,8.696000000000003
+3075,3079,427-51-0,O=C(OC4(C(=O)C)(CCC3C5C=C(C2=CC(=O)C1CC1C2(C)C5(CCC34(C)))Cl))C,Training,0,0,156,0.6166116116190477,60.440000000000005,108.95300000000003,1.596782817215482,902.5567344378746,416.9450000000002,4.607600000000004
+3076,3080,42794-87-6,Fc1cc(cc(F)c1(N))c2cc(F)c(N)c(F)c2,Training,1,1,94,0.608181900172894,52.04,60.53479999999999,2.625182066053657,523.9598548726741,256.20199999999994,3.0744000000000007
+3077,3081,4291-30-9,O=[N+]([O-])c2cccc(c1ccccc1)c2(O),Training,0,1,80,0.6182866860352763,63.370000000000005,60.19720000000003,2.591180358996231,523.0420115762225,215.208,2.967400000000001
+3078,3082,42924-53-8,O=C(C)CCc1ccc2cc(OC)ccc2(c1),Training,0,1,88,0.8015823313615688,26.3,69.50200000000004,2.279493578280862,543.6131589013072,228.291,3.370000000000002
+3079,3083,42978-43-8,O=C(OCc4c5ccccc5(c1ccc2cccc3ccc4(c1c23)))C,Training,1,1,120,0.23292173993691254,26.3,103.12200000000006,2.0292411559537986,1251.4797241454378,324.3790000000001,5.800300000000004
+3080,3084,4298-16-2,c1ccc(cc1)CC(NC)C,Training,0,0,60,0.6911085509284691,12.03,48.66770000000003,2.5081200778191075,193.28756760359943,149.23699999999997,1.837
+3081,3085,43000-65-3,O=C(OC4CCC2(C)(C(CCC1C3CCC(=O)NC3(C)(CCC12))C4))Cc5ccc(cc5)N(CCCl)CCCl,Training,1,1,210,0.29651928247774345,58.64000000000001,153.84669999999974,1.1596132806631574,997.3436561317753,563.6100000000001,6.336200000000007
+3082,3086,43047-59-2,OCc4ccc1nn(c3c1c4(c2ccc(cc2S3)Cl))CCN(CC)CC,Training,1,1,136,0.5222579773122772,41.290000000000006,108.01280000000004,1.8652984065360896,965.3349648366242,387.9360000000002,4.655400000000004
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+3085,3089,431-63-0,FC(F)C(F)C(F)(F)F,Training,0,0,56,0.50471363803362,0.0,16.955000000000002,3.877604668586773,82.79398751947123,152.03699999999998,2.1519000000000004
+3086,3090,431-89-0,FC(C(F)(F)F)C(F)(F)F,Training,0,0,62,0.4895108834234751,0.0,17.006000000000004,4.231132186198015,93.00007685190862,170.027,2.4490999999999996
+3087,3091,43192-03-6,O=[N+]([O-])c1cc(ccc1C)NO,Training,0,0,64,0.520189276712738,75.4,43.24260000000001,3.1672657777487148,311.5198400095355,168.152,1.7043199999999996
+3088,3092,43192-07-0,ONc1ccc(c(c1)C)C,Training,1,1,54,0.5808157166070327,32.26,41.32520000000002,3.0436180591142796,232.69924244622516,137.182,2.10454
+3089,3093,43218-55-9,n4c2ccc(c3c1ccc(cc1Sc(c23)n4CCN(CC)CC)Cl)C,Training,1,1,130,0.46369417382531747,21.060000000000002,106.82700000000004,1.8459051233130097,943.7545287686361,371.93700000000007,5.4715200000000035
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+3095,3099,437-50-3,O=C1c3cc(O)ccc3(Oc2cc(OC)cc(O)c12),Training,1,1,96,0.6548367258269042,79.9,69.87160000000002,2.535625283895241,847.6893313378117,258.229,2.366000000000001
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+3100,3104,4406-41-1,O=C(Nc1ccccc1)C(C)C,Training,0,0,64,0.7116050593142094,29.1,49.90970000000003,2.589782979601781,253.80090634082455,163.21999999999997,2.2811000000000003
+3101,3105,4424-06-0,O=C3c5ccc7c8nc1ccccc1n8(C(=O)c6ccc(c4nc2ccccc2n34)c5c67),Training,1,1,148,0.34752660790291495,68.74000000000001,126.38400000000001,1.7349842701213205,2032.2833062293016,412.4080000000002,4.344000000000002
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+3103,3107,4430-25-5,O=S4(=O)(OC(c1cc(c(O)c(c1)Br)Br)(c2cc(c(O)c(c2)Br)Br)c3c(c(c(c(c34)Br)Br)Br)Br),Training,0,0,174,0.15221500097438162,83.83000000000001,152.40839999999997,2.286401805436424,1368.225547742856,985.5509999999999,9.2086
+3104,3108,443-48-1,O=[N+]([O-])c1cnc(n1CCO)C,Training,1,1,66,0.5158680082581498,81.19,40.70420000000001,3.032858934158134,294.2284590462867,171.156,0.09201999999999994
+3105,3109,4435-53-4,O=C(OCCC(OC)C)C,Training,0,0,60,0.5543459625799845,35.53,37.721,3.110465475982731,101.02434166397533,146.18599999999998,0.9744999999999999
+3106,3110,4436-24-2,O1CC1Cc2ccccc2,Training,1,1,52,0.559885986678111,12.53,39.88600000000002,2.0335562235346227,201.22806798157623,134.17799999999997,1.6279000000000001
+3107,3111,4437-51-8,O=C(C(=O)CC)CC,Training,1,0,46,0.511617667997256,34.14,30.595999999999986,3.6432249455719163,91.09616281328597,114.144,0.9445999999999999
+3108,3112,4444-68-2,N(CC)(CC)CCCC,Training,0,0,56,0.5493790740981016,3.24,42.69600000000001,3.0922461946023914,48.52932501298081,129.24699999999999,2.1283000000000003
+3109,3113,4450-68-4,O=[N+]([O-])c1ccc(cc1)COS(=O)(=O)c2ccc(cc2)C,Training,1,0,110,0.48137050025560546,86.50999999999999,76.25020000000004,2.0753111080001228,735.9387641159275,307.327,2.808720000000001
+3110,3114,4457-41-4,O=C(OCc1ccc(cc1)[N+](=O)[O-])c2ccccc2,Training,1,0,96,0.47937733188194737,69.44,68.65790000000003,1.9547885837420842,578.1547764486286,257.245,2.9518000000000013
+3111,3115,4460-86-0,O=Cc1cc(OC)c(OC)cc1(OC),Training,0,0,76,0.6847821797370717,44.760000000000005,51.48550000000003,3.2714516432182212,333.13903760611623,196.20199999999997,1.5249
+3112,3116,4463-22-3,O=C(N(O)c1ccc(cc1)c2ccccc2)C,Training,1,1,86,0.6322637154927853,40.540000000000006,66.82450000000003,2.277298668830885,505.5052359816527,227.263,3.0957000000000017
+3113,3117,4465-94-5,O=P(O)(NCCCO)N(CCCl)CCCl,Training,1,1,92,0.3311998150755056,72.8,62.54380000000003,4.150322021331778,202.67431873426904,279.104,0.8383999999999996
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+3116,3120,4494-26-2,O=CC1=CN(C(=O)NC1(=O))C2OC(CO)C(O)C2,Training,0,0,98,0.5370820148323341,121.62000000000002,58.32980000000002,2.3786007075168314,562.2217115079821,256.214,-2.0101999999999993
+3117,3121,4513-36-4,O=C(OCC(C)(C)C)C=C,Training,0,0,58,0.43352176577832746,26.3,40.611000000000004,3.5507487210973183,130.68324254705823,142.19799999999998,1.7617
+3118,3122,4514-19-6,c1ccc5c(c1)cc3ccc2cccc4c2c3c5(cc4C),Training,1,1,98,0.23641815777600875,0.0,92.38900000000004,2.245944113672931,1132.5000637406122,266.34299999999996,6.045620000000004
+3119,3123,452-86-8,Oc1ccc(cc1(O))C,Training,0,0,48,0.5131220403965512,40.46,34.5086,3.1716780304409156,218.15617759993404,124.13899999999998,1.4062199999999998
+3120,3124,4531-49-1,O=C(Nc1ccccc1(OC))C(N=Nc2ccc(cc2Cl)c4ccc(N=NC(C(=O)Nc3ccccc3(OC))C(=O)C)c(c4)Cl)C(=O)C,Training,0,1,246,0.10673659782556452,160.24,183.11539999999962,1.4753095483378753,1777.9562165486243,689.5559999999999,8.037600000000008
+3121,3125,4533-39-5,O=[N+]([O-])c3cccc2nc1ccccc1c(NCCCN(C)C)c23,Training,1,1,124,0.3241605091955102,71.3,97.56410000000005,2.1413299744719705,892.7057219601597,324.38400000000007,3.6598000000000015
+3122,3126,4539-51-9,Nc1ccc3c(c1)[nH]c2ccccc23,Training,1,1,68,0.5155596465854098,41.81,60.217100000000016,2.5668411342691435,607.8208026305191,182.22600000000003,2.9033000000000007
+3123,3127,4543-63-9,O=C(ONC(=O)NC)NC,Training,1,1,58,0.39175524837833686,79.46,33.1321,3.3529215164640975,119.70950594454669,147.134,-0.8136000000000001
+3124,3128,4553-62-2,N#CCCC(C#N)C,Training,1,0,42,0.5370803037436823,47.58,29.623999999999988,3.179522116779088,126.44441158953074,108.14399999999999,1.44986
+3125,3129,4559-64-2,n1c3ccc(cc3(nc2cc(N)c(N)cc12))Cl,Training,1,1,84,0.47067852915512515,77.82,70.8788,2.4335026727125406,739.2299091599898,244.68499999999997,2.6007999999999996
+3126,3130,4560-58-1,O=C(O)CCC(C)C2CCC3C4CCC1CC(O)CCC1(C)C4(CC(=O)C23(C)),Training,0,0,158,0.730367663157964,74.6,107.64760000000008,1.5721205499548385,644.5164062880178,390.56400000000025,4.686100000000005
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+3128,3132,4568-36-9,O=S(=O)(c1cc(cc(c1(O))Cl)Cl)c2cc(cc(c2(O))Cl)Cl,Training,0,0,112,0.7923190907869466,74.60000000000001,81.7054,2.806855653489243,770.1364502484346,388.05500000000006,4.544200000000002
+3129,3133,4569-77-1,Oc1cc2nc3ccccc3(nc2(cc1(N))),Training,1,1,78,0.33897850990161615,72.03,63.12120000000002,2.4649885270272582,634.224009065861,211.224,2.0707999999999998
+3130,3134,458-37-7,O=C(C=Cc1ccc(O)c(OC)c1)CC(=O)C=Cc2ccc(O)c(OC)c2,Training,0,0,140,0.5481228320623274,93.06,102.01660000000003,1.9588614829982385,822.0399999194264,368.3850000000001,3.369900000000002
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+3132,3136,4584-57-0,O=[N+]([O-])c2ccc(C=Cc1ccc(cc1)N(C)C)cc2,Training,1,1,102,0.4806912511634895,46.38,82.79340000000005,2.101143338540724,613.930061455509,268.316,3.8312000000000026
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+3134,3138,4606-98-8,O=S(=O)(OCc1ccc(cc1)C)c2ccc(cc2)C,Training,0,0,100,0.8053361943604477,43.370000000000005,74.33280000000003,2.0925877739362795,640.7949717285212,276.357,3.208940000000002
+3135,3139,4612-63-9,c1ccc3c(c1)c2cc(c(cc2C3)C)C,Training,0,0,74,0.5092659780352894,0.0,64.15800000000003,2.288412090346857,535.7297284527629,194.27699999999996,3.874640000000002
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+3140,3144,4629-58-7,O=[N+]([O-])c2ccc(C=Cc1ccc(N)cc1)cc2,Training,1,1,90,0.386868487873679,69.16,72.87880000000003,2.1329911792252636,571.7479162169986,240.262,3.3474000000000004
+3141,3145,463-04-7,O=NOCCCCC,Training,1,1,48,0.31301049986876467,38.66,31.271999999999984,2.6162930904179853,56.39035952556319,117.14800000000001,1.8746
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+3157,3161,4698-96-8,O(c1ccc(cc1)c2ccccc2)CC3OC3,Training,1,1,86,0.7469736205070414,21.759999999999998,67.11300000000004,1.7046669676572632,472.03482335989,226.27499999999998,3.1312000000000015
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+3169,3173,476-57-3,O=C1c3cc(OC)cc(O)c3(C(=O)c2c(O)cc(c(O)c12)C),Training,1,1,112,0.5928757043181082,104.06,76.03240000000001,2.4023475846510975,850.445027953344,300.266,1.89582
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+3171,3175,476-66-4,O=C1Oc3c(O)c(O)cc4C(=O)Oc2c(O)c(O)cc1c2c34,Training,0,0,110,0.216284535941976,141.34,73.87719999999999,2.5540668740409904,1101.7122430110637,302.194,1.3127999999999997
+3172,3176,476-71-1,Oc1c(OC)cc4c3c1c2cc5OCOc5(cc2CC3N(C)CC4),Training,0,1,124,0.8736024618305053,51.160000000000004,88.99680000000005,1.8363347417534943,861.1757846095304,325.36400000000003,2.8816000000000006
+3173,3177,477-30-5,O=C1C=C3C(=CC=C1(OC))c2c(OC)c(OC)c(OC)cc2CCC3(NC),Training,0,0,144,0.8717462743954658,66.02000000000001,104.47770000000006,2.434728723741696,909.9037651026405,371.4330000000001,2.954900000000001
+3174,3178,477-83-8,O=C1c3ccccc3(C(=O)c2c(OC)c(c(O)cc12)CO),Training,1,0,106,0.7475086664582079,83.83000000000001,73.88860000000001,2.3777911536586727,776.4770705182434,284.267,1.6684999999999992
+3175,3179,477-84-9,O=Cc1c(O)cc2C(=O)c3ccccc3(C(=O)c2(c1(OC))),Training,0,1,104,0.7268842537037178,80.67,73.35330000000002,2.4042833587163073,804.5549019621773,282.251,1.9887000000000001
+3176,3180,478-06-8,O=C(O)c1c(O)cc2C(=O)c3ccccc3(C(=O)c2(c1(O))),Training,0,1,104,0.6249995898568739,111.89999999999999,70.03790000000001,2.38804448801563,834.2977538207974,284.223,1.5714
+3177,3181,478-08-0,O=C1c3ccccc3(C(=O)c2c(O)c(c(O)cc12)CO),Training,1,1,100,0.6203819640195609,94.83000000000001,69.00140000000002,2.3673330395915144,761.0994568832565,270.23999999999995,1.3654999999999997
+3178,3182,478-43-3,O=C(O)c1cc(O)c2C(=O)c3c(O)cccc3(C(=O)c2(c1)),Training,1,0,104,0.6249995898568739,111.9,70.03790000000001,2.3552515422121196,834.2977538207974,284.223,1.5714000000000001
+3179,3183,478-45-5,O=C(O)c1cc(O)c2C(=O)c3c(O)cc(O)cc3(C(=O)c2(c1)),Training,0,1,110,0.5317435266666511,132.13,71.7027,2.3610867095401513,879.9450806029399,300.22200000000004,1.277
+3180,3184,479-13-0,O=C3Oc1cc(O)ccc1c4oc2cc(O)ccc2c34,Training,0,1,98,0.4785965928491851,83.81,73.09160000000001,2.3224066117453703,1038.8652947796463,268.224,3.1036
+3181,3185,479-27-6,Nc1cccc2cccc(N)c12,Training,1,1,60,0.5760063964521945,52.04,52.772800000000004,2.9609415115705566,384.3581352532283,158.20399999999998,2.0042
+3182,3186,4792-83-0,[O-][N+](=Nc1ccc(OCC)cc1)c2ccc(OCC)cc2,Training,0,1,110,0.4487470851036367,56.89,80.59740000000005,2.116727032137956,591.9240832402107,286.331,4.4097000000000035
+3183,3187,479-45-8,O=[N+]([O-])c1cc(c(c(c1)[N+](=O)[O-])N([N+](=O)[O-])C)[N+](=O)[O-],Training,1,1,106,0.5646396118018021,175.79999999999998,61.8026,3.769454572555376,592.636916840488,287.144,1.0390999999999997
+3184,3188,479-50-5,O=C2c1ccccc1Sc3c(ccc(NCCN(CC)CC)c23)C,Training,1,1,126,0.67171766012986,32.34,106.61570000000006,2.0395698133868385,912.540265467161,340.49200000000013,4.476820000000004
+3185,3189,479-79-8,O=C3c1ccccc1c4ccc2ccccc2c34,Training,0,1,84,0.44509506734612314,17.07,72.81650000000003,2.184954318743393,799.5691953307492,230.266,4.051200000000002
+3186,3190,479-92-5,O=C2C(=C(N(N2(c1ccccc1))C)C)C(C)C,Training,0,0,90,0.7787148054561389,26.93,69.83600000000004,2.730260472737881,576.2599451429833,230.311,2.607820000000001
+3187,3191,480-22-8,Oc2cccc3cc1cccc(O)c1c(O)c23,Training,0,1,84,0.5159958739051682,60.69,66.44840000000002,2.636022080343262,672.1916027576739,226.231,3.109800000000001
+3188,3192,480-54-6,O=C1OC3CCN2CC=C(COC(=O)C(O)(CO)C(C)CC1(=CC))C23,Training,1,1,138,0.394724503128909,96.3,88.47360000000003,1.9256465977984363,627.0558299477345,351.3990000000001,0.1652
+3189,3193,480-81-9,O=C1OC3CCN2CC=C(COC(=O)C(O)(C(=C)CC1(=CC))C)C23,Training,1,0,130,0.40657767023266517,76.07,87.03780000000003,1.923879228646023,645.7945607873609,333.38400000000007,1.1128999999999996
+3190,3194,480-85-3,OCC1=CCN2CCC(O)C12,Training,0,0,62,0.494677806442317,43.7,41.15360000000002,2.1500779942209567,190.5310795617182,155.19700000000003,-0.6461000000000001
+3191,3195,4809-35-2,OC(COc1ccc(cc1)C(c2ccc(OCC(O)CCl)cc2)(C)C)CCl,Training,0,1,148,0.5791195334192781,58.92,109.45560000000005,2.036614372730205,626.8327245359449,413.3410000000001,3.9695000000000036
+3192,3196,4812-40-2,O=[N+]([O-])c1cnc(n1CCO)CO,Training,1,1,72,0.47787747301542616,101.42,41.890000000000015,3.0560974578731863,308.8280506390132,187.155,-0.7241000000000002
+3193,3197,48134-75-4,c1ccc(cc1)c2cc[n+](cc2)C,Training,0,0,64,0.577448410587959,3.88,53.05400000000003,2.4238559727704243,375.62904776215686,170.23499999999996,2.1780999999999997
+3194,3198,4813-50-7,OOCCCC,Training,1,1,38,0.32107802656658985,29.46,23.48879999999999,2.3390923149762908,17.509775004326936,90.122,1.2761
+3195,3199,481-39-0,O=C1C=CC(=O)c2c(O)cccc12,Training,1,1,64,0.6450139359253463,54.370000000000005,45.907800000000016,2.7569605368382883,429.7960406537963,174.155,1.3274
+3196,3200,481-42-5,O=C1C=C(C(=O)c2cccc(O)c12)C,Training,1,1,70,0.6739307044863264,54.370000000000005,50.52480000000002,2.750990748091934,469.4210300141994,188.182,1.7175
+3197,3201,481-49-2,O4c1ccc(cc1)CC7c6c(Oc2cc3c(cc2(OC))CCN(C)C3Cc5ccc(OC)c4c5)c8OCOc8(cc6CCN7(C)),Training,1,0,232,0.24502800268016348,61.86000000000001,170.7009999999995,1.3365735670293442,1770.4304335749712,606.719,6.873900000000008
+3198,3202,4816-14-2,N=C(N)c1ccc(cc1)c3cc2ccc(cc2s3)C(=N)N,Training,0,0,104,0.4404721970225324,99.74,89.29320000000003,2.0381206369192033,846.3444094468696,294.383,3.1364400000000003
+3199,3203,481-72-1,O=C1c3cccc(O)c3(C(=O)c2c(O)cc(cc12)CO),Training,1,1,100,0.6203819640195609,94.83,69.00140000000002,2.3498727995847597,761.0994568832565,270.23999999999995,1.3654999999999993
+3200,3204,481-73-2,O=C1c3cc(O)cc(O)c3(C(=O)c2c(O)cc(cc12)CO),Training,1,1,106,0.5316728860472278,115.06,70.66620000000002,2.354905029757158,806.2965209959959,286.239,1.0710999999999995
+3201,3205,481-74-3,O=C1c3cccc(O)c3(C(=O)c2c(O)cc(cc12)C),Training,1,1,94,0.6444480285471402,74.6,67.81560000000002,2.396091207881047,744.0510609635681,254.24099999999996,2.1816199999999997
+3202,3206,482-27-9,O=C2Oc3c(OC)c1occc1c(OC)c3(C=C2),Training,0,0,92,0.6500843101672217,61.81,65.36000000000003,2.629735699481395,781.0171114667733,246.218,2.5564
+3203,3207,4823-47-6,O=C(OCCBr)C=C,Training,1,1,46,0.3681587432773725,26.3,34.949999999999996,3.1114301208164354,90.42945954287094,179.01299999999998,1.1105
+3204,3208,482-44-0,O=C1Oc2c(OCC=C(C)C)c3occc3(cc2(C=C1)),Training,1,0,102,0.5349772470774251,52.58,77.18200000000003,2.213458196330433,847.6610936755231,270.284,3.8842000000000025
+3205,3209,4825-86-9,O=C2OC(C)Cc3ccc(C(=O)NC(C(=O)O)Cc1ccccc1)c(O)c23,Training,0,0,140,0.6942386692146322,112.93,95.72430000000004,1.8359321906365138,892.8449914021965,369.37300000000005,1.9193000000000002
+3206,3210,482-66-6,c1ccc4c(c1)ccc2c4(ccc3c2CCC3),Training,0,1,82,0.4878716637828488,0.0,73.47900000000004,2.2162773688294926,722.5174783695513,218.29899999999992,4.481700000000003
+3207,3211,483-65-8,c2cc1c3ccc(cc3(ccc1c(c2)C))C(C)C,Training,0,1,90,0.49273659384554264,0.0,80.28000000000004,2.386151583935516,720.5174783695513,234.34199999999996,5.424820000000003
+3208,3212,4836-66-2,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])CO,Training,1,0,74,0.5752578719806516,106.51,45.673600000000015,3.274414445393387,389.66658614642563,198.13399999999996,0.9952999999999999
+3209,3213,483-84-1,O=[N+]([O-])c1cc(c2ccc(cc2(c1(O)))S(=O)(=O)O)[N+](=O)[O-],Training,1,0,110,0.4901441362340321,160.88,68.7362,2.9861506212007947,889.556104908691,314.231,1.6085000000000003
+3210,3214,484-08-2,n2c1occc1c(OC)c3cc(OC)c(OC)cc23,Training,1,1,98,0.7233029923217835,53.72000000000001,71.17100000000003,2.438908343454287,747.8655179598607,259.26099999999997,3.006800000000002
+3211,3215,484-17-3,Oc2cc1ccccc1c3ccccc23,Training,1,1,72,0.540858097607516,20.23,63.11880000000003,2.6384478838128724,640.957112138695,194.23299999999998,3.6986000000000026
+3212,3216,484-23-1,n1nc(NN)c2ccccc2(c1NN),Training,1,1,72,0.3983479494698653,101.88,55.1582,2.7798716797036684,412.0258225260371,190.20999999999998,0.2009999999999998
+3213,3217,484-29-7,n2c1occc1c(OC)c3ccccc23,Training,1,0,74,0.603925773865151,35.260000000000005,58.06700000000002,2.574044785045302,627.640512154644,199.209,2.989600000000001
+3214,3218,484-47-9,n2c([nH]c(c1ccccc1)c2c3ccccc3)c4ccccc4,Training,1,1,110,0.5376922076827766,28.68,94.89570000000002,1.9147485215915385,837.5064296463364,296.373,5.410700000000004
+3215,3219,484-78-6,O=C(O)C(N)CC(=O)c1cccc(O)c1(N),Training,0,0,86,0.3226304158926939,126.63999999999999,57.07790000000001,2.891766289502256,430.827247968375,224.216,-0.040900000000000436
+3216,3220,4861-85-2,O=C(OC(C)C)Cc1ccccc1,Training,0,0,70,0.6629901982866924,26.3,51.37400000000004,2.45867389842926,264.67858479938934,178.23100000000002,2.1807
+3217,3221,486-25-9,O=C2c1ccccc1c3ccccc23,Training,0,1,66,0.5195293693386194,17.07,55.31050000000002,2.416126768880536,478.7637016600122,180.206,2.8980000000000015
+3218,3222,486-56-6,O=C2N(C)C(c1cnccc1)CC2,Training,0,0,68,0.6472008557238368,33.2,48.982000000000035,2.236360159695857,309.96060133940625,176.21899999999997,1.3749
+3219,3223,486-66-8,O=C1C(=COc2cc(O)ccc12)c3ccc(O)cc3,Training,0,0,94,0.700091545915688,70.67,71.24960000000002,2.2576735694139023,800.4836768266103,254.241,2.871200000000001
+3220,3224,4873-56-7,O=S(=O)(OCC(C)C)c1ccc(cc1)C,Training,0,1,84,0.7429271331215237,43.370000000000005,59.15480000000004,2.820991357385728,403.9641038981167,228.313,2.35632
+3221,3225,487-99-0,O=C(OCC2CCN1CCCC12)C(O)(C(O)C)C(C)C,Training,0,0,116,0.7306502527970437,70.0,75.12960000000005,1.9120188990198161,347.7826761686426,285.384,0.7817999999999995
+3222,3226,488-11-9,O=CC(=C(C(=O)O)Br)Br,Training,1,1,50,0.598916711396035,54.370000000000005,38.5798,4.471772749925975,172.6515613063118,257.86499999999995,1.2712999999999999
+3223,3227,488-23-3,c1cc(c(c(c1C)C)C)C,Training,0,0,54,0.5114796780810564,0.0,45.39000000000002,3.3421538077705124,219.46037742768317,134.22199999999998,2.9202800000000018
+3224,3228,4901-51-3,Oc1cc(c(c(c1Cl)Cl)Cl)Cl,Training,0,0,60,0.5287193643960513,20.23,48.14680000000001,3.4555464838177836,270.8740242221354,231.893,4.005799999999999
+3225,3229,490-91-5,O=C1C=C(C(=O)C=C1C)C(C)C,Training,0,0,64,0.5522549586177093,34.14,46.69200000000002,3.0118928453875435,292.9604403037665,164.20399999999998,1.6668999999999998
+3226,3230,491-35-0,n1ccc(c2ccccc12)C,Training,1,1,54,0.5519055037199659,12.89,46.48000000000002,2.9131611636048604,374.03449039867854,143.18899999999996,2.5432200000000007
+3227,3231,4914-30-1,O(c1cc2c(cc1(OC))C(NCC2)CC5=C(CN4CCc3cc(OC)c(OC)cc3C4C5)CC)C,Training,0,0,188,0.5650184028299402,52.19000000000001,138.1086999999999,1.4628554639331268,1126.1502327895696,478.6330000000003,5.007600000000005
+3228,3232,491-59-8,Oc2cccc3cc1cc(cc(O)c1c(O)c23)C,Training,1,1,90,0.5275136574320083,60.69,71.18540000000002,2.613927720326788,775.6298966071572,240.25799999999998,3.4182200000000016
+3229,3233,491-64-5,O=C1c3cc(OC)ccc3(Oc2cc(O)cc(O)c12),Training,1,1,96,0.6548367258269042,79.9,69.87160000000002,2.5285854910196264,847.6893313378117,258.229,2.366000000000001
+3230,3234,491-80-5,O=C1C(=COc2cc(O)cc(O)c12)c3ccc(OC)cc3,Training,0,0,106,0.7560099167404621,79.9,77.80160000000001,2.2397479278091876,862.2099982883233,284.267,2.8798000000000012
+3231,3235,492-27-3,O=C(O)c1nc2ccccc2(c(O)c1),Training,0,0,70,0.7148878381346437,70.42,50.367100000000015,2.7846388446711865,507.69331220127367,189.17,1.6385999999999998
+3232,3236,493-52-7,O=C(O)c2ccccc2(N=Nc1ccc(cc1)N(C)C),Training,1,1,102,0.8567737656666876,65.25999999999999,78.34630000000004,2.2318048143859897,633.8218150192178,269.304,3.8662000000000027
+3233,3237,4938-72-1,O=C(OCC(C)C)COc1cc(c(cc1Cl)Cl)Cl,Training,0,0,100,0.6029455764750311,35.53,72.76400000000002,2.5319279096126226,432.82096642806596,311.592,4.224800000000003
+3234,3238,494-03-1,c1ccc2cc(ccc2(c1))N(CCCl)CCCl,Training,1,1,90,0.7370344966577712,3.24,77.60100000000004,2.3240966141531545,478.36083368565164,268.1869999999999,4.123800000000003
+3235,3239,4947-27-7,O=C3c4ccccc4(C(=O)c2c3(ccc(c2(Nc1ccccc1))C)),Training,1,1,116,0.591867837373338,46.17,94.21070000000002,1.919033395348114,974.3838472218483,313.356,4.514020000000003
+3236,3240,494-90-6,o1cc(c2c1CC(C)CC2)C,Training,0,0,60,0.5538926622601129,13.14,44.63400000000002,2.3631649923562184,259.83653540052643,150.22099999999998,2.7128200000000007
+3237,3241,495-18-1,O=C(NO)c1ccccc1,Training,1,0,52,0.44409634457370617,49.33,35.69470000000001,2.8526279288191434,220.30753299614886,137.13799999999998,0.8056000000000003
+3238,3242,495-48-7,[O-][N+](=Nc1ccccc1)c2ccccc2,Training,1,1,74,0.4123582375548761,38.43,58.259400000000035,2.2921562052404463,451.56303988704076,198.225,3.612300000000002
+3239,3243,49562-28-9,O=C(c1ccc(OC(C(=O)OC(C)C)(C)C)cc1)c2ccc(cc2)Cl,Training,0,0,132,0.5540618915195044,52.60000000000001,97.26150000000004,2.0999292472814393,746.2705504674376,360.837,4.680000000000004
+3240,3244,496-14-0,O2Cc1ccccc1C2,Training,1,1,46,0.5061667423941253,9.23,34.935,2.53519473965517,194.56254955650076,120.15099999999997,1.7167999999999999
+3241,3245,496-72-0,Nc1ccc(cc1(N))C,Training,1,1,48,0.5071584204162337,52.04,40.00380000000001,3.1716780304409156,218.15617759993404,122.171,1.1594200000000001
+3242,3246,497-23-4,O=C1OCC=C1,Training,0,0,32,0.388929248564653,26.3,20.098999999999993,2.5935505462934776,93.72120767599536,84.07399999999998,0.09940000000000004
+3243,3247,497-56-3,O=[N+]([O-])c1cc(O)c(c(c1)[N+](=O)[O-])C,Training,0,1,74,0.5720654169940127,106.51000000000002,46.152600000000014,3.4275044779343165,414.78633577032497,198.134,1.5170199999999998
+3244,3248,497841-28-8,N2=CNC(NC(c1ccccc1)C)=C3C=C(N=C23)c4ccc(cc4)CCl,Training,1,1,130,0.4614852932652034,53.6,106.4774,1.6537748452171381,963.0546331497021,362.86400000000003,5.488400000000004
+3245,3249,49792-23-6,O=C(O)C6(C)(C(OC1OC(CO)C(O)C(O)C1(O))C(O)CC5(C)(C6(CCC3(C)(C5(CC=C2C4CC(C)(C)CCC4(C(=O)O)(CCC23(C))))))),Training,0,0,266,0.1686652578151701,194.20999999999998,168.6665999999996,1.3641309845989773,1313.3777576184957,664.8330000000001,3.0933
+3246,3250,498-02-2,O=C(c1ccc(O)c(OC)c1)C,Training,0,0,64,0.6786166527324065,46.53,44.66330000000002,3.1343002499495434,304.64199945095794,166.176,1.6034
+3247,3251,49852-84-8,c1ccc5c(c1)c2ccc3cccc4ccc(c2c34)c5CCl,Training,0,1,104,0.1888098175126323,0.0,97.20900000000005,2.2279322051501755,1138.5980587215813,300.788,6.4760000000000035
+3248,3252,49852-85-9,c1ccc5c(c1)c2ccc3cccc4ccc(c2c34)c5CBr,Training,1,1,104,0.1816236060151864,0.0,100.28300000000006,2.2279322051501755,1138.5980587215813,345.239,6.632100000000004
+3249,3253,4985-70-0,c2ccc3cc1c(cccc1Cl)cc3(c2),Training,0,1,72,0.476239910717608,0.0,66.46400000000003,2.532561174306745,640.9571121386949,212.67899999999997,4.646400000000002
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+3331,3335,512-04-9,OC6CC5=CCC4C(CCC3(C)(C4(CC2OC1(OCC(C)CC1)C(C)C23)))C5(C)CC6,Training,0,1,168,0.5157489370080627,38.69,117.70080000000009,1.2821987670487947,736.3902102956508,414.6300000000003,5.713900000000007
+3332,3336,51230-49-0,o2c1ccccc1c3cc(ccc23)Cl,Training,1,0,68,0.531560836348283,13.14,58.730000000000025,2.584067409670167,609.8208026305191,202.64,4.239400000000002
+3333,3337,512-56-1,O=P(OC)(OC)OC,Training,1,0,50,0.5489963488159847,44.760000000000005,28.633499999999987,3.7910098125875016,82.43699516085105,140.075,1.0337
+3334,3338,51264-14-3,O=S(=O)(Nc4ccc(Nc2c3ccccc3(nc1ccccc12))c(OC)c4)C,Training,1,1,142,0.4877079254910788,80.32000000000001,113.99220000000003,1.8513672623370376,1232.8167960032904,393.4680000000002,4.511700000000003
+3335,3339,51-28-5,O=[N+]([O-])c1ccc(O)c(c1)[N+](=O)[O-],Training,0,1,68,0.5485201907500785,106.51000000000002,41.41560000000001,3.267052212361692,375.28740254995904,184.10699999999997,1.2086
+3336,3340,5131-58-8,O=[N+]([O-])c1ccc(N)cc1(N),Training,1,1,58,0.35337020873087255,95.17999999999999,41.9212,3.1960696621259195,297.87891172429886,153.141,0.7592000000000001
+3337,3341,5131-60-2,Nc1ccc(c(N)c1)Cl,Training,1,1,48,0.5397866981817153,52.04,40.2768,3.1716780304409156,222.29788705001033,142.589,1.5044000000000002
+3338,3342,51325-35-0,O=C(Nc1nc(nc(n1)c2oc(cc2)[N+](=O)[O-])NC(=O)C)C,Training,1,1,114,0.6249042894699809,153.15,72.7908,2.449523094605354,720.9309594040383,306.2380000000001,0.9565999999999998
+3339,3343,51325-91-8,N#CC(C#N)=C1C=C(OC(=C1)C)C=Cc2ccc(cc2)N(C)C,Training,1,0,114,0.7938281060687961,60.050000000000004,90.98000000000003,2.241084700035079,778.5018595728167,303.36500000000007,3.9274600000000026
+3340,3344,51330-27-9,O=C(O)C8OC(OC2CCC3(C)(C4CC=C1C5CC(C)(C)CC(O)C5(C)(CCC1(C)C4(C)(CCC3(C2(C)(CO))))))C(OC7OC(CO)C(O)C(O)C7(OC6OC(C)C(O)C(O)C6(O)))C(O)C8(O),Training,0,0,378,0.11207752572237996,294.97999999999996,230.55979999999926,1.075786230255625,1816.9190722572105,943.1340000000009,0.7046000000000054
+3341,3345,513-31-5,C=C(CBr)Br,Training,1,1,30,0.5691327733202446,0.0,31.860999999999994,2.8473789230876716,40.1577218810798,199.873,2.2899000000000003
+3342,3346,513-37-1,C(=C(C)C)Cl,Training,1,1,30,0.4276283312711025,0.0,25.28399999999999,3.1431973062780685,41.60964047443681,90.553,2.1489000000000003
+3343,3347,5134-49-6,O=[N+]([O-])c1ccc(cc1)Cn3cnc2c(ncnc23)N,Training,1,1,100,0.5676015716085668,112.75999999999999,71.93380000000002,1.929969572514369,780.2468131635761,270.252,1.3649999999999998
+3344,3348,51357-79-0,n2c1ccc(cc1c(N)s2)Cl,Training,1,1,56,0.6836020313289691,38.91,49.04240000000001,2.873085923423898,396.23994574764356,184.651,2.5319
+3345,3349,51-36-5,O=C(O)c1cc(cc(c1)Cl)Cl,Training,0,0,58,0.7401842714593464,37.3,43.42130000000001,3.186012533928303,276.2420897763861,191.01299999999998,2.6916
+3346,3350,513-85-9,OC(C)C(O)C,Training,0,0,38,0.46574414882903137,40.46,23.361599999999992,2.9934972434784735,26.52932501298081,90.122,-0.252
+3347,3351,513-88-2,O=C(C)C(Cl)Cl,Training,1,1,36,0.48593925516848924,17.07,26.174999999999997,3.2575861612334887,59.813537528125096,126.97,1.3791
+3348,3352,514-10-3,O=C(O)C2(C)(CCCC3(C)(C1C(C=C(CC1)C(C)C)=CCC23)),Training,0,0,122,0.7602940324701217,37.3,89.53580000000005,1.9987472404856343,541.9104984355639,302.458,5.206200000000006
+3349,3353,51410-44-7,OC(C=C)c1ccc(OC)cc1,Training,0,0,64,0.6913670468861387,29.46,48.15080000000003,2.8371449191351785,251.0460188386611,164.20399999999998,1.9145999999999999
+3350,3354,51410-45-8,O(c1ccc(cc1)CC2OC2)C,Training,1,1,64,0.6332811819054802,21.759999999999998,46.43800000000003,2.0201505912672193,249.04601883866104,164.20399999999998,1.6365
+3351,3355,51-43-4,Oc1ccc(cc1(O))C(O)CNC,Training,0,0,72,0.5101568892419974,72.72,48.658100000000026,2.8351682624881787,288.1883450849283,183.207,0.35059999999999997
+3352,3356,51-44-5,O=C(O)c1ccc(c(c1)Cl)Cl,Training,0,0,58,0.7401842714593464,37.3,43.42130000000001,3.1515496683060507,296.492089776386,191.01299999999998,2.6916
+3353,3357,51-45-6,n1c[nH]cc1CCN,Training,0,0,44,0.5600816350147322,54.7,31.346099999999996,2.500248651523409,133.39382807919944,111.14800000000002,-0.08910000000000007
+3354,3358,51461-16-6,O=C1c3ccc(c(c3(C(=O)c2cccc(c12)[N+](=O)[O-]))[N+](=O)[O-])C,Training,1,1,114,0.5293567019387859,120.42000000000002,77.79480000000001,2.4037964809415615,931.8046121755008,312.237,2.5868200000000012
+3355,3359,514-78-3,O=C2C(=C(C=CC(=CC=CC(=CC=CC=C(C=CC=C(C=CC1=C(C(=O)CCC1(C)C)C)C)C)C)C)C(C)(C)CC2)C,Training,0,0,224,0.2473057077041016,34.14,182.1719999999994,1.9272212337964902,1272.274143051059,564.8540000000003,10.963799999999988
+3356,3360,51481-10-8,O=C3C(=CC4OC2C(O)CC(C)(C12(OC1))C4(CO)(C3(O)))C,Training,0,0,116,0.5458309652959041,99.52000000000001,70.36440000000003,1.9465996971042965,552.36709666319,296.31899999999996,-0.8377000000000003
+3357,3361,51483-39-7,C(C(CCl)Br)Cl,Training,1,1,38,0.587950648137283,0.0,34.155,2.754184786037662,27.97416845103709,191.883,2.2275
+3358,3362,51483-40-0,C(C(CBr)Cl)Br,Training,1,1,38,0.6457988588669854,0.0,37.22900000000001,2.754184786037662,27.97416845103709,236.334,2.3836000000000004
+3359,3363,51489-62-4,O=CNc2ccc(Oc1ccc(cc1)Cl)cc2,Training,1,1,86,0.836921579541008,38.33,67.65470000000002,2.077563222249952,493.8328413567314,247.681,3.7006000000000023
+3360,3364,515-46-8,O=S(=O)(OCC)c1ccccc1,Training,1,1,66,0.6702343643427895,43.370000000000005,45.25380000000003,2.9915745285024826,328.580422437888,186.23200000000003,1.4118000000000002
+3361,3365,51568-18-4,O=C(O)CCC(=O)CC(=O)C,Training,0,0,62,0.5876092289516222,71.44,37.174800000000005,3.5346044713558102,182.87959510731497,158.153,0.3994000000000002
+3362,3366,51576-10-4,O=C(OC24(C(=C)CC3(CCC1C(C(=O)O)(C)CCCC1(C)C3(CC2))(C4)))C,Training,0,0,144,0.5712455054068841,63.60000000000001,98.45280000000007,1.7123647788740266,683.629732496446,360.4940000000002,4.725800000000005
+3363,3367,516-06-3,O=C(O)C(N)C(C)C,Training,0,0,48,0.5369765717084767,63.31999999999999,30.44919999999999,3.6376825478398387,90.42945954287094,117.148,0.054300000000000015
+3364,3368,51630-58-1,N#CC(OC(=O)C(c1ccc(cc1)Cl)C(C)C)c3cccc(Oc2ccccc2)c3,Training,0,0,152,0.40052745192654815,59.31999999999999,116.43500000000002,1.7833639861151815,1026.2643155669198,419.90800000000013,6.679980000000005
+3365,3369,51640-90-5,O=C2Oc1c(cccc1[N+](=O)[O-])c3ccccc23,Training,1,1,88,0.28396376553205804,73.35,66.64440000000003,2.621421564022806,835.1288097672251,241.20199999999997,2.854400000000001
+3366,3370,5166-35-8,C=C(C)C(C)Cl,Training,1,1,36,0.35346826945707055,0.0,30.128999999999987,3.2575861612334887,54.95878455585175,104.58,2.1898
+3367,3371,517-28-2,Oc4ccc2c(OCC3(O)(Cc1cc(O)c(O)cc1C23))c4(O),Training,0,1,114,0.46946133619296915,110.38000000000001,75.53500000000001,1.9681617222066563,799.7084198980604,302.28200000000004,1.3204999999999993
+3368,3372,517-66-8,O(c3cc4c1c5OCOc5(cc2c1C(N(C)CC2)Cc4(cc3(OC))))C,Training,1,0,130,0.8403436400116808,40.16,93.88400000000004,1.8332801891017771,876.7303670871277,339.3910000000001,3.1846000000000023
+3369,3373,51775-36-1,C2C1C(C(C(CCl)(C1(CCl)(CCl))C2(Cl)Cl)Cl)Cl,Training,0,0,100,0.5989283783718174,0.0,78.85200000000003,2.6254264846871034,313.77627414196525,379.3689999999999,5.097800000000002
+3370,3374,517-82-8,O=C1C(O)=C(C(=O)c2c(O)c(O)c(O)c(O)c12)CC,Training,1,1,100,0.37915206749021796,135.29,61.70800000000002,2.9179584633215834,654.7771244168509,266.205,1.1100999999999999
+3371,3375,51787-42-9,n2c1c4ccccc4(ccc1c(c3cc(cc(c23)C)C)C),Training,1,1,102,0.3052358705913932,12.89,90.96600000000005,2.303426903467229,1012.4969221981513,271.36299999999994,5.466460000000004
+3372,3376,51787-75-8,O=[N+]([O-])c1ccc(cc1)c2ccc(cc2(N))[N+](=O)[O-],Training,1,1,96,0.5169085847143471,112.30000000000001,69.59920000000001,2.4146140925871658,652.5241136328642,259.221,2.7522
+3373,3377,51-79-6,O=C(OCC)N,Training,1,1,36,0.4950193943469449,52.32,21.2094,2.8312571099313644,52.75488750216347,89.09400000000001,0.10160000000000013
+3374,3378,518-28-5,O=C3OCC4C(O)c1cc5OCOc5(cc1C(c2cc(OC)c(OC)c(OC)c2)C34),Training,0,0,158,0.762917321090077,92.68000000000002,103.40480000000005,1.7415109606075292,991.4325050884056,414.41000000000014,2.4092000000000002
+3375,3379,51856-71-4,O=[N+]([O-])c2cc(N=[N+]([O-])c1cc(c(c(c1)[N+](=O)[O-])C)[N+](=O)[O-])c(c(c2)[N+](=O)[O-])C,Training,1,1,150,0.29410764436349107,210.99,94.35100000000003,2.7365583786759635,1075.9919181937478,406.26700000000017,3.8619400000000024
+3376,3380,51857-25-1,O=[N+]([O-])c2cc(N=[N+]([O-])c1cc(c(c(c1)[N+](=O)[O-])C)[N+](=O)[O-])cc(c2C)[N+](=O)[O-],Training,1,1,150,0.29410764436349107,210.99,94.35100000000001,2.705533882213521,1040.7419181937476,406.26700000000017,3.8619400000000024
+3377,3381,51868-46-3,O=C(Nc2cc(c(OC)cc2(N=Nc1c(cc(cc1Br)[N+](=O)[O-])[N+](=O)[O-]))N(CC=C)CC=C)C,Training,1,1,178,0.1651341361294137,152.57000000000002,131.53150000000005,2.679815590931317,1172.8291848119884,533.3390000000002,5.826300000000005
+3378,3382,518-75-2,O=C(O)C=2C(=O)C(=C1C(=COC(C)C1C)C=2(O))C,Training,0,1,96,0.6921211569723766,83.83,62.79160000000002,2.666558902363449,535.5848579389813,250.25,1.721
+3379,3383,518-82-1,O=C1c3cc(O)cc(O)c3(C(=O)c2c(O)cc(cc12)C),Training,1,1,100,0.5794952297659434,94.83,69.48040000000002,2.3956753300539084,725.8362617815494,270.23999999999995,1.8872199999999995
+3380,3384,518-83-2,O=C1c3ccccc3(C(=O)c2c(O)cc(O)cc12),Training,1,1,88,0.628686275140444,74.60000000000001,63.07860000000002,2.3734300485217066,700.9353339687136,240.21399999999997,1.8732
+3381,3385,519-23-3,n1ccc3c(c1)c(c2c4ccccc4([nH]c2c3C))C,Training,1,1,92,0.48641016175890156,28.68,80.57970000000003,2.3940166704541754,932.1144172463221,246.313,4.4861400000000025
+3382,3386,51938-12-6,O=NN(CCC)CCCCO,Training,1,1,66,0.345113828794939,52.900000000000006,43.97880000000002,3.276059486028382,98.4413633679148,160.21699999999998,1.1523
+3383,3387,51938-13-7,O=NN(CCCO)CCCC,Training,1,1,66,0.4487382699621953,52.900000000000006,43.97880000000002,3.326343011048127,90.44136336791479,160.21699999999998,1.1523
+3384,3388,51938-14-8,O=NN(CCO)CCCC,Training,1,1,60,0.44436151355199593,52.900000000000006,39.3618,3.294531737146327,87.81700155456724,146.19,0.7622000000000002
+3385,3389,51938-15-9,O=NN(CC(=O)C)CCCC,Training,1,1,64,0.4328794402231208,49.74,42.957000000000015,3.572873194657778,136.40226335060703,158.20099999999996,1.3589
+3386,3390,51938-16-0,O=NN(C)CCCCO,Training,1,1,54,0.3338548904917275,52.900000000000006,34.74479999999999,2.96362233860398,77.35824643629124,132.163,0.37210000000000004
+3387,3391,51938-21-7,O=NN(CCC(=O)OC)CCCC,Training,1,1,76,0.3433681276096825,58.97,48.909000000000034,3.5836316094366345,161.46812888559398,188.22699999999995,1.3330000000000002
+3388,3392,51940-44-4,O=C(O)C1=CN(c2nc(ncc2(C1(=O)))N3CCNCC3)CC,Training,1,1,116,0.8175614911237251,100.34999999999998,81.51400000000004,2.168642932607111,779.8773504105488,303.3220000000001,-0.08080000000000043
+3389,3393,519-73-3,c1ccc(cc1)C(c2ccccc2)c3ccccc3,Training,0,1,92,0.5766946529262025,0.0,80.27100000000004,2.1210106325672244,518.0619248819434,244.337,4.866800000000003
+3390,3394,520-18-3,O=C1C(O)=C(Oc2cc(O)cc(O)c12)c3ccc(O)cc3,Training,1,0,106,0.5458513994143424,111.13000000000001,74.5792,2.372496567253774,892.6662849554008,286.239,2.2824
+3391,3395,52021-61-1,O=CC(c1c(O)cc2C(=O)c3cc(O)cc(O)c3(C(=O)c2(c1(O))))CCOC(=O)C,Training,1,1,150,0.36780414950123663,158.42999999999998,96.46320000000001,2.145177354779921,1068.3520481818016,400.3390000000002,1.5201000000000002
+3392,3396,520-26-3,O=C4c5c(O)cc(OC2OC(COC1OC(C)C(O)C(O)C1(O))C(O)C(O)C2(O))cc5(OC(c3ccc(OC)c(O)c3)C4),Training,0,0,236,0.18471660959332944,234.28999999999996,140.69889999999987,1.3039965777101092,1319.3038683813043,610.565,-1.1565999999999983
+3393,3397,520-36-5,O=C1C=C(Oc2cc(O)cc(O)c12)c3ccc(O)cc3,Training,0,0,100,0.6318329361180623,90.9,72.9144,2.2893972855172384,846.5071386809369,270.24,2.5768000000000004
+3394,3398,5208-87-7,OC(C=C)c1ccc2OCOc2(c1),Training,0,0,68,0.6994079741077596,38.69,47.72180000000002,2.3524412898356597,332.941785033144,178.18699999999995,1.6346999999999998
+3395,3399,52101-36-7,O=C(OC)c2occ(c1ccccc1)c2c3ccccc3,Training,0,0,104,0.6664844877560786,39.44,80.91950000000003,2.2276669500505815,742.6493206498059,278.307,4.400200000000003
+3396,3400,52101-39-0,O=C(OC)c3oc(c(c1ccccc1)c3(c2ccccc2))[N+](=O)[O-],Training,1,1,120,0.4057427471675923,82.58,87.57390000000004,2.3858621225093963,884.5324062461585,323.3040000000001,4.308400000000003
+3397,3401,52101-40-3,O=C(O)c2oc(c(c1ccccc1)c2c3ccccc3)[N+](=O)[O-],Training,1,1,114,0.5749184684892814,93.58,83.19370000000004,2.3973483113047727,796.7592018021443,309.27700000000004,4.220000000000002
+3398,3402,52101-49-2,O=C(c3oc(c(c1ccccc1)c3(c2ccccc2))[N+](=O)[O-])C,Training,1,1,114,0.39675448761241267,73.35,86.23890000000004,2.397348311304773,794.7970605518752,307.30500000000006,4.724400000000003
+3399,3403,521-61-9,O=C1c3cc(OC)cc(O)c3(C(=O)c2c(O)cc(cc12)C),Training,1,1,106,0.7152891518907434,83.83,74.36760000000001,2.3549050297571577,804.8000144600138,284.267,2.19022
+3400,3404,5216-25-1,c1cc(ccc1C(Cl)(Cl)Cl)Cl,Training,1,1,60,0.5863837162361379,0.0,50.689000000000014,2.9937547882599267,233.61264077829026,229.921,4.1667000000000005
+3401,3405,52171-92-3,c1ccc2c(c1)ccc3c4cccc(c4(cc(c23)C))C,Training,1,1,96,0.3506276823536388,0.0,88.43400000000004,2.3466866445131025,961.5588177778452,256.34799999999996,5.763040000000004
+3402,3406,52171-93-4,c1ccc2c(c1)ccc3c2c(cc4C(=CCCc34)C)C,Training,1,1,98,0.45691495226328493,0.0,88.16300000000004,2.2222257425995773,865.9703844666501,258.3639999999999,5.650920000000004
+3403,3407,522-06-5,n3c1occc1c(OC)c4cc2OCOc2c(OC)c34,Training,1,1,102,0.7150183629602055,62.95000000000002,70.74200000000003,2.215035747931778,823.3939822009802,273.24399999999997,2.7269000000000005
+3404,3408,5221-17-0,O=CC(CBr)Br,Training,1,1,36,0.5023033260596614,17.07,32.57299999999999,2.964900494759056,46.05785641096993,215.87199999999999,1.3437000000000001
+3405,3409,522-19-0,n2c1occc1c(OC)c3cc(OC)cc(OC)c23,Training,1,1,98,0.7233029923217835,53.72000000000001,71.17100000000003,2.493704983058673,747.8655179598607,259.26099999999997,3.006800000000001
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+3425,3430,52559-52-1,O=C(Nc1c(cccc1CC)CC)CO,Training,1,0,82,0.789753789655315,49.33,60.913500000000035,3.045860492693432,325.22539782717354,207.27299999999994,1.7422
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+3428,3433,52671-42-8,O=Nc2ccc(Oc1ccccc1)cc2,Training,1,1,74,0.7033934625199948,38.66,58.41300000000003,2.146108592777894,436.9391154828053,199.209,3.876800000000002
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+3434,3439,52748-31-9,O1C=CC2OC2(C=C1),Training,0,0,42,0.43028249593392814,21.759999999999998,28.02599999999999,2.1678262299034907,132.6075250475963,110.11199999999998,0.8113999999999999
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+3437,3442,527-61-7,O=C1C=C(C(=O)C(=C1)C)C,Training,0,0,52,0.4659417707377386,34.14,37.528000000000006,3.051228729159755,232.43115658409945,136.14999999999998,1.0308
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+3439,3444,527-85-5,O=C(N)c1ccccc1C,Training,0,0,52,0.6150947811524278,43.09,39.69690000000002,3.1529414466808685,255.1894333808838,135.16599999999997,1.09392
+3440,3445,52819-96-2,O=C4Oc2c(c(OC)cc1OC3OC=CC3(c12))C5=C4C(=O)CC5(O),Training,1,1,122,0.7970358644058295,95.2,80.32530000000003,1.9554494299452598,1000.3917482730516,328.27600000000007,1.7673999999999999
+3441,3446,528-29-0,O=[N+]([O-])c1ccccc1[N+](=O)[O-],Training,1,1,62,0.49411926294389913,86.28,39.75080000000001,3.2670761957037717,303.0748996548373,168.10799999999995,1.503
+3442,3447,528-45-0,O=C(O)c1ccc(c(c1)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,78,0.5923677440348533,123.58000000000001,46.7101,3.3963489782409875,454.7936738455577,212.11699999999996,1.2011999999999998
+3443,3448,528-53-0,Oc1cc(O)c2cc(O)c([o+]c2(c1))c3cc(O)c(O)c(O)c3,Training,0,0,112,0.3005071373309243,132.68,76.0458,2.29469560096145,879.016930626118,303.246,2.6144999999999996
+3444,3449,52-86-8,O=C(c1ccc(F)cc1)CCCN3CCC(O)(c2ccc(cc2)Cl)CC3,Training,0,0,138,0.759345285057915,40.540000000000006,100.98730000000003,1.444579210133206,737.611323693879,375.8710000000001,4.425600000000004
+3445,3450,528-75-6,O=Cc1ccc(cc1[N+](=O)[O-])[N+](=O)[O-],Training,1,1,72,0.4114749481334959,103.35,45.1383,3.3438914542931713,414.5412232724884,196.11799999999997,1.3155000000000001
+3446,3451,529-19-1,N#Cc1ccccc1C,Training,0,0,44,0.5085022668084197,23.79,35.894000000000005,3.1993264386267954,244.98970244066405,117.15099999999997,1.8667
+3447,3452,529-20-4,O=Cc1ccccc1C,Training,0,0,46,0.5163635148900696,17.07,36.566500000000005,3.1479791300397526,215.56254955650078,120.15099999999997,1.80752
+3448,3453,529-49-7,O=C1c3cc(O)ccc3(Oc2cc(O)cc(O)c12),Training,1,1,90,0.5263727712755552,90.9,64.98440000000002,2.6114191107086504,832.0093942884614,244.20199999999997,2.063
+3449,3454,5296-38-8,O(c1ccc(cc1)Cc2ccccc2)CC3OC3,Training,1,1,92,0.7491608895896618,21.759999999999998,70.92500000000004,1.5938919196861527,486.265226919435,240.302,3.0550000000000015
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+3451,3456,53043-28-0,O=CC=1C(=O)C(O)(C)C(O)C2=COC(=CC=12)C,Training,1,0,90,0.4940595850221863,83.83000000000001,57.652600000000014,2.6905168750127437,493.0253777754103,236.22299999999996,-0.0056000000000004935
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+3453,3458,530-62-1,O=C(n1cncc1)n2cncc2,Training,0,1,60,0.5694494056446111,52.71,40.646000000000015,2.339063253730274,325.7815386057552,162.152,0.5959999999999999
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+3455,3460,5307-00-6,O(c1cc(N)c(cc1(N))C)C,Training,0,1,60,0.5935957489158801,61.269999999999996,46.55580000000001,3.2058276203237264,271.03972257956417,152.197,1.16802
+3456,3461,5307-14-2,O=[N+]([O-])c1cc(N)ccc1(N),Training,1,1,58,0.35337020873087255,95.17999999999999,41.9212,3.232208870305491,297.87891172429886,153.141,0.7592000000000001
+3457,3462,530-75-6,O=C(O)c2ccccc2(OC(=O)c1ccccc1(OC(=O)C)),Training,0,0,112,0.6890062124965186,89.9,76.11080000000004,2.3077517616581544,734.9208195249171,300.2660000000001,2.529300000000001
+3458,3463,530-78-9,O=C(O)c2ccccc2(Nc1cccc(c1)C(F)(F)F),Training,0,0,104,0.8882248174804238,49.33,68.12800000000001,2.337930511639871,638.3112969345251,281.23299999999995,4.147200000000001
+3459,3464,53175-28-3,O=CC(=CC)Cl,Training,1,1,34,0.3623771436727785,17.07,25.673999999999992,3.5040318284625833,75.61727061434749,104.536,1.3279
+3460,3465,531-75-9,O=C2Oc3cc(O)c(OC1OC(CO)C(O)C(O)C1(O))cc3(C=C2),Training,0,1,130,0.42851483868319096,149.82,78.54400000000001,1.8940464156872356,784.0986552582978,340.28400000000005,-1.3227000000000013
+3461,3466,531-82-8,O=C(Nc1nc(cs1)c2oc(cc2)[N+](=O)[O-])C,Training,1,1,88,0.6678077786262938,98.27000000000001,60.774100000000004,2.2374365110007863,574.3128940666095,253.23899999999998,2.2697000000000003
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+3463,3468,53198-46-2,O=NN(C)C(OC(=O)C)c1ccccc1,Training,1,0,80,0.3277555215776399,58.970000000000006,54.50700000000003,2.9019700014137535,339.7805543891172,208.217,1.8615
+3464,3469,53219-95-7,O=C(O)CCC(=O)Nc1cc(cc(c1)Cl)Cl,Training,0,0,86,0.8761989385400376,66.39999999999999,61.96150000000002,2.587170229787586,400.275210841485,262.092,2.7967000000000013
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+3468,3473,5329-15-7,O=C(Nc1ccc(N)cc1(OC))C,Training,1,1,70,0.6727266657928148,64.35000000000001,51.71010000000002,2.9861756521836407,323.3907822709721,180.20699999999997,1.2358
+3469,3474,5329-87-3,O=[N+]([O-])c2ccc3c1ccccc1CCc3(c2),Training,1,1,84,0.5513299482933861,43.14,65.94040000000003,2.178430140133262,604.9212469901295,225.24699999999996,3.360400000000002
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+3472,3477,533-30-2,n1csc2cc(N)ccc12,Training,1,0,50,0.58218565873613,38.91,44.03240000000001,2.860781632079712,353.1335934262615,150.206,1.8785
+3473,3478,533-31-3,Oc1ccc2OCOc2(c1),Training,0,0,52,0.5834330941778786,38.69,34.229800000000004,2.5226248626113557,257.0281739221536,138.122,1.1209
+3474,3479,53340-16-2,N1=C4C=CC(C=C4(Oc2cc(N)c3ccccc3(c12)))=[N+](CC)CC,Training,1,0,120,0.2663613341463539,55.059999999999995,98.90040000000005,2.101840136399002,1088.9239324788148,318.40000000000015,3.480000000000002
+3475,3480,533-73-3,Oc1ccc(O)c(O)c1,Training,1,0,48,0.3557004899606234,60.69,31.436399999999995,3.1716780304409156,219.54299954784685,126.11099999999998,0.8033999999999999
+3476,3481,534-07-6,O=C(CCl)CCl,Training,1,1,36,0.5060148575034207,17.07,26.446999999999996,2.98816088213427,46.75488750216347,126.97000000000001,1.0331000000000001
+3477,3482,534-22-5,o1cccc1C,Training,0,0,32,0.4628605847396023,13.14,23.44499999999999,3.049648321313926,107.4988650600484,82.102,1.5880200000000002
+3478,3483,53-43-0,O=C2CCC3C4CC=C1CC(O)CCC1(C)C4(CCC23(C)),Training,0,0,116,0.6868426969908572,37.3,82.71680000000005,1.6923546593637233,507.69574308017087,288.43100000000004,3.8792000000000035
+3479,3484,5343-65-7,O=C(Nc1ccc(cc1)C)CBr,Training,0,0,64,0.7730046811248167,29.1,53.60270000000002,2.644931667068772,268.36195376207496,228.08899999999994,2.3284200000000004
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+3481,3486,534-52-1,O=[N+]([O-])c1cc(c(O)c(c1)C)[N+](=O)[O-],Training,0,0,74,0.5720654169940127,106.51000000000002,46.15260000000001,3.4275044779343173,414.78633577032497,198.134,1.5170199999999998
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+3485,3490,535-11-5,O=C(OCC)C(C)Br,Training,1,1,48,0.4740866782166641,26.3,35.022,3.329150037184473,80.49785513558373,181.029,1.3329
+3486,3491,53527-28-9,O=CC2=CCC3C4(C)(CCC1C(C)(C)CCCC1(C)C4(CC(OC(=O)C)C3(C)(C2(C=O)))),Training,0,0,172,0.4374774234743459,60.440000000000005,120.1460000000001,1.8534222876682998,812.0540745849213,428.61300000000017,5.537300000000005
+3487,3492,53552-01-5,O=CNc2ccc(Oc1ccc(cc1Cl)Cl)cc2,Training,1,1,92,0.8462500682640565,38.33,72.66470000000002,2.151992586092112,555.417744186994,282.126,4.354000000000002
+3488,3493,535-80-8,O=C(O)c1cccc(c1)Cl,Training,0,0,52,0.675780363757627,37.3,38.41130000000001,3.069899265759275,257.53794892648057,156.56799999999998,2.0382
+3489,3494,536-33-4,n1ccc(cc1CC)C(N)=S,Training,0,0,58,0.6725460532160716,38.91,49.502400000000016,3.00588921891474,270.54949758389114,166.24899999999997,1.2782
+3490,3495,536-90-3,O(c1cccc(N)c1)C,Training,1,1,48,0.5706913849970715,35.25,37.406400000000005,2.936866102336592,197.86256853719752,123.155,1.2774
+3491,3496,53693-66-6,c1cc(ccc1c2ccc(cc2)N(CC)CC)c3ccc(cc3)N(CC)CC,Training,1,0,146,0.4332423903475475,6.48,124.43600000000008,1.7607958073309544,765.9444820470173,372.5560000000001,6.713000000000007
+3492,3497,53693-67-7,Nc1ccc(cc1)c2ccc(cc2)c3ccc(cc3)c4ccc(N)cc4,Training,0,1,126,0.4609036898837224,52.04,111.57480000000001,1.5731166480786358,910.7647883303563,336.4380000000001,5.852000000000004
+3493,3498,53693-68-8,c1cc(ccc1c2ccc(cc2)c3ccc(cc3)N(CC)CC)c4ccc(cc4)N(CC)CC,Training,0,1,174,0.25361089598449005,6.48,149.87199999999976,1.4708421098271367,1052.8771153851312,448.6540000000003,8.380000000000006
+3494,3499,53-70-3,c1ccc5c(c1)ccc4cc3c(ccc2ccccc23)cc45,Training,1,1,102,0.23019675559525438,0.0,96.46600000000004,2.0194254860819045,1070.7978172121288,278.354,6.299400000000003
+3495,3500,53716-49-7,O=C(O)C(c1ccc3c(c1)[nH]c2ccc(cc23)Cl)C,Training,0,1,96,0.7364039910992084,53.089999999999996,76.86550000000003,2.2432169557830854,791.2908570767097,273.71900000000005,4.162600000000002
+3496,3501,53737-95-4,O1C=CC2c3ccccc3(OC12),Training,1,1,60,0.5777656460365975,18.46,43.82400000000003,2.142948892947355,343.4467454636433,160.17199999999997,2.0326
+3497,3502,53757-28-1,O=[N+]([O-])c1oc(cc1)c2ncsc2,Training,1,1,66,0.5454825071155637,69.17,46.47040000000002,2.386117509806487,420.63934263790065,196.18699999999998,2.3113
+3498,3503,53757-29-2,O=[N+]([O-])c1oc(cc1)c2nc(C)sc2,Training,1,1,72,0.5639258570775536,69.17,51.20740000000002,2.3789367851448926,474.394700670178,210.21399999999997,2.619720000000001
+3499,3504,53757-30-5,O=CNc2nc(C=Cc1oc(cc1)[N+](=O)[O-])cs2,Training,1,1,92,0.5080641019134162,98.27000000000001,66.09110000000001,2.083459229756768,601.7945842101661,265.25,2.383000000000001
+3500,3505,537-92-8,O=C(Nc1cccc(c1)C)C,Training,0,1,58,0.6492858960302428,29.1,45.48270000000002,2.790931451480763,268.0201725709103,149.19299999999996,1.95342
+3501,3506,53797-18-5,O=C2c4cccc(O)c4(C(=O)c3c(OC1OC(CO)C(O)C(O)C1(O))cccc23),Training,1,1,152,0.3842963946125415,153.75,95.809,1.7391999653734134,983.9123205330154,402.355,-0.6537000000000006
+3502,3507,5381-78-2,O=[N+]([O-])c2ccc1c(ncn1C)c2,Training,0,1,66,0.48924458617392336,60.96,47.368400000000015,2.6972319726965024,475.1939168291226,177.163,1.4814999999999998
+3503,3508,5381-79-3,O=[N+]([O-])c1ccc2ncn(c2(c1))C,Training,1,1,66,0.48924458617392336,60.96,47.36840000000002,2.724812383846014,475.1939168291226,177.16299999999998,1.4814999999999998
+3504,3509,538-23-8,O=C(OCC(OC(=O)CCCCCCC)COC(=O)CCCCCCC)CCCCCCC,Training,1,0,194,0.09026518387328009,78.9,131.92600000000004,4.367407054130715,461.0032508161705,470.6910000000005,7.0661000000000085
+3505,3510,538-41-0,N(=Nc1ccc(N)cc1)c2ccc(N)cc2,Training,1,1,80,0.5916277966742379,76.75999999999999,65.88480000000001,2.145171926717264,437.932139382656,212.256,3.266400000000001
+3506,3511,5385-75-1,c1ccc3c(c1)cc4c2ccccc2c5c6ccccc6(cc3c45),Training,1,1,110,0.21382716694563916,0.0,103.39000000000003,2.007900821276399,1291.9954058134356,302.37600000000003,6.793600000000003
+3507,3512,53-86-1,O=C(O)Cc3c1cc(OC)ccc1n(C(=O)c2ccc(cc2)Cl)c3C,Training,0,0,128,0.7678065120522065,68.53,95.74730000000002,2.2323717333782787,973.2479304430422,357.7930000000001,3.9273200000000035
+3508,3513,538-74-9,c1ccc(cc1)CSCc2ccccc2,Training,0,1,76,0.7374218696001749,0.0,67.88300000000004,1.8095807579695855,341.09815896246135,214.333,4.120000000000003
+3509,3514,538-75-0,C(=NC1CCCCC1)=NC2CCCCC2,Training,0,0,84,0.6134805030612402,24.72,63.60900000000005,1.7724612352891178,206.92050794163038,206.33299999999997,3.825700000000003
+3510,3515,5392-40-5,O=CC=C(C)CCC=C(C)C,Training,0,0,62,0.34370646240024516,17.07,48.48600000000003,3.625759660368785,171.3117986128446,152.237,2.878000000000001
+3511,3516,53940-49-1,Oc1ccc(cc1(OC))CC2OC2,Training,1,1,70,0.7135951695115432,41.99,48.10280000000003,2.158767704922831,305.03820984224546,180.20299999999997,1.3420999999999998
+3512,3517,53-94-1,ONc2ccc3c1ccccc1Cc3(c2),Training,1,1,74,0.587484920120555,32.26,60.09320000000002,2.1818027616860505,519.69444448744,197.23699999999997,3.0589000000000013
+3513,3518,53950-62-2,O=CN(O)c1ccc(c(c1)Cl)Cl,Training,0,0,64,0.4578985252667222,40.540000000000006,46.79150000000001,3.0381059024067825,303.4578919800297,206.028,2.3454000000000006
+3514,3519,53-95-2,O=C(N(O)c2ccc3c1ccccc1Cc3(c2))C,Training,1,1,90,0.5235519120251784,40.540000000000006,69.63050000000003,2.058450680301562,634.1407700417452,239.27399999999997,2.999900000000002
+3515,3520,53956-04-0,O=C(O)C7OC(OC1C(OC(C(=O)O)C(O)C1(O))OC3CCC4(C)(C5C(=O)C=C2C6CC(C(=O)O)(C)CCC6(C)(CCC2(C)C5(C)(CCC4(C3(C)(C))))))C(O)C(O)C7(O),Training,0,0,326,0.17121034762756882,267.03999999999996,199.43839999999946,1.1738525001509732,1731.1441342741448,822.9419999999999,2.245600000000002
+3516,3521,5397-37-5,O=[N+]([O-])c1ccc3c(c1)c2ccccc2C3,Training,1,1,78,0.4580063651015218,43.14,61.33840000000003,2.2203264139998535,590.2365074060834,211.21999999999997,3.1660000000000013
+3517,3522,540-49-8,C(=CBr)Br,Training,1,1,24,0.5435004110474422,0.0,26.993999999999996,2.549193338482967,19.219280948873624,185.846,2.2474
+3518,3523,540-51-2,OCCBr,Training,1,1,26,0.5017509953790179,20.23,20.879799999999996,1.9747448713915894,8.0,124.965,0.3736
+3519,3524,5405-41-4,O=C(OCC)CC(O)C,Training,0,0,54,0.5623769753174953,46.53,32.930799999999984,3.2711920488970017,88.30376252379817,132.159,0.3204000000000001
+3520,3525,5405-53-8,O=[N+]([O-])c2ccc3c1ccc(cc1Cc3(c2))[N+](=O)[O-],Training,1,1,94,0.520386281365871,86.28,67.99280000000002,2.1011972719451757,663.0783106971865,256.217,3.074200000000001
+3521,3526,540-80-7,O=NOC(C)(C)C,Training,1,1,42,0.372158403692473,38.66,26.63299999999999,3.336809769016681,64.58027134782354,103.121,1.4829
+3522,3527,54083-22-6,O=C(NN=C(C)C3(O)(Cc1c(O)c4C(=O)c5cccc(OC)c5(C(=O)c4(c(O)c1C(OC2OC(C)C(O)C(N)C2)C3))))c6ccccc6,Training,1,1,246,0.1017247369344972,210.23,166.6787999999997,1.455501021314744,1797.484009810674,645.6650000000001,2.2458
+3523,3528,5408-55-9,O=[N+]([O-])c3ccc2c(oc1ccc(cc12)[N+](=O)[O-])c3,Training,1,1,94,0.5175755189960696,99.42,67.0288,2.3299192806751465,836.618584993866,258.18899999999996,3.402400000000001
+3524,3529,5410-97-9,O=[N+]([O-])c3ccc2c(oc1ccccc12)c3,Training,1,1,78,0.4588339118278573,56.28,60.374400000000016,2.409407788086353,699.6227880794761,213.192,3.494200000000001
+3525,3530,54-11-5,n1cccc(c1)C2N(C)CCC2,Training,0,0,64,0.6261518225795568,16.130000000000003,48.84200000000003,2.1945916577858466,245.27530899395387,162.23599999999996,1.8483
+3526,3531,5412-25-9,O=P(O)(OCC(CBr)Br)OCC(CBr)Br,Training,1,1,92,0.4123883731140621,55.760000000000005,74.74730000000002,3.8135223466218973,199.30857514984194,497.7400000000001,3.4368000000000016
+3527,3532,54150-69-5,O(c1ccc(N)c(OC)c1)C,Training,1,1,60,0.650857113073011,44.480000000000004,43.95840000000001,3.021543291114781,247.8474159248874,153.181,1.286
+3528,3533,541-59-3,O=C1C=CC(=O)N1,Training,1,1,36,0.40202799341337114,46.17,22.2897,2.759543614305127,131.76878450632645,97.07300000000001,-0.8010000000000002
+3529,3534,54-16-0,O=C(O)Cc2c[nH]c1ccc(O)cc12,Training,0,0,72,0.6730115735644503,73.32,51.30330000000002,2.5494126737496963,487.0728097407957,191.186,1.5006
+3530,3535,541-73-1,c1cc(cc(c1)Cl)Cl,Training,0,0,42,0.5285863388321962,0.0,36.46200000000001,3.077660437970554,166.38833891467198,147.004,2.9934000000000003
+3531,3536,5417-50-5,O=C(Nc1cnc2ccccc2(c1))C,Training,0,1,70,0.741315224108568,41.99,56.04670000000002,2.4574956097268665,479.42615539699864,186.214,2.1932
+3532,3537,5418-93-9,n1c(N)[nH]c2ccc(cc12)Cl,Training,0,1,56,0.6288112834438336,54.699999999999996,45.5161,2.8159631541870422,393.4850582454801,167.59899999999996,1.7984999999999998
+3533,3538,542-02-9,n1c(nc(nc1N)C)N,Training,0,0,48,0.4801759172022822,90.71,33.388799999999996,3.165670309917317,169.72019968705186,125.13500000000002,-0.6555800000000003
+3534,3539,5422-34-4,O=C(NCCO)C(O)C,Training,1,1,54,0.4374582005328141,69.56,31.77629999999999,3.275479121279178,92.2038970536883,133.147,-1.5243000000000002
+3535,3540,54235-20-0,O=[N+]([O-])c4c(O)cc3c1ccccc1c2cccc4(c23),Training,1,1,96,0.4150764441232693,63.370000000000005,76.69720000000002,2.2630208855439107,899.6077278045394,263.252,4.101000000000002
+3536,3541,542-56-3,O=NOCC(C)C,Training,1,1,42,0.3990486740455806,38.66,26.584999999999987,2.8099823316091586,53.65148445440323,103.121,1.3404
+3537,3542,542-85-8,C(=NCC)=S,Training,0,1,28,0.3444821787350851,12.36,25.566999999999993,2.9339686496662654,53.91340299823497,87.14699999999999,1.1091
+3538,3543,54292-59-0,OCCN(c2ccc(N=Nc1cnccc1)cc2)CCO,Training,0,0,110,0.7651049704515837,81.31,81.23960000000004,2.05614616510202,551.6461175004911,286.33500000000004,2.288
+3539,3544,54292-61-4,OCCN(c2ccc(N=Nc1cnccc1)c(c2)C)CCO,Training,0,0,116,0.7700865763216961,81.31,85.97660000000005,2.1658797830782106,610.7978004740407,300.3620000000001,2.5964200000000006
+3540,3545,54292-63-6,n2cccc(N=Nc1ccc(cc1)N(CC)CC)c2,Training,0,0,98,0.7444284538071325,40.85,78.41600000000004,2.0863390793582033,515.6016547805535,254.337,4.343200000000004
+3541,3546,54-31-9,O=C(O)c2cc(c(cc2(NCc1occc1))Cl)S(=O)(=O)N,Training,0,0,112,0.768936392874182,122.62999999999998,75.81920000000002,2.406625749127726,771.1955159056121,330.749,1.8907000000000003
+3542,3547,54357-08-3,O=[N+]([O-])c1ccc2cc(ccc2(c1))C,Training,1,1,70,0.5082749800477625,43.14,55.33940000000002,2.672415665122394,505.61373284730047,187.19799999999998,3.056420000000001
+3543,3548,543-67-9,O=NOCCC,Training,1,1,36,0.2947241080331184,38.66,22.037999999999993,2.488403771876112,37.774437510817336,89.09400000000001,1.0944
+3544,3549,5437-38-7,O=C(O)c1cccc(c1[N+](=O)[O-])C,Training,1,1,68,0.5545811672294876,80.44,44.79270000000001,3.427344204506424,372.4068180287228,181.14699999999996,1.6014199999999998
+3545,3550,544-16-1,O=NOCCCC,Training,1,1,42,0.3068770515611316,38.66,26.654999999999987,2.558780869327957,46.954453363209694,103.12100000000001,1.4845
+3546,3551,5443-49-2,O=CC(=Cc1ccccc1)Br,Training,1,1,56,0.5423590537409061,17.07,49.41000000000002,2.8717118913324144,264.15103906059477,211.05799999999996,2.6213000000000006
+3547,3552,54455-37-7,O=C1c2ccc(cc2(C(=O)N1CCl))[N+](=O)[O-],Training,1,1,82,0.25716559494543073,80.52,54.3164,2.557307326044616,514.2304913339291,240.60199999999998,1.3871
+3548,3553,544-63-8,O=C(O)CCCCCCCCCCCCC,Training,0,0,96,0.48835050387044804,37.3,68.71380000000005,2.9047075575882766,154.8143311431168,228.37599999999992,4.772100000000005
+3549,3554,5447-11-0,O=C(O)C(NC(=O)COc1cc(c(cc1Cl)Cl)Cl)CCSC,Training,0,0,122,0.6701502801145082,75.63000000000001,89.53250000000004,2.581621409016786,556.3318942078622,386.68400000000014,3.3481000000000023
+3550,3555,54484-90-1,O=C2c1ccccc1Sc3c(ccc(NCC[N+]([O-])(CC)CC)c23)CO,Training,1,1,138,0.3770064313443027,72.39,109.58990000000006,2.0598989863700923,979.854988063836,372.4900000000002,3.6733000000000033
+3551,3556,54484-91-2,[O-][N+](CC)(CC)CCn4nc2c1ccc(cc1Sc3c2c4(ccc3CO))Cl,Training,1,1,142,0.3751636107998659,61.11,109.80120000000004,1.8589515802615648,1014.1197377963093,403.9350000000002,4.668000000000005
+3552,3557,545-06-2,N#CC(Cl)(Cl)Cl,Training,1,1,34,0.47630585255168656,23.79,25.903,3.552734354515761,75.77443751081735,144.388,1.88018
+3553,3558,54522-52-0,OCC9OC(OCC(C)CCC7(OC)(OC6CC5C8CC=C4CC(OC3OC(CO)C(OC1OC(C)C(O)C(O)C1(O))C(O)C3(OC2OC(C)C(O)C(O)C2(O)))CCC4(C)C8(CCC5(C)C6C7(C))))C(O)C(O)C9(O),Training,0,0,426,0.08461476261515977,335.06,253.5535999999991,0.8540534472883232,1916.6892356138167,1063.2380000000005,-1.325599999999987
+3554,3559,54522-53-1,OCC9OC(OCC(C)CCC7(OC)(OC6CC5C8CC=C4CC(OC3OC(CO)C(O)C(OC1OC(CO)C(O)C(O)C1(O))C3(OC2OC(C)C(O)C(O)C2(O)))CCC4(C)C8(CCC5(C)C6C7(C))))C(O)C(O)C9(O),Training,0,0,432,0.07197330806463023,355.29,254.96539999999914,0.8714634063916726,1933.4017392978608,1079.2370000000005,-2.3531999999999775
+3555,3560,54556-98-8,O=C(OC1CCN(C)CC1)C(OCCC)(c2ccccc2)c3ccccc3,Training,0,0,144,0.6937242687137711,38.769999999999996,106.51800000000006,1.9808883190442803,669.4180239904894,367.48900000000003,3.994200000000003
+3556,3561,54567-09-8,N#Cc2cc(ccc2(N=Nc1ccc(cc1)N(CCO)CCO))[N+](=O)[O-],Training,1,1,134,0.4243543877580249,135.35000000000002,94.81400000000005,2.18233542265848,824.0371457768737,355.3540000000001,2.6728800000000015
+3557,3562,5460-35-5,O=C1C=C(N)c2ccccc2(C1(=O)),Training,1,1,64,0.5887544550264427,60.160000000000004,47.943900000000006,2.7179085954703854,432.3058156581232,173.171,0.7516000000000002
+3558,3563,54607-64-6,O=C(O)c3occ(c1ccccc1)c3(c2ccccc2),Training,0,0,98,0.7663509153336601,50.44,76.53930000000003,2.2488026153738145,727.4413879838897,264.28000000000003,4.3118000000000025
+3559,3564,5461-85-8,O=NN(C(=N)N[N+](=O)[O-])CC(C)C,Training,1,1,74,0.21757457205237504,111.69,45.19580000000002,4.147959187921841,216.2153978634197,189.17499999999998,0.3418699999999999
+3560,3565,5464-79-9,n1c(N)sc2cccc(OC)c12,Training,1,1,62,0.7285742310609612,48.14,50.58440000000002,2.7795504276400855,410.3501069254241,180.23199999999997,1.8871
+3561,3566,5466-84-2,O=C1OC(=O)c2cc(ccc12)[N+](=O)[O-],Training,1,1,70,0.2860042006820723,86.51,42.8424,2.6076190147194995,464.79948506711423,193.11399999999998,0.9054
+3562,3567,546-80-5,O=C1CC2(CC2(C1C))(C(C)C),Training,0,0,62,0.5629498098503591,17.07,44.16600000000002,2.1958602485706944,206.91831683475922,152.23699999999997,2.2576
+3563,3568,546-88-3,O=C(NO)C,Training,1,0,30,0.30133300938287955,49.33,15.603200000000001,2.8473789230876716,42.91260938324327,75.06700000000001,-0.4883000000000004
+3564,3569,5470-37-1,O=C(O)C3NC(c2[nH]c1ccccc1c2C3)C,Training,0,0,88,0.6998696580235105,65.12,64.97720000000001,2.1624135563929454,588.1170294749016,230.267,1.8277999999999999
+3565,3570,54755-20-3,O=[N+]([O-])c2cccc1cc(ccc12)C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.812393942338178,505.61373284730047,187.19799999999998,3.056420000000002
+3566,3571,54755-21-4,O=[N+]([O-])c2cccc1ccc(cc12)C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.8378456171703186,505.61373284730047,187.19799999999998,3.056420000000001
+3567,3572,54779-53-2,n1ccc3c(c1)c(c2c4cc(N)ccc4([nH]c2c3C))C,Training,1,1,98,0.46874198219962515,54.699999999999996,84.99210000000002,2.36267537609087,979.9468244572546,261.328,4.068340000000002
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+3613,3619,55520-40-6,O=C(O)C(N)Cc1ccc(O)cc1,Training,0,0,70,0.6277204469356521,83.55,47.42200000000002,2.641763904889644,294.23305328030176,181.191,0.3465999999999995
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+3615,3621,55556-85-9,O=NN1CCCC(O)C1,Training,1,1,52,0.5129291486704721,52.900000000000006,32.60879999999999,2.310570132500946,107.13111721021242,130.147,0.12450000000000011
+3616,3622,55556-88-2,O=NN1CC(N(N=O)CC1C)C,Training,1,1,68,0.5761366238694804,65.34,43.92600000000003,2.6023299133983055,166.3868987998214,172.188,0.7438
+3617,3623,55556-91-7,O=NN1CCC(=O)CC1,Training,1,1,50,0.4780452254188568,49.74,31.608999999999988,2.3372734121311263,124.919684538544,128.131,0.3327000000000001
+3618,3624,55556-92-8,O=NN1CC=CCC1,Training,1,1,44,0.3731138272637754,32.67,31.12499999999999,2.3714157955008353,110.99629734317608,112.13199999999999,0.9297000000000001
+3619,3625,55556-93-9,O=NN1CCC(O)CC1,Training,1,1,52,0.5129291486704721,52.900000000000006,32.60879999999999,2.255115324010933,99.13111721021241,130.147,0.1245
+3620,3626,55556-94-0,O=NN1CCN(N=O)C(C)C1,Training,1,1,62,0.543875950085329,65.34,39.33100000000001,2.462637994593921,162.56140738249672,158.161,0.35530000000000006
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+3625,3631,5557-27-7,O=C1c3c(O)ccc(OC)c3(Oc2cc(OC)cc(OC)c12),Training,1,1,114,0.7494239594994165,78.13000000000001,81.31080000000004,2.5749668125232548,925.446615834498,302.28200000000004,2.6776
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+3628,3634,55610-00-9,O=C2Nc3cc1ccccc1c4c5OCOc5(cc2c34),Training,1,1,96,0.6330005007217929,47.56,75.53020000000004,2.1275268999431116,930.042344628715,263.25199999999995,3.2874000000000008
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+3632,3638,55691-69-5,O=[N+]([O-])c4ccc2c1ccccc1c3ccc(c4(c23))[N+](=O)[O-],Training,1,1,106,0.4067617049069634,86.28,81.68680000000003,2.258002478257131,919.0975196627454,292.25,4.303600000000002
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+3639,3645,55792-21-7,O=C(OCCN1CCCCC1)Nc2ccccc2(OCCCCCCC),Training,0,0,146,0.5584141822154451,50.8,105.95770000000007,1.6735024681624393,515.7325831402242,362.5140000000003,5.070200000000005
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+3651,3657,56-05-3,n1c(nc(cc1Cl)Cl)N,Training,0,0,48,0.5886371447422314,51.8,36.4644,3.165670309917317,174.5749526593252,163.99499999999998,1.3656
+3652,3658,56183-12-1,OC4c3cccc2ccc1cccc(c1c23)C4(O),Training,0,0,88,0.5887893889724674,40.46,71.37360000000002,2.359231064311487,709.7479180477756,236.26999999999998,3.0734000000000017
+3653,3659,56183-24-5,OC3c4ccccc4(c2ccc1ccccc1c2C3(O)),Training,0,0,98,0.6497155282679522,40.46,79.30360000000003,2.136738276255657,807.3773254778289,262.308,3.5872000000000024
+3654,3660,56-18-8,NCCCNCCCN,Training,0,0,56,0.416527485911045,64.07,40.212500000000006,2.595082706793886,41.567631415296866,131.22299999999998,-0.7263999999999986
+3655,3661,56211-40-6,O=C(NC(C)C)NS(=O)(=O)c2cnccc2(Nc1cccc(c1)C),Training,0,0,128,0.7708144759661694,100.19000000000001,92.68790000000003,2.2883466603467544,834.721096902533,348.42800000000005,2.5299200000000006
+3656,3662,56222-35-6,O=NN1CCC(O)C1,Training,1,1,46,0.47980834656750654,52.900000000000006,27.99179999999999,2.3167167127314605,96.03910001730776,116.11999999999999,-0.26560000000000006
+3657,3663,5623-11-0,O=C(O)c1c(N)cccc1(NC(=O)C),Training,1,1,74,0.6102668511712604,92.41999999999999,52.11740000000001,3.2083792987844033,387.6434985601214,194.19,0.9254
+3658,3664,56257-59-1,O=C6c5c(O)ccc4c2ccc(O)c3C(=O)C1OC1C(c23)C(O)(c45)CC6,Training,1,1,130,0.6273820821741297,107.36,88.40140000000002,1.8036949046268314,1070.4564695055874,350.32600000000014,1.9897999999999996
+3659,3665,56299-00-4,O=CC4(OC34(C(=O)C=C2C1OC1C(OC(=O)C)C(C)C2(C)C3))(C),Training,1,0,124,0.42799438350022306,85.5,77.47800000000004,1.7401381974294092,667.9947432985094,320.3410000000001,0.9672999999999994
+3660,3666,563-04-2,O=P(Oc1cccc(c1)C)(Oc2cccc(c2)C)Oc3cccc(c3)C,Training,0,0,134,0.48200363092194987,44.760000000000005,103.02750000000005,1.922794749427274,829.5625787062976,368.36900000000014,6.256760000000005
+3661,3667,563-12-2,O(CC)P(OCC)(=S)SCSP(OCC)(OCC)=S,Training,0,0,116,0.34347389826428293,36.92,95.12300000000005,4.359571541268355,279.3414689864336,384.4870000000002,5.005300000000004
+3662,3668,56316-37-1,O=NN(CCC)CCCC(=O)O,Training,1,1,70,0.46539535032348195,69.97,44.52880000000002,3.4361030881556247,149.58691465459873,174.2,1.2446000000000002
+3663,3669,5632-47-3,O=NN1CCNCC1,Training,1,1,46,0.47162525923597565,44.7,30.237699999999993,2.2166579722077144,79.35260810785708,115.13600000000001,-0.42700000000000005
+3664,3670,5633-20-5,O=C(OCC#CCN(CC)CC)C(O)(c1ccccc1)C2CCCCC2,Training,0,0,142,0.6005702926906202,49.769999999999996,103.43680000000006,2.0565547506887887,609.2696852458507,357.4940000000002,3.342900000000002
+3665,3671,56341-08-3,FC(F)(F)c1cc(cc(c1(N))Cl)C(O)CNC(C)(C)C,Training,0,0,114,0.7503125443072508,58.28,73.58190000000003,3.0493416941611864,483.730216961499,310.74700000000007,3.3625000000000016
+3666,3672,563-41-7,O=C(N)NN,Training,0,0,30,0.18646929432832585,81.14,16.9065,2.8473789230876716,42.1577218810798,75.071,-1.4716
+3667,3673,56355-17-0,O=C(O)C(c2ccc(Oc1nccs1)cc2)C,Training,0,0,88,0.9039409784041448,59.42,64.68080000000003,2.1027689714723516,492.9791099020906,249.29100000000003,3.1235000000000017
+3668,3674,56362-05-1,O=[N+]([O-])c1ccc(cc1(OP(=O)(OCC)NC(C)CC))C,Training,0,1,118,0.4452625337011343,90.7,80.58260000000004,3.112387649797255,549.3631990060858,316.29400000000004,3.814720000000002
+3669,3675,56-40-6,O=C(O)CN,Training,0,0,30,0.42117088793654706,63.31999999999999,16.6902,2.8473789230876716,42.91260938324327,75.06700000000001,-0.9702999999999999
+3670,3676,56413-75-3,O=[N+]([O-])c1ccccc1(NN),Training,1,1,58,0.3751167479723402,81.19,40.90650000000001,3.121219318886156,274.2848350774007,153.14099999999996,0.8803999999999998
+3671,3677,56438-59-6,O(c1ccc(cc1)CCC2OC2)C,Training,1,1,70,0.6578682089248313,21.759999999999998,51.055000000000035,1.8800615756519445,261.92369729722583,178.231,2.0266
+3672,3678,56-49-5,c1ccc5c(c1)ccc3c5(cc2ccc(c4c2c3CC4)C),Training,1,0,100,0.28942743473511123,0.0,91.10500000000005,2.07952095199302,1038.130433495046,268.3589999999999,5.553220000000004
+3673,3679,565-20-8,O=C(Nc1ccc(cc1)S(=O)(=O)c2ccc(N)cc2)C,Training,0,0,104,0.8466863071601987,89.26,77.05190000000003,2.344260332870976,720.0192623873418,290.344,2.0599999999999996
+3674,3680,56525-92-9,n1nc(OC)c2cccnc2(c1),Training,0,0,60,0.626400015282235,47.900000000000006,43.885000000000026,2.7909670297392637,396.9300352819674,161.16399999999996,1.0333999999999999
+3675,3681,56525-94-1,n1nc(OC)c2ncccc2(c1),Training,0,0,60,0.626400015282235,47.900000000000006,43.885000000000026,2.7909670297392637,396.9300352819674,161.164,1.0333999999999999
+3676,3682,56-53-1,Oc1ccc(cc1)C(=C(c2ccc(O)cc2)CC)CC,Training,0,0,104,0.7796984854737206,40.46,83.60960000000004,2.521517738794993,536.8202783238603,268.356,4.8286000000000024
+3677,3683,56548-64-2,O=C(Nc2cc(c(OC)cc2(N=Nc1c(cc(cc1Br)[N+](=O)[O-])[N+](=O)[O-]))N(CC)CC)C,Training,1,1,170,0.2662891611899378,152.57000000000002,122.48550000000007,2.6639877401405,1086.4632009719114,509.31700000000023,5.494100000000005
+3678,3684,56-55-3,c3ccc4cc2c(ccc1ccccc12)cc4(c3),Training,1,1,84,0.288354374686931,0.0,78.96000000000004,2.268265813130303,866.2526221384026,228.29399999999998,5.146200000000003
+3679,3685,565-64-0,O=C(O)C(CCl)Cl,Training,0,0,42,0.5830880177500019,37.3,27.996799999999997,3.3434170589539596,73.33515884998701,142.96900000000002,0.9172
+3680,3686,56-57-5,O=[N+]([O-])c1cc[n+]([O-])c2ccccc12,Training,1,1,70,0.29495596090703713,70.08,49.562400000000025,2.8831748525258547,510.38326813716645,190.15800000000002,1.3814
+3681,3687,56600-58-9,O=C2c3ccccc3(C(=O)c1c2(ccc(c1[N+](=O)[O-])CC)),Training,1,1,104,0.5341760476589799,77.28,75.78140000000002,2.3797775938599606,807.9194299387775,281.267,2.9326000000000016
+3682,3688,56602-33-6,n1nn(O[P+](N(C)C)(N(C)C)N(C)C)c2ccccc12,Training,0,1,110,0.7736002495417681,49.660000000000004,82.08900000000006,2.4689192297663123,560.3117268885673,297.32300000000004,1.2223000000000002
+3683,3689,56656-97-4,N#CC(=Cc1oc(cc1)Br)C(=O)OC,Training,0,0,72,0.4615431727750022,63.230000000000004,52.01400000000001,2.9603730356106865,413.9367117714949,256.05499999999995,2.1220799999999995
+3684,3690,5667-20-9,ONC=2NC=NC1=NC=NC1=2,Training,1,1,56,0.5031799039420619,86.72,36.2089,2.6633483078454794,331.71041851243854,151.129,0.10560000000000003
+3685,3691,56681-55-1,O=C(N(c1c(cccc1CC)CC)COC)CO,Training,0,1,100,0.7834677946737955,49.77,71.64580000000004,3.2766131919478854,381.7756193711608,251.3259999999999,1.7406000000000001
+3686,3692,56719-24-5,O=C(OC)C(=C(OP(=O)(OC)OC)c1cc(ccc1Cl)Cl)Cl,Training,0,0,122,0.3088713295235532,71.06,83.96050000000002,3.5075871283901976,637.748806283406,389.55499999999995,4.4913000000000025
+3687,3693,56719-41-6,O=C(OC)C(=C(OP(=O)(OC)OC)c1ccc(cc1Cl)Cl)Br,Training,0,0,122,0.28126709880850803,71.06,87.03450000000004,3.472534574618769,640.5036937855695,434.006,4.647400000000003
+3688,3694,56-72-4,O=C2Oc1cc(OP(OCC)(OCC)=S)ccc1C(=C2Cl)C,Training,0,0,120,0.5593356676649471,57.900000000000006,90.39600000000003,2.4320213745926904,778.6322379127124,362.771,4.4311200000000035
+3689,3695,56-75-7,O=C(NC(CO)C(O)c1ccc(cc1)[N+](=O)[O-])C(Cl)Cl,Training,0,1,110,0.4090709280478973,112.70000000000002,72.56670000000001,2.821158149823159,480.20675753303044,323.13199999999995,0.9089999999999998
+3690,3696,5679-89-0,O=[N+]([O-])c2cc(N=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])C)ccc2C,Training,0,0,118,0.3639139604555908,124.71000000000001,81.04220000000002,2.4418466782093518,831.912493409467,316.2730000000001,4.045540000000003
+3691,3697,56803-37-3,O=P(Oc1ccccc1)(Oc2ccccc2)Oc3ccc(cc3)C(C)(C)C,Training,0,0,140,0.4489661731449895,44.760000000000005,107.51650000000005,1.8587929384863013,855.0526320420856,382.39600000000013,6.629000000000005
+3692,3698,56-81-5,OCC(O)CO,Training,0,0,38,0.3814944322102413,60.69,20.1784,2.7541847860376616,25.219280948873624,92.09400000000001,-1.6681000000000001
+3693,3699,56856-83-8,O=NN(C)COC(=O)C,Training,1,1,52,0.23666608524796656,58.970000000000006,30.19099999999999,3.264770519247031,114.38037532843026,132.119,0.12019999999999997
+3694,3700,568-75-2,OCc3c1ccccc1c(c2c4ccccc4(ccc23))C,Training,1,1,102,0.3838887439156021,20.23,89.61980000000005,2.36530895271389,982.9549960983214,272.34700000000004,4.946920000000004
+3695,3701,56892-30-9,Oc2cc3ccc4cc1ccccc1c5ccc(c2)c3c45,Training,1,1,98,0.29257925528338974,20.23,89.31680000000004,2.1895313526681774,1119.5501677212192,268.31500000000005,5.442800000000003
+3696,3702,56892-33-2,Oc1cc4c5ccccc5(cc3ccc2cccc1c2c34),Training,1,1,98,0.2925792552833897,20.23,89.31680000000004,2.245944113672931,1138.300167721219,268.315,5.442800000000003
+3697,3704,56-93-9,c1ccc(cc1)C[N+](C)(C)C,Training,0,0,60,0.5647334091641918,0.0,48.17840000000004,2.6576609845322254,208.0644283534882,150.24499999999998,1.8928
+3698,3705,5694-00-8,O=C(N)C1OC1,Training,1,1,34,0.4112890013896534,55.620000000000005,18.934399999999997,2.3076098467926744,76.86238311218402,87.078,-1.1295000000000002
+3699,3706,569-57-3,O(c1ccc(cc1)C(c2ccc(OC)cc2)=C(c3ccc(OC)cc3)Cl)C,Training,0,0,138,0.5005017670153245,27.69,110.75100000000003,2.138491131461032,861.8471018927728,380.87100000000015,5.867800000000004
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+3701,3708,569-61-9,N=C1C=CC(C=C1)=C(c2ccc(N)cc2)c3ccc(N)cc3,Training,1,0,108,0.734748547099071,75.89,93.7375,2.1835591104632144,726.0788697398173,287.366,3.7986700000000004
+3702,3709,56980-94-0,O=C(c1cc(N)ccc1(OCC(O)CNC(C)(C)C))C,Training,0,0,112,0.5442377525370885,84.58000000000001,80.11640000000004,2.5921228890517933,466.6766970898735,280.368,1.5991999999999997
+3703,3710,56986-35-7,O=NN(CCCC)C(OC(=O)C)CCC,Training,1,1,88,0.27048635219271405,58.970000000000006,57.871000000000045,4.248011703748917,197.10652223979864,216.28099999999995,2.459200000000001
+3704,3711,56986-36-8,O=NN(COC(=O)C)CCCC,Training,1,1,70,0.26330922422890385,58.970000000000006,44.04200000000002,3.5229879076328428,149.58691465459873,174.19999999999996,1.2905
+3705,3712,57011-48-0,[N-]=[N+]=NCC(O)CN=[N+]=[N-],Training,1,1,54,0.3508884598018757,117.75000000000001,34.0328,3.515570079501987,157.43195019909115,142.12199999999999,0.9679
+3706,3713,57018-52-7,OC(C)COC(C)(C)C,Training,1,0,56,0.6110606270494343,29.46,37.3858,3.2807108400137506,71.4755611642712,132.203,1.1823000000000001
+3707,3714,570-24-1,O=[N+]([O-])c1cccc(c1(N))C,Training,1,1,58,0.37618304623671805,69.16,42.24580000000001,3.273580821537543,296.492089776386,152.15299999999996,1.4854199999999997
+3708,3715,57-06-7,C(=NCC=C)=S,Training,1,0,32,0.2883568789906168,12.36,30.089999999999993,3.0739155094200403,81.54887502163469,99.15800000000002,1.2752
+3709,3716,570-74-1,C2=C1CCCCC1(C)C3CCC4(C)(C(CCC4(C3(C2)))C(C)CCCC(C)C),Training,0,0,154,0.4259164481648038,0.0,117.6630000000001,1.4877857803983847,556.3856189774723,370.6650000000002,8.417900000000005
+3710,3717,57074-49-4,O=C1OC2CC(C)C3CC(OCC)OC(OCC)C3(C)(CC2(C1(=C))),Training,1,0,136,0.5814963729024242,53.99000000000001,89.03500000000007,1.919491986784454,503.9856154571134,338.44400000000013,3.2821000000000025
+3711,3718,57074-51-8,O=C1OC2CC(C)C3CC(O)OC(O)C3(C)(CC2(C1(=C))),Training,1,0,112,0.5154645855073497,75.99000000000001,70.22060000000005,1.9560467871423421,447.54482686786565,282.33600000000007,1.1937
+3712,3719,5709-67-1,O=[N+]([O-])c1nc2ccccc2([nH]1),Training,1,1,60,0.5106665276804901,71.82,42.74810000000001,2.6972540609797386,401.89903839344754,163.136,1.4710999999999999
+3713,3720,5709-68-2,O=[N+]([O-])c2nc1ccccc1n2C,Training,1,1,66,0.48924458617392336,60.96,47.368400000000015,2.8108156540972478,475.1939168291226,177.16299999999998,1.4814999999999998
+3714,3721,57-10-3,O=C(O)CCCCCCCCCCCCCCC,Training,0,0,108,0.4134897831112085,37.3,77.94780000000006,2.9229656090325555,177.93577382145608,256.4299999999999,5.552300000000006
+3715,3722,5711-16-0,O=C(O)C4(C)(CCCC1(C)(C4(CCC23(CC(C)C(O)(CCC12)C3)))),Training,0,0,130,0.7597114642501475,57.53,88.92960000000005,1.7414098018627744,545.0048756586318,320.47300000000007,4.234900000000004
+3716,3723,57117-24-5,O=NN(C(=O)ON=C(C)SC)C,Training,1,1,68,0.21748384556204906,71.33,46.66300000000002,3.935302063356529,206.11512574993122,191.212,1.4326
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+3718,3725,57-14-7,NN(C)C,Training,1,0,26,0.2992187840448161,29.259999999999998,17.874399999999998,2.3237900077244498,8.75488750216347,60.099999999999994,-0.5783
+3719,3726,571-60-8,Oc1ccc(O)c2ccccc12,Training,1,1,60,0.5800799709220194,40.46,47.27760000000002,2.946471324842402,380.60813525322834,160.172,2.2509999999999994
+3720,3727,57166-92-4,NCN,Training,1,0,20,0.3387469784398889,52.04,13.241800000000001,1.6329931618554523,2.7548875021634682,46.07299999999999,-1.1387
+3721,3728,57-27-2,Oc5ccc4c1c5(OC2C(O)C=CC3C(N(C)CCC123)C4),Training,0,0,110,0.7033474919154649,52.93,77.57660000000004,1.8445254467475667,670.2442212037415,285.34300000000013,1.1980999999999997
+3722,3729,57309-27-0,O=C2c1ccccc1N(O)C2(c3ccccc3)C,Training,0,1,90,0.8312401446264042,40.540000000000006,68.83200000000002,2.198022409631189,608.9004834580174,239.274,2.993900000000002
+3723,3730,57309-30-5,ON4c5ccccc5(C(=Nc1ccccc1)C4(c2ccccc2)(c3ccccc3)),Training,0,0,140,0.4787449714342432,35.83,117.0105,1.885585648307553,1115.4775316747189,376.45900000000006,5.960400000000004
+3724,3731,57309-38-3,ON3c4ccccc4(C(=Nc1ccccc1)C3(c2ccccc2)C),Training,0,0,118,0.727584398123559,35.83,97.14050000000002,1.9706202848204828,889.9819031406815,314.38800000000003,4.932000000000003
+3725,3732,57333-96-7,OC3C(=C)C(=CC=C1CCCC2(C)(C1CCC2(C(C)CCC(O)C(C)C)))CC(O)C3,Training,0,0,170,0.5310504106541727,60.69,123.96840000000007,1.7158112855570773,675.5956632424765,416.6460000000002,5.560600000000006
+3726,3733,573-56-8,O=[N+]([O-])c1cccc(c1(O))[N+](=O)[O-],Training,0,1,68,0.5485201907500785,106.51000000000002,41.41560000000001,3.3454419708109935,343.03740254995904,184.10699999999997,1.2086000000000003
+3727,3734,5737-13-3,O=C1c4cccc3ccc2cccc1c2c34,Training,1,1,74,0.40117164269017197,17.07,67.60200000000003,2.611800424223829,790.521534892919,204.22799999999998,3.3820000000000014
+3728,3735,57409-54-8,OCC(C)(CBr)Br,Training,0,1,44,0.715330689422464,20.23,38.21180000000001,3.3604351426960575,47.65148445440323,231.915,1.5272000000000001
+3729,3736,57-41-0,O=C1NC(=O)C(N1)(c2ccccc2)c3ccccc3,Training,0,0,94,0.8001945345367882,58.2,70.33840000000004,2.2308361050041703,583.6085383833889,252.27300000000002,1.7695999999999998
+3730,3737,574-25-4,OCC3OC(n2cnc1c2(ncnc1S))C(O)C3(O),Training,1,0,102,0.40132662500835337,113.52000000000001,65.58440000000002,2.0354351458697546,606.2272193160345,284.297,-1.2735000000000003
+3731,3738,57470-78-7,O=C(Nc1ccc(OCC(O)CNC(C)(C)C)c(c1)C(=O)C)N(CC)CC,Training,0,0,152,0.5740604449563793,90.89999999999999,107.64370000000005,2.7871583156014084,636.6042613427059,379.5010000000002,2.8907000000000016
+3732,3739,57470-96-9,O=C(Nc1ccc(OCC(O)CNC(C)(C)C)c(c1)C(=O)C)NCC,Training,0,0,140,0.5379638785989166,99.69,98.39940000000004,2.725465662096274,596.4742409679401,351.4470000000001,2.1583999999999994
+3733,3740,57471-01-9,O=C(Nc1ccc(OCC(O)CNC(C)(C)C)c(c1)C(=O)C)NC(C)(C)C,Training,0,0,152,0.546001987719233,99.69,107.61140000000006,2.7599823494177187,660.1711617808195,379.50100000000015,2.937000000000001
+3734,3741,57-47-6,O=C(Oc1ccc2c(c1)C3(C)(CCN(C)C3(N2C)))NC,Training,0,0,108,0.8482399591613493,44.81,78.31570000000005,2.0037327536679768,560.049649552965,275.3519999999999,1.7738999999999996
+3735,3742,57491-68-6,Nc1ccccc1SCSc2ccccc2(N),Training,1,1,88,0.5010363680811002,52.04,78.28980000000003,1.9253337901512144,454.78306509762695,262.403,3.6929000000000016
+3736,3743,57-50-1,OCC2OC(OC1(OC(CO)C(O)C1(O))(CO))C(O)C(O)C2(O),Training,0,1,136,0.2378914345193498,189.52999999999997,68.64140000000003,2.177269658127326,393.2032272794937,342.297,-5.395599999999993
+3737,3744,575-41-7,c1ccc2c(c1)cc(cc2C)C,Training,0,0,60,0.5476492453414697,0.0,53.422000000000025,2.892065045173516,413.30786619344804,156.22799999999995,3.456640000000002
+3738,3745,57541-73-8,O=NN1CCC(C(C1)Br)Br,Training,1,1,58,0.5391181025830777,32.67,47.41500000000002,2.39859276588968,132.81635834269238,271.94,1.9005
+3739,3746,575-43-9,c2cc1cc(ccc1c(c2)C)C,Training,0,0,60,0.5476492453414697,0.0,53.422000000000025,2.8630257936849905,413.3078661934481,156.22799999999995,3.456640000000002
+3740,3747,575-44-0,Oc1ccc2c(O)cccc2(c1),Training,1,1,60,0.6201010705740534,40.46,47.27760000000003,2.8630257936849905,421.10813525322834,160.172,2.2509999999999994
+3741,3748,57576-44-0,O=C(OC)C5c1cc6C(=O)c7cccc(O)c7(C(=O)c6(c(O)c1C(OC4OC(C)C(OC3OC(C)C(OC2OC(C(=O)CC2)C)C(O)C3)C(N(C)C)C4)CC5(O)(CC))),Training,1,1,316,0.22836136977761778,217.04999999999998,201.22719999999933,1.13450069639701,1938.8269480303738,811.8779999999998,3.157700000000001
+3742,3749,57-57-8,O=C1OCC1,Training,1,0,28,0.37438135799613564,26.3,15.576,2.3224050495909916,51.91340299823497,72.063,-0.06669999999999998
+3743,3750,57609-64-0,O=C(OCCCOC(=O)c1ccc(N)cc1)c2ccc(N)cc2,Training,0,1,120,0.4812026516544334,104.64,86.89080000000001,1.6708779869837946,606.49765209744,314.34100000000007,2.2549
+3744,3751,576-24-9,Oc1cccc(c1Cl)Cl,Training,0,0,48,0.6227397221533862,20.23,38.12680000000001,3.2478347337367026,202.0478870500104,163.003,2.6990000000000007
+3745,3752,57-63-6,C#CC3(O)(CCC2C4CCc1cc(O)ccc1C4(CCC23(C))),Training,0,0,116,0.7180018360911579,40.46,86.50660000000005,1.721704964542758,658.1613573389167,296.4100000000001,3.6126000000000023
+3746,3753,57-66-9,O=C(O)c1ccc(cc1)S(=O)(=O)N(CCC)CCC,Training,0,0,106,0.8330157421148818,74.67999999999999,72.74210000000004,3.0653305378819273,516.0791280132663,285.365,2.1955
+3747,3754,57-67-0,O=S(=O)(NC(=N)N)c1ccc(N)cc1,Training,0,0,76,0.2992027059784887,122.06,53.09,3.047486126365013,437.2625285893112,214.25000000000003,-0.5594299999999999
+3748,3755,57-68-1,O=S(=O)(Nc1nc(cc(n1)C)C)c2ccc(N)cc2,Training,0,0,100,0.8285267006028038,97.97,73.16890000000002,2.3305090060525346,675.9193645265302,278.337,1.47644
+3749,3756,57-71-6,O=C(C(=NO)C)C,Training,0,1,40,0.29549474478819515,49.66,25.576499999999992,3.8165829734656636,106.25742227201614,101.10499999999999,0.42549999999999993
+3750,3757,577-19-5,O=[N+]([O-])c1ccccc1Br,Training,1,1,52,0.5176565043579056,43.14,40.79640000000001,3.1529414466808685,261.67965837655686,202.00699999999995,2.3573000000000004
+3751,3758,577-33-3,Oc1ccc2c(O)c3ccccc3(cc2(c1(O))),Training,1,1,84,0.4074444347671861,60.69,66.44840000000002,2.5910755102638614,732.1916027576736,226.231,3.1098000000000003
+3752,3759,577-59-3,O=C(c1ccccc1[N+](=O)[O-])C,Training,0,1,62,0.381035510605069,60.209999999999994,43.10090000000002,3.2670761957037717,299.8297871570008,165.14799999999997,1.7973999999999999
+3753,3760,5776-38-5,Nc2c1ccccc1[n+](c3ccccc23)C,Training,1,1,78,0.4469417265024487,29.9,67.04240000000003,2.6661476433549485,569.6954776678717,209.272,2.3997
+3754,3761,5776-39-6,c1ccc3c(c1)cc2ccccc2[n+]3C,Training,1,1,72,0.38250909805589794,3.88,62.63000000000003,2.597968359562711,586.9571121386949,194.25699999999998,2.817500000000001
+3755,3762,577-71-9,O=[N+]([O-])c1ccc(O)cc1[N+](=O)[O-],Training,1,1,68,0.5485201907500785,106.51000000000002,41.41560000000001,3.3486590713152182,375.28740254995904,184.10699999999997,1.2086
+3756,3763,57775-29-8,OC(COc2cccc3[nH]c1ccccc1c23)CNC(C)C,Training,0,0,116,0.6553391910672782,57.28,90.44520000000004,1.8161625471085339,763.9631809253929,298.386,3.0588000000000015
+3757,3764,57781-14-3,O=C(OCC(=O)C3(OC(=O)C)(CCC2C4CC(F)C1=CC(=O)C(=CC1(C)C4(F)(C(O)CC23(C)))Br))C,Training,0,0,192,0.5262370826233467,106.97000000000001,122.64080000000004,1.8238229217798503,1072.0335619978919,559.4000000000002,3.4619000000000026
+3758,3765,578-06-3,n1c3ccccc3(cc2c1cccc2(N)),Training,1,1,72,0.44109773137968267,38.91,63.661400000000015,2.5325611743067444,644.1543647116672,194.237,2.970200000000001
+3759,3766,57816-08-7,c1ccc2c(c1)ccc5c2Cc4ccc3ccccc3c4C5,Training,1,1,104,0.3517650946568827,0.0,93.50800000000005,1.7793938607071806,939.2227961681523,280.37,5.488000000000004
+3760,3767,57-83-0,O=C4C=C3CCC1C(CCC2(C)(C(C(=O)C)CCC12))C3(C)CC4,Training,0,0,126,0.7013194281770768,34.14,90.88100000000006,1.669603312482063,588.6489897976311,314.46900000000005,4.723500000000005
+3761,3768,57830-29-2,Oc1ccc(cc1)CN(c2ncccc2)CCN(C)C,Training,0,0,106,0.8752253427570678,39.6,81.94780000000004,2.1150368066003717,511.0050109847871,271.36400000000003,2.3554000000000004
+3762,3769,57835-92-4,O=[N+]([O-])c4cc3cccc2ccc1cccc4(c1c23),Training,1,1,90,0.282303256286246,43.14,76.80040000000004,2.4249789291454245,943.2668646967957,247.253,4.492200000000002
+3763,3770,5784-45-2,n1nc(c2ccccc2(c1))Cl,Training,0,0,54,0.5972040822894839,25.78,44.548000000000016,2.913161163604861,381.2537713475522,164.59499999999997,2.2832
+3764,3771,578-46-1,O=[N+]([O-])c1ccc(cc1(N))C,Training,0,1,58,0.37618304623671805,69.16,42.24580000000001,3.1960696621259204,296.492089776386,152.15299999999996,1.4854199999999997
+3765,3772,578-54-1,Nc1ccccc1CC,Training,0,1,48,0.5634496399051838,26.02,40.23240000000002,3.0065240073265844,193.51405299160075,121.18299999999999,1.8312
+3766,3773,5786-21-0,N=2c4cc(ccc4(Nc1ccccc1C=2N3CCN(C)CC3))Cl,Training,0,1,118,0.8001222420891722,30.870000000000005,96.44370000000004,1.8304332090303406,763.3669443617505,326.83100000000013,3.7227000000000032
+3767,3774,578-66-5,n1cccc2cccc(N)c12,Training,1,1,54,0.5725810426076291,38.91,46.155400000000014,2.9131611636048604,376.7244463345713,144.17699999999996,1.817
+3768,3775,578-67-6,Oc1cccc2ncccc12,Training,1,0,54,0.6141033567827179,33.120000000000005,43.407800000000016,2.9131611636048604,378.7244463345712,145.161,1.9404
+3769,3776,578-68-7,n1ccc(N)c2ccccc12,Training,0,1,54,0.6120847733236583,38.91,46.155400000000014,2.91316116360486,376.7244463345713,144.177,1.817
+3770,3777,579-07-7,O=C(c1ccccc1)C(=O)C,Training,0,0,56,0.4696543696018401,34.14,41.45350000000002,2.9479803431399967,274.87402422213546,148.16099999999997,1.4583
+3771,3778,579527-03-0,N#Cc1ccc(cc1)CC23(C(=O)N(C(=O)N3(CC(N=[N+]=[N-])C2))c4cc(cc(c4)Cl)Cl),Training,1,1,150,0.29661942000937347,113.17,111.19299999999998,1.766871877233347,1118.72596772091,441.278,4.6977800000000025
+3772,3779,579-66-8,Nc1c(cccc1CC)CC,Training,1,1,60,0.6418508425408987,26.02,49.61040000000003,3.0951982523071,218.37813497601377,149.23699999999997,2.3936
+3773,3780,580-15-4,n1cccc2cc(N)ccc12,Training,0,1,54,0.5725810426076291,38.91,46.155400000000014,2.828901215620696,381.97444633457127,144.177,1.817
+3774,3781,580-16-5,Oc1ccc2ncccc2(c1),Training,0,0,54,0.6141033567827179,33.120000000000005,43.40780000000002,2.8289012156206956,383.9744463345712,145.161,1.9403999999999997
+3775,3782,580-17-6,n1cc(N)cc2ccccc12,Training,1,1,54,0.6120847733236582,38.91,46.155400000000014,2.8289012156206965,381.97444633457127,144.17699999999996,1.817
+3776,3783,580-18-7,Oc1cnc2ccccc2(c1),Training,0,0,54,0.6141033567827179,33.120000000000005,43.40780000000002,2.8289012156206956,383.9744463345712,145.16099999999997,1.9403999999999997
+3777,3784,580-19-8,n1cccc2ccc(N)cc12,Training,1,0,54,0.5725810426076291,38.91,46.155400000000014,2.828901215620696,381.97444633457127,144.177,1.817
+3778,3785,580-20-1,Oc1ccc2cccnc2(c1),Training,0,0,54,0.6141033567827179,33.120000000000005,43.40780000000002,2.8289012156206956,383.9744463345712,145.161,1.9403999999999997
+3779,3786,580-21-2,Fc1nc2ccccc2(cc1),Training,0,1,54,0.5211236867870965,12.89,41.701000000000015,2.828901215620696,383.9744463345712,147.152,2.373900000000001
+3780,3787,580-22-3,n1c(N)ccc2ccccc12,Training,1,0,54,0.6120847733236582,38.91,46.155400000000014,2.828901215620696,381.97444633457127,144.17699999999996,1.817
+3781,3788,5802-60-8,NN(Cc1ccccc1)Cc2ccccc2,Training,0,0,82,0.6231300554824448,29.259999999999998,66.31840000000004,1.922984044254818,369.7651793663836,212.29599999999996,2.562500000000001
+3782,3789,5806-00-8,O=[N+]([O-])c2cccc(N=[N+]([O-])c1cccc(c1C)[N+](=O)[O-])c2C,Training,0,0,118,0.3639139604555908,124.71000000000001,81.04220000000002,2.5369427770231385,831.912493409467,316.2730000000001,4.045540000000003
+3783,3790,58-08-2,O=C2c1c(ncn1C)N(C(=O)N2C)C,Training,0,0,74,0.5384628262372215,61.82,51.19600000000001,3.221281081084589,616.5285919942219,194.194,-1.0293
+3784,3791,581-28-2,n1c3ccccc3(cc2cc(N)ccc12),Training,1,1,72,0.44109773137968256,38.91,63.661400000000015,2.474936442179002,644.1543647116672,194.23699999999997,2.9702
+3785,3792,581-29-3,n1c3ccccc3(cc2ccc(N)cc12),Training,1,1,72,0.44109773137968256,38.91,63.661400000000015,2.474936442179002,644.1543647116672,194.23699999999997,2.9702
+3786,3793,58139-46-1,O=CNc1nc(cs1)c2ccc([N+](=O)[O-])s2,Training,1,1,82,0.5159143709568502,85.13,61.768100000000004,2.274112946065218,534.1258571732326,255.28,2.3481000000000005
+3787,3794,58139-48-3,O=[N+]([O-])c4ccc(c2nc1ccccc1c(n2)N3CCOCC3)s4,Training,1,1,122,0.5372535344801808,81.39,92.53740000000003,1.8485272311920158,905.2288439831212,342.38000000000017,3.1031000000000013
+3788,3795,58139-51-8,O=[N+]([O-])c2cc(c1nc(N)sc1)sc2,Training,1,1,72,0.6302790130432874,82.05,56.49380000000001,2.3789367851448926,476.74321621577474,227.27,2.362
+3789,3796,58139-52-9,O=CNc1nc(cs1)c2cc(cs2)[N+](=O)[O-],Training,1,1,82,0.5159143709568502,85.13,61.768100000000004,2.274112946065218,534.1258571732326,255.28,2.3481000000000005
+3790,3797,58139-53-0,O=C(Nc1nc(cs1)c2cc(cs2)[N+](=O)[O-])C,Training,1,1,88,0.6853803083687531,85.13,66.38510000000001,2.2374365110007863,575.558006564446,269.307,2.738200000000001
+3791,3798,58-14-0,n1c(nc(c(c1N)c2ccc(cc2)Cl)CC)N,Training,0,0,88,0.8561371493463948,77.82,70.6808,2.613511657499358,536.9470467453648,248.71699999999998,2.5237999999999996
+3792,3799,581-47-5,n1ccc(cc1)c2ncccc2,Training,1,0,58,0.6317729528591786,25.78,47.468000000000025,2.457149480139045,305.23158955045676,156.188,2.1436
+3793,3800,581-50-0,n1cccc(c1)c2ncccc2,Training,1,1,58,0.6317729528591786,25.78,47.468000000000025,2.457149480139045,305.23158955045676,156.18800000000002,2.1436
+3794,3801,581-64-6,n2c1ccc(N)cc1[s+]c3cc(N)ccc23,Training,1,1,78,0.35303929243614485,64.92999999999999,70.35780000000001,2.4397721399992816,637.2240090658609,228.3,2.8950000000000005
+3795,3802,581-89-5,O=[N+]([O-])c1ccc2ccccc2(c1),Training,1,1,64,0.49116998683506796,43.14,50.602400000000024,2.6860346638769905,465.18632858848656,173.171,2.748000000000001
+3796,3803,58-19-5,O=C2CC3CCC1C4CCC(O)C4(C)(CCC1C3(C)(CC2C)),Training,0,0,124,0.7278176746345383,37.3,87.28780000000006,1.6458817679492257,486.09891615235574,304.47400000000005,4.205100000000003
+3797,3804,58-27-5,O=C1C=C(C(=O)c2ccccc12)C,Training,1,1,64,0.5994834910884169,34.14,48.86000000000002,2.690389534648589,427.4713488019866,172.183,2.0119
+3798,3805,5831-16-3,c1ccc2c(c1)ccc3c2c(cc4c3CCC4C)C,Training,1,0,94,0.4688816627996116,0.0,82.92700000000005,2.2241002206253673,795.8470840263556,246.35299999999992,5.351120000000003
+3799,3806,58329-89-8,OCCN(c2ccc(N=Nc1ccc(cc1)C)cc2)CCO,Training,0,0,116,0.7713984866328484,68.42,88.18160000000005,2.0563469215647143,588.3060446706215,299.3740000000001,3.201420000000001
+3800,3807,58336-35-9,O=C1Oc2c(C=C1)cc4c3c2CCCN3CCC4,Training,1,0,92,0.6643633800604551,33.45,71.33900000000004,2.120405238053589,684.6884593403908,241.28999999999988,2.4918000000000005
+3801,3808,58337-49-8,O=C(O)C(NC(=O)C)CSCCCl,Training,1,1,76,0.5118729960834639,66.4,53.28550000000002,3.8080936033693424,188.576468174762,225.69699999999997,0.5477000000000001
+3802,3809,5836-85-1,O=C3c2cc(OC)c1c4ccccc4(ccc1c2CC3),Training,1,0,98,0.6162526227740005,26.3,80.65750000000004,2.243741937584164,862.0460214805196,262.30800000000005,4.130500000000002
+3803,3810,583-78-8,Oc1cc(ccc1Cl)Cl,Training,0,0,48,0.6227397221533862,20.23,38.12680000000001,3.1716780304409156,222.29788705001033,163.003,2.6990000000000007
+3804,3811,58430-01-6,n3c1cc(c(cc1c(c4ccc2ccccc2c34)C)C)C,Training,1,1,102,0.3052358705913932,12.89,90.96600000000005,2.2706649024867476,1012.4969221981514,271.363,5.466460000000004
+3805,3812,584-48-5,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])Br,Training,1,1,68,0.5918783213250876,86.28,47.45080000000001,3.267052212361692,378.8970430243959,247.00399999999996,2.2655000000000003
+3806,3813,5845-67-0,O=C1NC(C(=O)NC1)CC(C)C,Training,0,1,68,0.5946649686705492,58.2,44.39540000000002,2.489865723076995,201.23454122869495,170.21200000000002,-0.3529000000000009
+3807,3814,584-84-9,O=C=Nc1ccc(c(N=C=O)c1)C,Training,1,1,64,0.5076416678350385,58.86,46.74200000000002,3.2503947748121873,413.62292024010196,174.15899999999996,1.92962
+3808,3815,585-07-9,O=C(OC(C)(C)C)C(=C)C,Training,0,0,58,0.41263230500732573,26.3,40.659000000000006,3.9324159117142323,151.13075145540296,142.19799999999998,1.9042
+3809,3816,585-08-0,O2C3c4ccccc4(c1ccccc1C23),Training,1,1,72,0.584773793261462,12.53,58.44500000000003,2.087723276821366,495.03989348241106,194.233,3.4796000000000014
+3810,3817,58-54-8,O=C(O)COc1ccc(C(=O)C(=C)CC)c(c1Cl)Cl,Training,0,0,102,0.6438970754146427,63.6,73.35430000000002,3.0691765104126865,537.6899088554333,303.14099999999996,3.6057000000000023
+3811,3818,5855-71-0,O=[N+]([O-])c2cc(N)ccc2(c1ccc(N)cc1[N+](=O)[O-]),Training,1,1,102,0.4999059360603501,138.32,74.0116,2.7463520033016087,653.0986647406514,274.23600000000005,2.3343999999999996
+3812,3819,585-71-7,c1ccc(cc1)C(C)Br,Training,0,1,48,0.5892424022841078,0.0,43.78400000000002,2.8482340505977515,167.1823264341432,185.06399999999996,3.142500000000002
+3813,3820,5857-92-1,[O-][N+](=Nc1ccc(c(N)c1)C)c2ccc(c(N)c2)C,Training,1,1,98,0.37318351171048675,90.47,76.55820000000003,2.360725025179113,649.8893784000562,256.30899999999997,3.3935400000000007
+3814,3821,585-79-5,O=[N+]([O-])c1cccc(c1)Br,Training,1,1,52,0.5176565043579056,43.14,40.79640000000001,3.069899265759275,261.67965837655686,202.00699999999995,2.3573000000000004
+3815,3822,585-86-4,OCC(O)C(O)C(OC1OC(CO)C(O)C(O)C1(O))C(O)CO,Training,0,1,138,0.2029803994672465,200.52999999999997,70.83220000000004,2.8851034466565175,340.9686271756471,344.31300000000005,-5.761199999999992
+3816,3823,58-61-7,OCC3OC(n2cnc1c(ncnc12)N)C(O)C3(O),Training,0,1,102,0.49051986767922334,139.54,62.74480000000002,2.035435145869755,602.6175788415977,267.245,-1.979999999999999
+3817,3824,5862-77-1,O(c1ccc(N)cc1(N))CC,Training,1,1,60,0.6267701498923569,61.269999999999996,46.43580000000001,2.899778231413746,247.8474159248874,152.197,1.2497000000000003
+3818,3825,58632-95-4,N#CC(=NOC(=O)OC(C)(C)C)c1ccccc1,Training,0,1,94,0.34791286990007136,71.67999999999999,65.91100000000003,2.714243349309678,481.1980875305468,246.266,2.8659800000000013
+3819,3826,58658-11-0,n3c1ccccc1c(Nc2ccc(N)cc2)c4ccccc34,Training,1,1,106,0.4138853688774672,50.94,93.38610000000001,1.9725257808696763,905.0441921604436,285.35,4.713800000000002
+3820,3827,586-78-7,O=[N+]([O-])c1ccc(cc1)Br,Training,1,1,52,0.5176565043579056,43.14,40.79640000000001,3.003400684579817,244.42965837655686,202.00699999999995,2.3573000000000004
+3821,3828,58683-84-4,O=[N+]([O-])c2ccc(N=Nc1ccccc1)cc2(OC),Training,1,1,96,0.4711434176896301,77.09,70.26640000000003,2.269592640468479,611.7854362792872,257.249,4.018800000000002
+3822,3829,5869-25-0,Nc1ccc2c4cccc3cccc(c2(c1))c34,Training,1,1,80,0.4413478987641275,26.02,72.79040000000002,2.2608185570237374,751.3150785276883,217.271,4.069400000000002
+3823,3830,587-04-2,O=Cc1cccc(c1)Cl,Training,0,0,46,0.5466495888095015,17.07,36.83950000000001,3.0707606817835655,219.91106510209755,140.56899999999996,2.1525
+3824,3831,58718-48-2,O=[N+]([O-])c2cccc1nc3cccc(c3(nc12))[N+](=O)[O-],Training,1,1,98,0.4015305561084459,112.06,70.35280000000003,2.4830548438993,808.8400089999907,270.204,2.599400000000001
+3825,3832,5875-25-2,O=C(N)C(C)Br,Training,1,0,36,0.5375310363432878,43.09,27.583399999999997,3.2575861612334887,61.813537528125096,151.99099999999999,0.2551000000000001
+3826,3833,58775-50-1,O=C1c5c(O)ccc(c5(Oc2cc3OC4OC=CC4(O)(c3(c(O)c12))))CC=C(C)C,Training,1,1,148,0.45180404872513324,109.36000000000001,104.99240000000005,1.8617155030645527,1310.7106141020267,394.37900000000013,3.3161000000000023
+3827,3834,58-85-5,O=C1NC2CSC(CCCCC(=O)O)C2(N1),Training,0,1,90,0.4934781151921962,78.43,61.593200000000024,1.7030406543934973,297.78872926636205,244.31599999999997,0.7968
+3828,3835,58-90-2,Oc1c(cc(c(c1Cl)Cl)Cl)Cl,Training,0,0,60,0.5287193643960513,20.23,48.14680000000001,3.4555464838177836,270.8740242221354,231.893,4.005799999999999
+3829,3836,589-15-1,c1cc(ccc1CBr)Br,Training,0,0,48,0.6701713272142724,0.0,46.77300000000001,2.881555877646136,178.61256853719752,249.933,3.344000000000001
+3830,3837,589-17-3,c1cc(ccc1CCl)Br,Training,0,0,48,0.617873833985474,0.0,43.69900000000001,2.881555877646136,180.61256853719752,205.48199999999997,3.187900000000001
+3831,3838,58917-67-2,OC6c4cc1ccc2cccc3ccc(c1c23)c4C5OC5C6(O),Training,1,1,112,0.38635993495173776,52.989999999999995,88.72660000000002,1.8560082840322294,1084.6259786701926,302.329,3.431800000000002
+3832,3839,58917-91-2,Oc1cc6cccc5ccc2c(c1=C(O)C34(OC24(CCCC3)))c56,Training,1,1,114,0.6235147956738221,52.99,88.33560000000004,1.93724671148082,1083.394244693039,304.3450000000001,3.635600000000001
+3833,3840,589-18-4,OCc1ccc(cc1)C,Training,0,0,48,0.5979173456611149,20.23,37.101800000000004,2.8815558776461367,176.26405299160075,122.16699999999997,1.48732
+3834,3841,58-93-5,O=S(=O)(N)c1cc2c(cc1Cl)NCNS2(=O)(=O),Training,0,0,94,0.6544582690300506,118.35999999999999,61.63640000000001,2.7904937240424075,683.3155123780438,297.74500000000006,-0.3513000000000001
+3835,3842,58957-92-9,O=C1c5ccccc5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)C)CC4(OC3OC(C)C(O)C(N)C3)),Training,1,1,190,0.32834650610487814,176.61,123.7906,1.6648191484378903,1292.8054355459653,497.5000000000002,1.0202999999999995
+3836,3843,59-00-7,O=C(O)c1nc2c(O)cccc2(c(O)c1),Training,0,0,76,0.6531126670320804,90.65,52.03190000000002,2.853613540666951,550.3588400172699,205.169,1.3441999999999996
+3837,3844,590-17-0,N#CCBr,Training,0,0,22,0.4354466178463637,23.79,19.406999999999996,2.4330963097956353,35.79319390447952,119.94899999999998,0.90488
+3838,3845,590-21-6,C(=CCl)C,Training,1,1,24,0.41246466954180205,0.0,20.666999999999994,2.549193338482967,18.464393446710154,76.526,1.7588000000000001
+3839,3846,59-02-9,Oc2c(c(c1OC(C)(CCc1c2C)CCCC(C)CCCC(C)CCCC(C)C)C)C,Training,0,0,178,0.35864394447897774,29.46,134.3908,1.7382656832927925,705.4238777923209,430.7170000000003,8.840260000000004
+3840,3847,59-05-2,O=C(O)CCC(NC(=O)c1ccc(cc1)N(C)Cc2nc3c(nc2)nc(nc3(N))N)C(=O)O,Training,0,1,172,0.29472034504927447,210.54,118.26160000000004,1.6746221241939347,1201.0294275064248,454.44700000000023,0.2684000000000003
+3841,3848,5907-38-0,O=C1C(=C(N(N1c2ccccc2)C)C)N(C)CS(=O)(=O)O,Training,1,1,114,0.8430014275958216,84.54,80.56560000000005,2.588329530830611,805.9321855038761,311.36300000000006,0.7659199999999999
+3842,3849,5908-27-0,O=C1C=C(c2ccccc2(C1(=O)))S(=O)(=O)O,Training,1,1,82,0.5737425295681475,88.51,55.30510000000001,2.7951910152968695,624.3644037337875,238.21999999999997,0.6807000000000001
+3843,3850,590-86-3,O=CCC(C)C,Training,0,0,36,0.4618018883133206,17.07,25.518999999999988,2.8141442217770294,39.20310343869658,86.134,1.2314
+3844,3851,590-88-5,NCCC(N)C,Training,0,0,38,0.48587295687129933,52.04,27.320799999999995,2.6272148478988635,26.72905595320056,88.154,-0.3176000000000001
+3845,3852,5910-89-4,n1ccnc(c1C)C,Training,0,0,42,0.49689376298127774,25.78,31.505999999999986,3.1348615113454477,162.63833891467198,108.14399999999999,1.09344
+3846,3853,591-12-8,O=C1OC(=CC1)C,Training,0,0,38,0.4194343403362061,26.3,24.465999999999994,2.5803181355669738,124.04184397996642,98.10099999999998,0.8371
+3847,3854,591-17-3,c1cc(cc(c1)Br)C,Training,0,0,42,0.5624635581750883,0.0,38.87900000000001,3.077660437970554,164.24662946459569,171.03699999999998,2.7575200000000013
+3848,3855,591-27-5,Oc1cccc(N)c1,Training,1,1,42,0.4875296866315732,46.25,32.5192,3.077660437970554,168.38833891467198,109.128,0.9743999999999999
+3849,3856,591-35-5,Oc1cc(cc(c1)Cl)Cl,Training,0,0,48,0.6227397221533862,20.23,38.12680000000001,3.165670309917317,171.82006515716174,163.003,2.699
+3850,3857,59-14-3,O=C1NC(=O)N(C=C1Br)C2OC(CO)C(O)C2,Training,0,0,94,0.6458903815058055,104.55000000000001,60.64230000000002,2.3353960419232735,524.8528777321774,307.1,-1.0602000000000005
+3851,3858,591-87-7,O=C(OCC=C)C,Training,1,0,40,0.3775448287483148,26.3,26.829999999999988,2.9670528832697767,76.14933958998697,100.11699999999999,0.7355
+3852,3859,59229-75-3,O=[N+]([O-])c1cc(N)c(c(N)c1)C,Training,1,1,64,0.37116878927500957,95.17999999999999,46.6582,3.306535412749064,312.41852769827057,167.16799999999998,1.06762
+3853,3860,59230-81-8,c1ccc2c(c1)ccc4c2c(c3ccccc3c4C)CBr,Training,1,1,102,0.21595217856539364,0.0,96.32800000000005,2.3760990396040507,982.9549960983214,335.2439999999999,6.349520000000004
+3854,3861,592-41-6,C=CCCCC,Training,0,0,36,0.36350557388151317,0.0,29.721999999999984,2.488403771876112,29.01955000865387,84.16199999999999,2.3626000000000005
+3855,3862,59282-34-7,O=[N+]([O-])c1cc(OC)cc(c1(O))C(C)(C)C,Training,0,0,88,0.6198380621811589,72.60000000000001,60.01320000000003,3.4968613112856786,420.72811860574797,225.24399999999997,2.6065000000000005
+3856,3863,59283-76-0,O=[N+]([O-])c1cc(NO)c(c(c1)[N+](=O)[O-])C,Training,1,1,80,0.5810234168423455,118.54000000000002,49.897,3.4469225429954142,430.87898791820936,213.14899999999997,1.6125199999999997
+3857,3864,593-56-6,O(N)C,Training,0,0,20,0.37397768229049305,35.25,11.1964,1.6329931618554523,4.754887502163468,47.057,-0.49350000000000005
+3858,3865,593-60-2,C=CBr,Training,1,1,18,0.4398237132310551,0.0,19.123999999999995,2.1874960973678963,10.264662506490405,106.94999999999999,1.5248
+3859,3866,59405-51-5,N(=Nc1cc(c(N)cc1(N))C)c2cnccc2,Training,1,1,86,0.6100361057984933,89.64999999999999,68.41680000000001,2.3059146156171826,548.3224883150316,227.27100000000002,2.9698200000000012
+3860,3867,59405-62-8,O=C(Nc2cc(ccc2(N=Nc1cnccc1))N(C)C)C,Training,0,0,108,0.8726226221063642,69.95,83.48570000000004,2.3307234872205354,652.3684823602063,283.33500000000004,3.5214000000000025
+3861,3868,59405-70-8,N(=Nc1ccc(cc1)N(C)C)c2cnc(OC)cc2,Training,1,0,98,0.7855908901146411,50.08,75.73400000000004,2.083124249146663,546.6635769007231,256.30899999999997,3.571600000000002
+3862,3869,59405-72-0,N(=Nc1ccc(cc1)N(CC)CC)c2cnc(OCCCC)cc2,Training,1,0,128,0.4499657157618108,50.08,98.81900000000005,1.9477471064039533,618.8199768196412,326.4440000000001,5.522100000000005
+3863,3870,594-20-7,CC(C)(Cl)Cl,Training,0,1,32,0.4221420520617552,0.0,25.78499999999999,3.0237157840738176,20.36452797660028,112.98700000000001,2.2001
+3864,3871,594-42-3,C(Cl)(Cl)(Cl)SCl,Training,1,0,38,0.5229365572936219,0.0,33.734,3.1684898726705697,37.30296890880646,185.89000000000001,3.2011000000000003
+3865,3872,594-70-7,O=[N+]([O-])C(C)(C)C,Training,0,1,42,0.33959596980258466,43.14,26.74739999999999,3.7911184170869663,82.18080946738405,103.121,1.0615999999999999
+3866,3873,594-71-8,O=[N+]([O-])C(C)(C)Cl,Training,1,1,42,0.22789722122276404,43.14,26.926399999999994,3.7911184170869663,85.42592196522058,123.539,1.238
+3867,3874,594-72-9,O=[N+]([O-])C(C)(Cl)Cl,Training,1,1,42,0.24140889979353933,43.14,27.1054,3.7911184170869663,86.18080946738405,143.957,1.4143999999999999
+3868,3875,59-50-7,Oc1ccc(c(c1)C)Cl,Training,0,0,48,0.5897674587091335,20.23,37.85380000000001,3.1716780304409156,220.15617759993404,142.58499999999998,2.3540200000000002
+3869,3876,5956-39-8,O=CC1=CCC2C(C)(C)CCCC2(C)(C1(C=O)),Training,0,1,94,0.6876928204767676,34.14,67.54700000000004,2.450622155595548,367.1181094709745,234.33899999999994,3.163100000000002
+3870,3877,59-67-6,O=C(O)c1cnccc1,Training,0,0,46,0.5998689433499305,50.19,31.196299999999997,2.981454614041131,207.5576620543373,123.11099999999998,0.7797999999999999
+3871,3878,59702-31-7,O=C1NCCN(C1(=O))CC,Training,0,0,56,0.47554073534683566,49.410000000000004,35.2637,2.5954277335679676,167.13075145540293,142.15800000000002,-1.0353000000000003
+3872,3879,597-25-1,O=P(OC)(OC)N1CCOCC1,Training,0,0,72,0.6207689791325629,48.0,44.01650000000002,2.577214448630608,172.38689879982144,195.15499999999994,0.7195
+3873,3880,5975-78-0,O=C1OC(C)CCCC(=O)CCCCCc2cc(O)cc(O)c12,Training,0,0,126,0.7147878989312391,83.83000000000001,85.67910000000003,2.2301987715542246,579.0198314353454,320.385,3.4990000000000028
+3874,3881,59804-37-4,O=C(Nc1ncccc1)C3=C(O)c2c(ccs2)S(=O)(=O)N3C,Training,0,1,114,0.8677133347559903,99.59999999999998,81.68330000000003,2.060666749584648,871.6999809705909,337.38200000000006,1.6425
+3875,3882,598-38-9,OCC(Cl)Cl,Training,1,1,32,0.5003788036173845,20.23,22.579799999999995,2.5395388613593908,21.609640474436812,114.959,0.7824
+3876,3883,598-57-2,O=[N+]([O-])NC,Training,0,1,30,0.3348073817029261,55.17,16.054100000000002,2.8473789230876716,42.91260938324327,76.055,-0.6025
+3877,3884,59865-13-3,O=C1NC(C(=O)N(C)C(C(=O)N(C)C(C(=O)N(C)C(C(=O)N(C)C(C(=O)NC(C(=O)N(C)CC(=O)N(C)C(C(=O)NC(C(=O)N(C)C(C(=O)NC1C)CC(C)C)C(C)C)CC(C)C)CC)C(O)C(C)CC=CC)C(C)C)CC(C)C)CC(C)C)C,Training,0,0,486,0.14792471467331686,278.8,328.4446000000003,4.320268725023782,2325.0756756660257,1202.6349999999986,3.269000000000001
+3878,3885,59-87-0,O=C(N)NN=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,74,0.40818931541952863,123.76000000000002,45.67549999999999,2.6374009499939133,382.93815266453123,198.13799999999998,0.19000000000000006
+3879,3886,59-89-2,O=NN1CCOCC1,Training,1,1,46,0.4526699090278015,41.900000000000006,28.18699999999999,2.2166579722077144,80.10749561002055,116.12,0.0
+3880,3887,5989-27-5,C=C(C)C1CC=C(C)CC1,Training,0,0,56,0.48503449155951595,0.0,45.91200000000003,2.495412226862891,162.8771237954945,136.23799999999997,3.308900000000002
+3881,3888,59901-89-2,O=C(c1ccc2OCOc2(c1))C3OC3,Training,1,1,72,0.5176672357656962,48.06,46.635500000000015,1.9499517038518825,395.108513716102,192.17,0.9968
+3882,3889,59901-90-5,O=C(OC(c1ccc2OCOc2(c1))C3OC3)C,Training,1,1,90,0.5864325477235538,57.290000000000006,56.812000000000026,1.8711207650919623,452.2092521883251,236.22299999999996,1.4183
+3883,3890,59901-91-6,OC(c1ccc2OCOc2(c1))C3OC3,Training,1,1,74,0.7088648605975014,51.22,47.26480000000002,1.9104210733923028,359.1396728870035,194.18599999999998,0.8474999999999999
+3884,3891,599-07-5,O=C(O)C45(CCC2(C(=CCC1C3(C)(CC(O)C(O)C(C(=O)O)(C)C3(CCC12(C))))C5(CC(C)(C)CC4))(C)),Training,0,0,202,0.3825496862530512,115.06000000000002,136.0332,1.6196675547074264,1016.9093023613179,502.69200000000046,5.269100000000005
+3885,3892,59-92-7,O=C(O)C(N)Cc1ccc(O)c(O)c1,Training,1,0,76,0.5125069246930147,103.78,49.08680000000002,2.7772680269131413,350.6652327975252,197.19,0.05219999999999958
+3886,3893,599-64-4,Oc1ccc(cc1)C(c2ccccc2)(C)C,Training,0,0,82,0.8040228291516069,20.23,66.67680000000004,2.4257059111812187,454.5534417002411,212.292,3.7181000000000024
+3887,3894,599-79-1,O=C(O)c3cc(N=Nc1ccc(cc1)S(=O)(=O)Nc2ncccc2)ccc3(O),Training,0,0,142,0.5405882217196541,141.31,100.7296,1.7658464964858716,1130.3973704840953,398.4000000000001,3.7016000000000013
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+3889,3896,60032-80-6,c1ccc6c(c1)cc3c2ccccc2c4c3c6(cc5c4CCCC5),Training,1,1,114,0.28566733997214694,0.0,102.52600000000004,1.9161868586784674,1147.714893742806,306.40800000000013,6.519200000000005
+3890,3897,60-09-3,N(=Nc1ccc(N)cc1)c2ccccc2,Training,1,1,74,0.5789748062022296,50.739999999999995,61.47240000000002,2.152989281939098,446.0532648827137,197.241,3.6842000000000015
+3891,3898,60102-37-6,O=C2OCC3=CCN(C)CCC(OC(=O)C1(OC1(C))(CC(C)C2(O)C))C3(=O),Training,1,1,150,0.46926789805360725,105.66999999999999,93.72580000000005,1.9702289880994583,685.5456507833804,381.4250000000001,0.22070000000000106
+3892,3899,60110-37-4,O=C(NCc1ccccc1)C(C)(C)Br,Training,0,0,76,0.8268577929301866,29.1,61.294700000000034,2.46429105182416,302.81361205191496,256.143,2.4763
+3893,3900,60-11-7,N(=Nc1ccc(cc1)N(C)C)c2ccccc2,Training,1,0,86,0.7203844404050564,27.96,71.38700000000004,2.1154755667127603,486.6355887837592,225.29500000000002,4.168000000000003
+3894,3901,60129-60-4,O=C(O)C5(C)(CCCC2(C)(C5(CCC34(CC(=C)C(OC1OC(CO)C(O)C(O)C1(O))(CCC23)C4)))),Training,1,0,192,0.30435006270259285,136.68,121.53900000000007,1.4118830232150374,859.7386789662304,480.5980000000002,1.9791999999999994
+3895,3902,60129-67-1,O=[N+]([O-])c2ccc(N=Nc1ccc(cc1)N(CCO)CCO)c(c2)[N+](=O)[O-],Training,1,1,142,0.3876097869519923,154.70000000000002,96.75340000000004,2.226083696888437,833.6945439648748,375.3410000000002,2.7094000000000014
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+3897,3904,60197-68-4,O=C(OCC4OC(Oc1cccc2C(=O)c3cccc(O)c3(C(=O)c12))C(OC(=O)C)C(OC(=O)C)C4(OC(=O)C))C,Training,1,1,216,0.3203460031379962,178.02999999999997,133.99779999999996,1.7939292436711487,1428.0598093924602,570.5030000000003,1.6295
+3898,3905,602-01-7,O=[N+]([O-])c1cccc(c1[N+](=O)[O-])C,Training,1,1,68,0.5150434173626991,86.28,44.487800000000014,3.427344204506424,374.7553335743196,182.13499999999996,1.8114199999999998
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+3901,3908,602-38-0,O=[N+]([O-])c2cccc1cccc(c12)[N+](=O)[O-],Training,1,1,80,0.5722102808006498,86.28,57.256800000000005,2.924515991348853,545.6387652577181,218.16799999999998,2.656200000000001
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+3903,3910,60254-83-3,O=C(O)C(NC(=O)C(NC(=O)CNC(=O)CN)Cc1ccccc1)CC(C)C,Training,0,0,154,0.33936910902366485,150.62,103.16230000000006,2.8567554958444807,678.1613751608779,392.45600000000013,-0.5956999999999972
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+3935,3942,606-20-2,O=[N+]([O-])c1cccc(c1C)[N+](=O)[O-],Training,1,1,68,0.5150434173626991,86.28,44.487800000000014,3.3454419708109935,342.5053335743196,182.13499999999996,1.81142
+3936,3943,606-22-4,O=[N+]([O-])c1cccc(c1(N))[N+](=O)[O-],Training,1,1,68,0.4184019522317551,112.30000000000001,44.163199999999996,3.3454419708109935,343.89215552223243,183.12299999999996,1.0852
+3937,3944,606-31-5,O=Cc1c(cccc1[N+](=O)[O-])[N+](=O)[O-],Training,1,1,72,0.4114749481334959,103.35,45.1383,3.4705423562307702,382.2912232724884,196.11799999999997,1.3155000000000001
+3938,3945,606-35-9,O=[N+]([O-])c1cc(c(OC)c(c1)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,90,0.5747366517892077,138.65,52.95719999999999,3.625430618211918,477.18394073503225,243.13099999999997,1.4197999999999997
+3939,3946,606-37-1,O=[N+]([O-])c2cc1ccccc1c(c2)[N+](=O)[O-],Training,1,1,80,0.5722102808006498,86.28,57.256800000000005,2.8367375455945996,594.3887652577181,218.16799999999998,2.656200000000001
+3940,3947,60657-25-2,OC2C=Cc1c3ccc5cccc4ccc(cc1C2(O))c3c45,Training,1,1,106,0.4795480247802584,40.46,90.14660000000005,2.0519023101732183,1045.8298626920148,286.33000000000004,4.005100000000003
+3941,3948,6066-82-6,O=C1N(O)C(=O)CC1,Training,0,1,44,0.3425323761630293,57.61000000000001,22.873499999999996,2.7003421243315966,126.21884910034808,115.088,-0.47540000000000004
+3942,3949,6068-96-8,OOCCC,Training,1,1,32,0.390606564095757,29.46,18.871799999999997,2.19060968716425,12.36452797660028,76.095,0.8859999999999999
+3943,3950,607-30-7,ONc2cccc1ccccc12,Training,1,1,60,0.6267307753584164,32.26,49.35720000000002,2.7909670297392646,392.4656418352572,159.188,2.6409000000000002
+3944,3951,607-35-2,O=[N+]([O-])c2cccc1cccnc12,Training,1,1,64,0.49121081405272493,56.03,48.39740000000002,2.8309756583676706,462.6262845243794,174.159,2.143
+3945,3952,607-57-8,O=[N+]([O-])c2ccc3c1ccccc1Cc3(c2),Training,1,1,78,0.4580063651015218,43.14,61.33840000000003,2.1753580684432072,590.2365074060834,211.21999999999997,3.1660000000000013
+3946,3953,607-59-0,N(=Nc1cccc2ccccc12)c3ccc(cc3)N(C)C,Training,1,1,104,0.5942824331557091,27.96,88.89300000000004,1.9069985208696183,768.5802477036193,275.355,5.321200000000004
+3947,3954,60768-66-3,O=[N+]([O-])c2ccc1c(cns1)c2,Training,1,1,60,0.4989745387229236,56.03,46.274400000000014,2.676772326608393,437.653925895611,180.188,2.2044999999999995
+3948,3955,60784-46-5,O=NN(C(=O)NCCO)CCCl,Training,1,1,70,0.3655165308382802,82.0,43.705500000000015,3.76615173955013,154.8738711324017,195.606,-0.08949999999999991
+3949,3956,607-91-0,O(c1cc(cc2OCOc12)CC=C)C,Training,0,0,74,0.6866314906407247,27.69,53.01800000000002,2.4313271343440146,357.79543102653986,192.21399999999997,2.1524
+3950,3957,60-80-0,O=C1C=C(N(N1c2ccccc2)C)C,Training,0,0,72,0.6656235641878139,26.93,55.74700000000003,2.6880057866501375,493.75123770895794,188.23000000000002,1.4844199999999999
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+3952,3959,608-25-3,Oc1cccc(O)c1C,Training,0,0,48,0.5485235528461614,40.46,34.508599999999994,3.2478347337367026,197.9061775999341,124.13899999999998,1.4062199999999998
+3953,3960,608-71-9,Oc1c(c(c(c(c1Br)Br)Br)Br)Br,Training,0,0,66,0.39302429393032645,20.23,66.60679999999999,3.6035674514745475,230.20322477240757,488.59299999999996,5.204700000000001
+3954,3961,60872-63-1,O=C2OC1C(=O)C(=CCN(C)CC1)COC(=O)C(OC(=O)C)(C)C(C)CC2(=CC),Training,1,1,160,0.3670086748375761,99.21000000000001,103.75200000000007,2.475234407094507,754.1285688869322,407.46300000000014,1.5802999999999996
+3955,3962,60877-79-4,n2c1c(cc(cc1Cl)Cl)c(N)s2,Training,1,1,62,0.7383881969774914,38.91,54.052400000000006,2.9242062797931907,438.14415089128414,219.096,3.1853000000000007
+3956,3963,60877-83-0,Oc3ccc(C=Nc1c2cc(cc(c2(ns1))Cl)Cl)cc3,Training,1,1,100,0.6700877895568398,45.480000000000004,85.00080000000001,2.004396634484601,796.7891603187908,323.20400000000006,5.059300000000001
+3957,3964,60877-85-2,O=[N+]([O-])c3ccc(C=Nc1c2cc(cc(c2(ns1))Cl)Cl)cc3,Training,1,1,110,0.3666532723617519,68.39,89.99040000000001,1.9378193814669091,890.9893831648641,352.202,5.261900000000001
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+3959,3966,60877-90-9,Oc3ccccc3(C=Nc1c2ccccc2(ns1)),Training,0,1,88,0.7077329777168239,45.480000000000004,74.98080000000003,1.9988474987466853,718.3956658155007,254.31400000000002,3.752500000000002
+3960,3967,60877-91-0,Oc3cccc(C=Nc1c2ccccc2(ns1))c3,Training,1,0,88,0.7077329777168239,45.480000000000004,74.98080000000002,1.9686671818409875,718.3956658155007,254.31400000000002,3.752500000000002
+3961,3968,60877-92-1,Oc3ccc(C=Nc1c2ccccc2(ns1))cc3,Training,1,0,88,0.707732977716824,45.480000000000004,74.98080000000003,1.9415334700975961,701.1456658155008,254.31400000000005,3.7525000000000013
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+3966,3973,608-93-5,c1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,0,60,0.4510272795995529,0.0,51.49200000000001,3.455546483817783,267.2643837476986,250.339,4.9536
+3967,3974,60905-56-8,OC(Nc1c2ccccc2(ns1))C(Cl)(Cl)Cl,Training,0,1,86,0.6594924143832113,45.15,69.53950000000002,2.2822857153055605,496.7049092657186,297.59399999999994,3.3968
+3968,3975,609-15-4,O=C(OCC)C(C(=O)C)Cl,Training,0,0,58,0.35126872765994904,43.370000000000005,36.955000000000005,3.8231925262701543,143.92835504489477,164.58799999999997,0.7458999999999998
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+4007,4014,612-23-7,O=[N+]([O-])c1ccccc1CCl,Training,1,1,58,0.38948169603836147,43.14,42.65340000000002,3.121219318886156,274.8980131294879,171.58299999999997,2.3336000000000006
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+4043,4050,616-69-3,O=[N+]([O-])c1cc(c(c(c1)C)C)[N+](=O)[O-],Training,0,1,74,0.5349825702680807,86.28,49.22480000000001,3.4275044779343165,414.047460699165,196.16199999999998,2.11984
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+4144,4151,627-18-9,OCCCBr,Training,1,1,32,0.5597006103704939,20.23,25.49679999999999,2.19060968716425,14.364527976600282,138.992,0.7637
+4145,4152,627-30-5,OCCCCl,Training,1,1,32,0.49733307627124734,20.23,22.42279999999999,2.19060968716425,14.364527976600282,94.541,0.6075999999999999
+4146,4153,62-73-7,O=P(OC=C(Cl)Cl)(OC)OC,Training,1,0,66,0.5401938935101219,44.760000000000005,42.498500000000014,4.102541909313091,180.53107956171817,220.976,2.6804000000000006
+4147,4154,62783-49-7,O=NN(C)Cc1cccc(c1)C,Training,1,0,64,0.505952130608248,32.67,48.44100000000003,2.6890998247329745,272.98597477455394,164.20799999999997,2.10822
+4148,4155,62783-50-0,O=NN(C)Cc1ccc(cc1)C,Training,0,1,64,0.505952130608248,32.67,48.44100000000003,2.6400206596775657,255.7359747745539,164.208,2.10822
+4149,4156,628-02-4,O=C(N)CCCCC,Training,0,0,48,0.546650332315748,43.09,33.33639999999999,2.8223545542480317,70.92878689342031,115.176,1.0519999999999996
+4150,4157,6281-23-8,O=C(O)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,68,0.4324223533977618,93.58,42.03220000000001,2.804194668300063,364.714736008263,183.119,1.2856
+4151,4158,6281-32-9,OCc2ccnc1ccccc12,Training,0,1,60,0.6869222311376356,33.120000000000005,47.665800000000026,2.7909670297392646,392.4656418352572,159.188,1.7270999999999999
+4152,4159,62826-28-2,O(c1ccccc1CC2OC2)C,Training,1,1,64,0.6332811819054802,21.759999999999998,46.438000000000024,2.1514333525396574,266.2960188386611,164.20399999999998,1.6365
+4153,4160,6285-57-0,O=[N+]([O-])c1ccc2nc(N)sc2(c1),Training,1,1,66,0.5550570073696386,82.05,50.68680000000001,2.673911381671464,479.5424323747194,195.20299999999997,1.7866999999999997
+4154,4161,6285-68-3,n1c(N)[nH]c2ccc(cc12)C,Training,1,1,56,0.5922174122340765,54.699999999999996,45.24310000000001,2.8159631541870422,389.1365426998833,147.18099999999995,1.45352
+4155,4162,6287-38-3,O=Cc1ccc(c(c1)Cl)Cl,Training,0,0,52,0.5993581530925117,17.07,41.84950000000001,3.158901732156222,257.78306142431705,175.01399999999998,2.805900000000001
+4156,4163,628-94-4,O=C(N)CCCCC(=O)N,Training,0,0,58,0.5102778049489436,86.18,36.85679999999999,3.0550899395377584,117.70950594454669,144.174,-0.48260000000000053
+4157,4164,62895-88-9,O=C(OC(C)C)c1cc(ccc1(N))Cc2ccc(N)c(c2)C(=O)OC(C)C,Training,0,0,144,0.5948210456279321,104.64,105.61780000000005,2.2676779015236352,774.5704060631213,370.4490000000001,3.5722000000000023
+4158,4165,62902-12-9,N(=C1C=CC(C=C1)=C(c2ccc(cc2)NC)c3ccc(cc3)N(C)C)C,Training,0,0,132,0.8639179904077587,27.630000000000003,114.41870000000004,2.113390816543169,862.0551038113279,343.4740000000001,4.793000000000005
+4159,4166,629-14-1,O(CC)CCOCC,Training,1,0,50,0.5024136978092385,18.46,32.98599999999998,2.53006045688352,31.509775004326936,118.17599999999999,1.0594000000000001
+4160,4167,62966-21-6,O=C(O)C=CC(=O)CC(=O)C,Training,0,0,60,0.4650337847469217,71.44,37.0808,3.8779586826574968,214.48046338522258,156.137,0.1754
+4161,4168,6300-61-4,O=S(=O)(O)c2ccc(N=Nc1cc(c(N)cc1(N))C)cc2,Training,1,1,110,0.4555348446774066,131.13,80.43640000000002,2.2785058420638666,798.9112398437553,306.34700000000004,2.8215200000000014
+4162,4169,630125-99-4,n1cnc(cc1Oc2ccc(N)cc2)NC,Training,1,1,82,0.76633287742025,73.06,62.50710000000002,2.1649889470801353,469.66570815222946,216.244,1.8927999999999998
+4163,4170,630-16-0,C(C(Br)(Br)Br)Br,Training,1,1,38,0.5914525798483149,0.0,43.306000000000004,3.168489872670569,35.30296890880646,345.654,3.2198
+4164,4171,630-17-1,CC(C)(C)CBr,Training,0,1,38,0.4661280812361133,0.0,33.24899999999999,3.1684898726705697,33.69332843436965,151.047,2.4274000000000004
+4165,4172,63017-87-8,O=[N+]([O-])c2ccc1ccccc1c2C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.8139493599047367,505.61373284730047,187.19799999999998,3.056420000000002
+4166,4173,63018-94-0,c1ccc3c(c1)c(c2ccc(cc2c3C)C)C,Training,1,1,84,0.471699273640577,0.0,75.66500000000003,2.6301267768649694,720.7625908673879,220.31499999999994,4.918260000000004
+4167,4174,63019-38-5,Oc4cccc1c4(ccc2c3ccccc3(ccc12)),Training,1,1,90,0.4382001128928585,20.23,80.62480000000004,2.2938872818722986,922.3919838784873,244.293,4.851800000000003
+4168,4175,63019-39-6,Oc2ccc3ccc1c4ccccc4(ccc1c3(c2)),Training,1,1,90,0.43820011289285854,20.23,80.62480000000004,2.2802168469713417,922.3919838784873,244.293,4.8518000000000026
+4169,4176,63019-40-9,Oc2cccc3ccc1c4ccccc4(ccc1c23),Training,1,1,90,0.4382001128928585,20.23,80.62480000000004,2.3223093653220155,922.3919838784873,244.293,4.851800000000003
+4170,4177,63038-82-4,OC4c2cc5ccc1ccccc1c5(cc2C3OC3C4(O)),Training,1,1,104,0.4908991874831261,52.989999999999995,80.03460000000003,1.8626305706895758,886.1504003190425,278.307,2.840800000000002
+4171,4178,63041-76-9,c2cc3ccc4cc1cc(ccc1c5ccc(c2)c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000004,2.177136483389207,1116.7500637406124,266.34299999999996,6.045620000000004
+4172,4179,63041-77-0,c2cc3ccc4cc1c(cccc1C)c5ccc(c2)c3c45,Training,1,1,98,0.23641815777600877,0.0,92.38900000000004,2.211712753586288,1116.7500637406124,266.34299999999996,6.045620000000003
+4173,4180,63041-90-7,O=[N+]([O-])c4c5ccccc5(c1ccc2cccc3ccc4(c1c23)),Training,1,1,108,0.17366715134946126,43.14,94.30640000000004,2.2396253837391966,1224.6824987418458,297.31300000000005,5.645400000000003
+4174,4181,6309-46-2,O=C(Oc1ccc(cc1)CO)C,Training,0,0,64,0.5283455758864678,46.53,43.67380000000002,2.70914782437365,263.6070662599115,166.17599999999996,1.1041999999999998
+4175,4182,63104-32-5,c2cc3ccc4cc1cccc(c1c5ccc(c2)c3c45)C,Training,1,1,98,0.23641815777600875,0.0,92.38900000000004,2.2282792169185273,1116.7500637406124,266.34299999999996,6.045620000000004
+4176,4183,6312-87-4,O=C(Nc2ccc(Oc1ccccc1)cc2)C,Training,1,1,86,0.871814034248296,38.33,67.26170000000003,2.057573148701637,491.39047628592255,227.263,3.4373000000000022
+4177,4184,6313-44-6,O=C2c1ccccc1C(c3ccccc23)[N+](=O)[O-],Training,0,1,88,0.5672855869065998,60.209999999999994,65.15390000000001,2.333771428157134,614.0936095054086,239.23,2.597100000000001
+4178,4185,631-64-1,O=C(O)C(Br)Br,Training,1,1,36,0.6705579213453947,37.3,29.277799999999996,3.2575861612334887,60.568425030288566,217.844,1.1869
+4179,4186,63166-73-4,O=C(OC1CC6(OCC1(C))(OC4CC(C(=O)OC3OC(C)C(O)C(OC(=O)C)C3(OC2OC(C)C(O)C(OC(=O)C)C2(O)))CCC4C56(OC5)))C=Cc7ccccc7,Training,0,0,314,0.13850644691934158,224.56999999999996,190.9703999999994,1.0371460323210524,1665.680568051222,804.839,1.3125000000000062
+4180,4187,6317-18-6,N#CSCSC#N,Training,0,Non Predicted,36,0.3215945166813277,47.58,31.275,2.7683855790457867,95.08376481184145,130.197,1.37246
+4181,4188,632-21-3,O=C(C(Cl)Cl)C(Cl)Cl,Training,1,1,48,0.6178983309898237,17.07,35.995000000000005,3.65123357893369,79.28421251514428,195.85999999999999,2.1629000000000005
+4182,4189,63-25-2,O=C(Oc1cccc2ccccc12)NC,Training,1,1,76,0.7695670306859667,38.33,59.03170000000003,2.464953756163773,488.45103080120373,201.225,2.558
+4183,4190,6325-54-8,c1ccc4c(c1)ccc3c4(cc2ccccc2c3CCl),Training,1,1,96,0.23111691485368627,0.0,88.51700000000004,2.300527217114131,937.9563134380708,276.76599999999996,5.885000000000003
+4184,4191,632-79-1,O=C1OC(=O)c2c1c(c(c(c2Br)Br)Br)Br,Training,0,0,78,0.2523528670738498,43.370000000000005,66.988,2.9225689093555407,464.3436252723838,463.70099999999996,4.0472
+4185,4192,6334-18-5,O=Cc1cccc(c1Cl)Cl,Training,0,0,52,0.5993581530925117,17.07,41.849500000000006,3.267344316501557,257.7830614243171,175.01399999999998,2.805900000000001
+4186,4193,63358-49-6,O=C(O)C3N2C(=O)C(NC(=O)C(NC(=O)C(N)CC(=O)NC)c1ccc(O)cc1)C2SC3(C)(C),Training,0,0,184,0.23751592933960308,191.16,121.30810000000001,1.7788223055435575,1015.2695599279655,493.5420000000002,-1.3553999999999955
+4187,4194,63390-11-4,Nc1ccc(cc1)c2cc(c(N)c(c2)Cl)Cl,Training,1,1,82,0.7586739279140474,52.04,70.7228,2.5239337976273553,498.03712407405914,253.13199999999998,3.8248000000000006
+4188,4195,63390-12-5,Nc1ccc(cc1Cl)c2cc(c(N)c(c2)Cl)Cl,Training,1,1,88,0.7598842780895455,52.04,75.7328,2.5667343335123993,558.9536913380496,287.577,4.4782
+4189,4196,633-96-5,O=S(=O)(O)c3ccc(N=Nc2c(O)ccc1ccccc12)cc3,Training,0,0,116,0.5554519797011201,99.32000000000001,86.04540000000003,1.9884810245033662,996.2689010836858,328.34900000000005,4.207500000000002
+4190,4197,63412-06-6,O=NN(C(=O)c1ccccc1)C,Training,1,1,62,0.4901587458094668,49.74,44.33050000000002,2.854633727978676,284.36915143875984,164.164,1.4400000000000002
+4191,4198,6341-85-1,O1CC1C2(OC2)(C),Training,1,1,40,0.43881896808554555,25.06,24.09699999999999,2.0405061831029374,92.25327665163482,100.11699999999999,0.17410000000000003
+4192,4199,6344-63-4,Nc2cccc3c1ccccc1Cc23,Training,1,1,68,0.5301091582882801,26.02,59.09640000000002,2.3250739440427637,500.33879156140733,181.23799999999997,2.8400000000000016
+4193,4200,6344-66-7,Nc1ccc3c(c1)c2ccccc2C3,Training,1,1,68,0.5301091582882802,26.02,59.09640000000002,2.2977402437268273,500.33879156140733,181.238,2.8400000000000007
+4194,4201,634-66-2,c1cc(c(c(c1Cl)Cl)Cl)Cl,Training,0,0,54,0.44741511729822037,0.0,46.482000000000006,3.3421538077705124,229.16988337222986,215.894,4.3002
+4195,4202,634-67-3,Nc1ccc(c(c1Cl)Cl)Cl,Training,0,0,54,0.5002950753011226,26.02,45.88440000000001,3.3421538077705124,232.41499587006638,196.46400000000003,3.229
+4196,4203,634-90-2,c1c(cc(c(c1Cl)Cl)Cl)Cl,Training,0,0,54,0.44741511729822037,0.0,46.482000000000006,3.3105328747224085,232.91988337222992,215.894,4.3002
+4197,4204,634-91-3,Nc1cc(c(c(c1)Cl)Cl)Cl,Training,0,0,54,0.5002950753011226,26.02,45.88440000000001,3.310532874722407,236.16499587006643,196.464,3.229
+4198,4205,634-93-5,Nc1c(cc(cc1Cl)Cl)Cl,Training,0,0,54,0.6335838032441449,26.02,45.88440000000001,3.310532874722407,236.16499587006643,196.464,3.229
+4199,4206,63521-85-7,O=C1c5cccc(OC)c5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)CO)CC4(OC3OC(C)CC(N)C3)),Training,1,1,202,0.2984123018928681,185.84,130.3646,1.6999678792658943,1344.0991285905268,527.5260000000003,1.0304999999999993
+4200,4207,635-27-8,n1cccc2c1cccc2Cl,Training,1,1,54,0.5821504570721324,12.89,46.75300000000002,2.9131611636048604,378.7244463345713,163.60699999999997,2.888200000000001
+4201,4208,63-56-9,n1cccnc1N(Cc2ccc(OC)cc2)CCN(C)C,Training,0,0,112,0.779023670000752,41.49,84.63000000000005,2.1048843505456873,527.7330568376073,286.379,2.0534
+4202,4209,6358-23-2,O=[N+]([O-])c2ccc(Nc1ccccc1(O))c(c2)[N+](=O)[O-],Training,1,1,102,0.5026447751149442,118.54000000000002,71.14030000000001,2.4393826428888046,686.5430539431337,275.22,2.9522000000000004
+4203,4210,6358-31-2,O=C(Nc1ccccc1(OC))C(N=Nc2ccc(cc2(OC))[N+](=O)[O-])C(=O)C,Training,0,1,146,0.32027340521631126,132.49,100.25710000000005,2.2595871753538384,928.0418846224061,386.36400000000015,3.2920000000000016
+4204,4211,6358-53-8,Oc2ccc3ccccc3(c2(N=Nc1cc(OC)ccc1(OC))),Training,1,0,116,0.6914018028807638,63.41000000000001,89.33480000000003,2.085854416459371,875.2697386572677,308.33700000000005,4.978000000000003
+4205,4212,636-21-5,Nc1ccccc1C,Training,1,1,42,0.5002819996278854,26.02,35.59140000000001,3.134861511345448,160.49662946459569,107.15599999999999,1.57722
+4206,4213,63642-50-2,O=C3c2ccc1c4ccccc4(ccc1c2CCC3),Training,1,1,92,0.5331886631514902,17.07,78.72250000000004,2.156293043757969,814.3978758376484,246.30899999999994,4.512000000000002
+4207,4214,6367-36-8,[N-]=[N+]=NCC(=O)OC(C)(C)C,Training,1,1,62,0.2642147761294876,75.06000000000002,39.85800000000001,3.7913613608002423,188.49430151423402,157.17299999999997,1.6384
+4208,4215,637-07-0,O=C(OCC)C(Oc1ccc(cc1)Cl)(C)C,Training,0,0,88,0.761604620096077,35.53,62.79200000000004,2.715496102823987,357.0315516842347,242.702,3.060500000000002
+4209,4216,63710-09-8,O=C(OC)C4c1cc5C(=O)c6c(O)ccc(O)c6(C(=O)c5(c(O)c1C(OC3OC(C)C(OC2OC(C)C(O)C(O)C2)C(N(C)C)C3)CC4(O)(CC))),Training,1,1,278,0.15152714415360954,221.97999999999996,175.44979999999956,1.3850565542190207,1715.8996107531093,715.749,1.7448999999999995
+4210,4217,63710-10-1,O=C(OC)C5c1cc6C(=O)c7c(O)ccc(O)c7(C(=O)c6(c(O)c1C(OC4OC(C)C(OC3OC(C)C(OC2OC(C)C(O)C(O)C2)C(O)C3)C(N(C)C)C4)CC5(O)(CC))),Training,1,1,330,0.11924998547431165,260.66999999999996,205.28159999999932,1.1363714744028401,1967.0647878672332,845.892,1.6259000000000001
+4211,4218,63-74-1,O=S(=O)(N)c1ccc(N)cc1,Training,0,0,60,0.5805509816764027,86.17999999999999,42.22760000000001,3.2015159310664942,341.3499619957354,172.209,-0.08380000000000026
+4212,4219,6375-16-2,O=C(Nc1ccc(c(N)c1)C)C,Training,1,1,64,0.6183522099186595,55.120000000000005,49.89510000000001,2.8927584746076427,307.39688695312145,164.208,1.5356200000000002
+4213,4220,63-75-2,O=C(OC)C1=CCCN(C)C1,Training,1,1,62,0.5139158149125915,29.54,42.213000000000015,2.5733242043241216,186.53107956171817,155.19699999999997,0.4213
+4214,4221,637-69-4,O(c1ccc(C=C)cc1)C,Training,0,0,52,0.6028361255721728,9.23,43.08500000000002,2.895351845489354,210.67480493540782,134.178,2.3382000000000005
+4215,4222,63785-41-1,O=S(=O)(O)Oc1ccc2cc3ccc4cccc5ccc(c2(c1))c3c45,Training,0,0,122,0.2793645625530675,63.60000000000001,99.82860000000005,1.9524573772810374,1371.58855052251,348.37900000000013,4.918800000000003
+4216,4223,63785-42-2,O=S(=O)(O)Oc5cccc1c5(cc2ccc3cccc4ccc1c2c34),Training,0,0,122,0.2793645625530675,63.60000000000001,99.82860000000004,2.007104145437783,1371.58855052251,348.3790000000001,4.918800000000003
+4217,4224,637-92-3,O(CC)C(C)(C)C,Training,0,0,44,0.4904141269367242,9.23,31.37899999999998,3.154490065368808,42.63193444574935,102.17699999999998,1.8214000000000001
+4218,4225,6379-69-7,O=C(OC2CC4OC1C=C(C(=O)CC1(C)C2(C)C34(OC3))C)C=CC,Training,0,0,130,0.44110501223657095,65.13,86.25000000000004,1.777365074685731,673.244632222241,332.3960000000001,2.3461
+4219,4226,638-07-3,O=C(OCC)CC(=O)CCl,Training,0,0,58,0.3499333048298977,43.370000000000005,36.977000000000004,3.4720657581481276,132.9546184423832,164.588,0.7475
+4220,4227,6385-62-2,c1cc[n+]3c(c1)c2cccc[n+]2CC3,Training,0,1,68,0.5383486697644573,7.76,52.26800000000003,2.287583078364963,431.75287485739244,184.24199999999996,0.9421999999999999
+4221,4228,63885-23-4,O=NN(C(=N)NCC)[N+](=O)[O-],Training,1,1,62,0.1939431178826054,111.69,36.03180000000001,4.139445403543677,179.81145612174103,161.12099999999998,-0.29423
+4222,4229,63980-20-1,N(=NCC)NCC,Training,1,1,42,0.41730915636233956,36.75,29.073699999999988,2.7771492902446893,50.89659695223976,101.15299999999999,0.9830000000000001
+4223,4230,640-15-3,O(C)P(OC)(=S)SCCSCC,Training,0,0,74,0.5060697166799627,18.46,63.76000000000003,3.5223947479401634,145.72862410467502,246.35899999999995,2.990000000000001
+4224,4231,64091-91-4,O=NN(C)CCCC(=O)c1cnccc1,Training,1,1,80,0.4040252507547986,62.63,56.22650000000003,2.341992394284751,326.69920263576444,207.23300000000003,1.6577
+4225,4232,64099-25-8,O=[N+]([O-])c2cccc1c(nsc12)OC,Training,1,1,72,0.5626673388952586,65.26,52.82640000000002,2.7615726079706606,494.29209068966935,210.21399999999997,2.2131
+4226,4233,64099-26-9,O=[N+]([O-])c1ccc2c(c1)c(ns2)OC,Training,1,1,72,0.5626673388952586,65.26,52.82640000000002,2.6684176509168966,494.29209068966935,210.21399999999997,2.2131
+4227,4234,64099-27-0,n2c(OC)c1cccc(N)c1s2,Training,1,1,62,0.6815523127175503,48.14,50.58440000000002,2.7993977958921907,410.3501069254241,180.23199999999997,1.8871
+4228,4235,64099-28-1,n2c(OC)c1cc(N)ccc1s2,Training,1,1,62,0.6815523127175505,48.14,50.58440000000002,2.749758659519757,410.3501069254241,180.232,1.8871
+4229,4236,64-17-5,OCC,Training,0,0,20,0.40680796565539457,20.23,12.759800000000002,1.6329931618554523,2.7548875021634682,46.069,-0.0014000000000000679
+4230,4237,64-18-6,O=CO,Training,0,0,18,0.3801607209681124,37.3,8.6928,2.1874960973678963,10.264662506490405,46.025,-0.29919999999999997
+4231,4238,64188-64-3,c1ccc(cc1)CN3C4c5ccccc5(c2ccccc2C34),Training,1,1,106,0.6003209599358527,3.01,89.34500000000004,1.5955209806298716,785.7906939039157,283.374,4.965200000000004
+4232,4239,64188-65-4,c1ccc3c(c1)c2ccccc2C4N(C34)C5CCCCC5,Training,1,1,106,0.6544454664569794,3.01,86.07200000000005,1.6225617458253718,632.2426993899911,275.39500000000004,5.097700000000003
+4233,4240,64188-66-5,c1ccc3c(c1)c2ccccc2C4N(CCCC)C34,Training,1,1,96,0.7202805119077819,3.01,78.97400000000005,1.8175837688666932,565.0922775934866,249.35699999999994,4.565100000000004
+4234,4241,641-90-7,O=C1c3cc(O)cc(O)c3(C(=O)c2c(O)c(O)c(cc12)C),Training,1,1,106,0.46644582817217317,115.06,71.1452,2.4150258850154187,834.7879788164705,286.239,1.5928199999999995
+4235,4242,64-19-7,O=C(O)C,Training,0,0,24,0.4298828832001217,37.3,13.309800000000001,2.8030394876740514,27.019550008653873,60.05200000000001,0.09090000000000004
+4236,4243,64201-68-9,O=CNc1nc(cs1)c2ccc(cc2)[N+](=O)[O-],Training,1,1,86,0.5114172642858024,85.13,63.89110000000001,2.2612190057813626,550.1786953873201,249.251,2.2866
+4237,4244,64216-20-2,O=C(NC(c2nc1ccccc1s2)S)NC(c4nc3ccccc3s4)S,Training,1,1,132,0.2852708371898297,66.91,114.3614,1.419609031701126,926.7044958350626,418.5940000000001,4.762200000000003
+4238,4245,64224-21-1,n1ccnc(c1)C2=C(C(=S)SS2)C,Training,0,0,66,0.5509158141740411,25.78,58.79300000000001,2.598277517406467,457.7414202573002,226.351,3.3045100000000005
+4239,4246,6422-86-2,O=C(OCC(CC)CCCC)c1ccc(cc1)C(=O)OCC(CC)CCCC,Training,0,0,158,0.3433083562994692,52.60000000000001,113.61900000000009,2.501752982778215,513.4728097510645,390.5640000000003,6.433000000000007
+4240,4247,642-83-1,O=C(OC1C(=O)OC2C(OC(=O)C)C(=O)OC12)C,Training,0,1,98,0.444243155260409,105.2,50.86800000000002,2.1554126985388855,387.593616668077,258.18199999999996,-1.299399999999999
+4241,4248,6428-31-5,O=S(=O)(O)c5cc6cc(c(N=Nc2ccc(N=Nc1ccc(N)cc1(N))cc2)c(N)c6(c(O)c5(N=Nc4ccc(N=Nc3ccc(N)cc3(N))cc4)))S(=O)(=O)O,Training,1,1,284,0.036665579342178,357.95000000000005,209.77599999999993,1.3438426205330218,2674.9874049797977,795.824,8.611400000000005
+4242,4249,64314-52-9,O=C1c5ccccc5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)CO)CC4(OC3OC(C)C(O)C(N)C3)),Training,1,1,196,0.25670338958593386,196.83999999999997,125.2024,1.6675072487627811,1310.9210445251979,513.4990000000003,-0.007300000000000639
+4243,4250,64356-85-0,O=C1C=C(C(=O)C3(O)(OC(C)(C)C2CC123))C(=CC)Cl,Training,1,1,102,0.7951754087735382,63.60000000000001,68.36080000000003,2.162753913913106,573.995038727714,282.72299999999996,1.7108999999999996
+4244,4251,64371-62-6,O1CC1(c2ccc(cc2)c3ccccc3)C,Training,1,1,80,0.6898506162161254,12.53,65.18200000000003,1.9363720320606872,480.6032179593456,210.27599999999998,3.599000000000002
+4245,4252,6441-91-4,O=[N+]([O-])c3ccc(N=Nc1c(N)ccc2cc(cc(O)c12)S(=O)(=O)O)c(c3)S(=O)(=O)O,Training,0,0,162,0.14070128974200027,222.84999999999997,106.92680000000003,2.228323951408021,1482.700181501709,468.4250000000002,2.9446000000000003
+4246,4253,644-21-3,NN(c1ccccc1)CC,Training,1,1,54,0.49140414893821865,29.259999999999998,43.64940000000002,2.746978188530898,183.70889642965702,136.19799999999998,1.3866000000000003
+4247,4254,64431-93-2,N1=C(NCC1)c2ccc(cc2)c3cc4ccc(cc4([nH]3))C5=NCCN5,Training,0,0,124,0.6912747885195907,64.57,102.54810000000003,1.4760614196792097,994.6033493741389,329.4070000000001,2.5344999999999995
+4248,4255,64432-06-0,O=C(OC1OC(CO)C(O)C(O)C1(O))C7(C)(CCCC4(C)(C7(CCC56(CC(=C)C(OC3OC(CO)C(O)C(O)C3(OC2OC(C)C(O)C(O)C2(O)))(CCC45)C6)))),Training,0,0,314,0.0730174777034441,274.74999999999994,184.9839999999995,1.1010735687091948,1432.7581318050914,788.8810000000007,-1.9104999999999894
+4249,4256,6449-35-0,O=S(=O)(O)c5cc6cc(N)ccc6(c(O)c5(N=Nc1ccc(cc1(OC))c4ccc(N=Nc2cc(c3ccccc3(c2(O)))S(=O)(=O)O)c(OC)c4)),Training,1,1,260,0.05419755266396215,243.11999999999998,188.60119999999978,1.3360595003543607,2663.6141364710656,729.7490000000004,7.994800000000008
+4250,4257,645-00-1,O=[N+]([O-])c1cccc(c1)I,Training,0,1,52,0.4346469827065539,43.14,45.813400000000016,3.069899265759275,261.67965837655686,249.00699999999995,2.1994
+4251,4258,645-05-6,n1c(nc(nc1N(C)C)N(C)C)N(C)C,Training,0,0,84,0.7033804434333938,48.39000000000001,62.80800000000004,3.200818079145855,268.63201166582786,210.285,0.0696000000000001
+4252,4259,64507-38-6,O=C(O)c2cc(cc1cccnc12)Br,Training,0,0,70,0.8482833268412876,50.19,56.40230000000001,2.8657325704443615,510.4481997034371,252.06699999999998,2.695500000000001
+4253,4260,645-09-0,O=C(N)c1cccc(c1)[N+](=O)[O-],Training,1,1,62,0.5176201644204088,86.23,41.61430000000001,3.121805775248301,305.92830270259753,166.13599999999994,0.6937
+4254,4261,645-12-5,O=C(O)c1oc(cc1)[N+](=O)[O-],Training,1,1,58,0.5076056976882865,93.58,32.3217,2.994170560413119,273.07635116796956,157.081,0.8859999999999999
+4255,4262,6452-71-7,OC(COc1ccccc1(OCC=C))CNC(C)C,Training,0,0,106,0.6704564525308724,50.72,76.77450000000005,2.4490008122380638,379.4083655141889,265.35299999999995,1.9890999999999999
+4256,4263,64532-97-4,O=P(Oc1ccccc1)(Oc2ccccc2)Oc3ccc(cc3)CCCCCCCCC,Training,0,0,170,0.18134654179678722,44.760000000000005,130.51350000000005,1.5832269620223371,896.9099606777806,452.5310000000004,8.624600000000001
+4257,4264,645-45-4,O=C(CCc1ccccc1)Cl,Training,1,1,58,0.633823998552948,17.07,45.623000000000026,2.453018743531937,230.57786591623355,168.623,2.3846000000000007
+4258,4265,645-62-5,O=CC(=CCCC)CC,Training,0,1,52,0.4170682144329801,17.07,39.346000000000004,3.6081784153458765,103.13526283059372,126.199,2.3218000000000005
+4259,4266,646-06-0,O1COCC1,Training,0,0,30,0.4020858486861461,18.46,16.771,2.083333333333333,16.464393446710154,74.07900000000001,-0.009299999999999975
+4260,4267,646-14-0,O=[N+]([O-])CCCCCC,Training,0,0,54,0.324369516956492,43.14,36.00339999999999,2.8288681349096856,83.12704561867443,131.175,1.8434
+4261,4268,64625-66-7,OC5c3ccc2c(cc1ccccc1c2C)c3C4OC4C5(O),Training,1,1,110,0.4941691551560917,52.989999999999995,84.77160000000003,1.914354216044739,930.7555430877238,292.334,3.149220000000003
+4262,4269,64-67-5,O=S(=O)(OCC)OCC,Training,1,1,56,0.5842085255575997,52.60000000000001,32.17179999999999,3.7345628196665563,135.95057052383706,154.18699999999998,0.30420000000000014
+4263,4270,64-69-7,O=C(O)CI,Training,1,0,30,0.47788715019272743,37.3,26.522799999999997,2.8473789230876716,42.91260938324327,185.948,0.506
+4264,4271,6471-49-4,O=C(Nc1cccc(c1)[N+](=O)[O-])c3cc4ccccc4(c(N=Nc2cc(ccc2(OC))[N+](=O)[O-])c3(O)),Training,1,1,180,0.18175447754307195,169.56,130.48680000000002,1.7828797897016686,1551.6690150727436,487.4280000000002,6.0381000000000045
+4265,4272,64724-48-7,O=C(Oc2c(ccc3c1ccccc1Cc23)NC(=O)C)C,Training,0,0,106,0.5796726912984221,55.4,80.29670000000003,2.1488212616419213,749.6955947193659,281.31100000000004,3.1415000000000006
+4266,4273,64-77-7,O=C(NCCCC)NS(=O)(=O)c1ccc(cc1)C,Training,0,0,100,0.8008194430489944,75.27000000000001,69.80720000000004,2.6444911926355648,494.5587374421375,270.35400000000004,1.78302
+4267,4274,64810-99-7,O=S(=O)(O)Oc2ccc3ccc4cc1ccccc1c5ccc2c3c45,Training,1,0,122,0.2793645625530675,63.60000000000001,99.82860000000005,2.014594723376398,1387.33855052251,348.37900000000013,4.918800000000003
+4268,4275,64811-02-5,O=S(=O)(O)Oc2c1ccccc1c3ccc5cccc4ccc2c3c45,Training,0,0,122,0.2793645625530675,63.60000000000001,99.82860000000005,2.1283245931342574,1371.58855052251,348.37900000000013,4.918800000000003
+4269,4276,6483-86-9,O=C2c3cc(ccc3(C(=O)c1c2(cccc1[N+](=O)[O-])))S(=O)(=O)O,Training,1,1,116,0.4278603215762689,131.64999999999998,76.21800000000002,2.311134725633247,1007.7810056714928,333.27700000000004,1.6169
+4270,4277,64-86-8,O=C1C=C3C(=CC=C1(OC))c2c(OC)c(OC)c(OC)cc2CCC3(NC(=O)C),Training,0,0,154,0.8325220081385356,83.09,109.23470000000006,2.4141279799484034,1001.3949196223746,399.44300000000015,2.871600000000001
+4271,4278,64894-89-9,[N-]=[N+]=Nc4ccc3c(nc1ccccc1c3(Nc2ccc(cc2)C(=O)O))c4,Training,1,1,130,0.2092998195981974,110.98,104.73900000000003,1.897554633159321,1228.545745649577,355.3570000000001,5.771600000000004
+4272,4279,64894-90-2,[N-]=[N+]=Nc4ccc3c(nc1ccccc1c3(Nc2ccc(cc2)NS(=O)(=O)C))c4,Training,1,1,144,0.19891320660998563,119.85,116.24620000000002,1.8130315868639155,1377.787672214492,404.4550000000001,5.444900000000005
+4273,4280,64896-26-0,O=C(O)c2ccc(N=Nc1ccc(O)c(c1)C(=O)O)cc2,Training,0,1,106,0.7452458170796388,119.55,72.64340000000001,2.2269705454841824,722.6442679121708,286.243,3.2040000000000006
+4274,4281,64920-31-6,OC3C=Cc2c4ccc1ccccc1c4(ccc2C3(O)),Training,1,1,98,0.6094202746465475,40.46,81.45460000000003,2.1217816926578568,848.5358923439028,262.308,3.4141000000000026
+4275,4282,64920-32-7,OC3C=Cc2ccc1c4ccccc4(ccc1c2C3(O)),Training,1,1,98,0.6094202746465475,40.46,81.45460000000003,2.151233404999915,848.5358923439028,262.308,3.4141000000000026
+4276,4283,64920-33-8,OC4c2ccc1c5ccccc5(ccc1c2C3OC3C4(O)),Training,1,1,104,0.4908991874831261,52.989999999999995,80.03460000000004,1.8938253181150846,886.1504003190425,278.307,2.840800000000002
+4277,4284,65002-17-7,O=C(O)C(NC(=O)C(C)(C)S)CS,Training,0,0,76,0.514564467882502,66.4,56.484500000000025,4.262901151185302,212.27341935356316,223.319,0.19400000000000012
+4278,4285,65199-11-3,O=C1C=Cc2c3ccc5cccc4ccc(cc2(C1(=O)))c3c45,Training,1,0,102,0.24514826603620993,34.14,91.37800000000004,2.23001004567033,1286.5622574536485,282.29800000000006,3.895400000000002
+4279,4286,65267-04-1,O=NN(C(=O)NCC(=O)N)CCCl,Training,1,1,74,0.35815054351673364,104.86,45.81410000000001,3.9057468347671884,209.956179579275,208.60499999999996,-0.5965
+4280,4287,65271-80-9,O=C1c3c(O)ccc(O)c3(C(=O)c2c(ccc(NCCNCCO)c12)NCCNCCO),Training,1,1,172,0.13931677804751474,163.17999999999998,119.96900000000004,1.9686005898708738,916.8717129663695,444.4880000000002,-0.13920000000000032
+4281,4288,6533-68-2,O=C(OC1CC3N(C)C(C1)C2OC23)C(c4ccccc4)CO,Training,0,0,118,0.6618093940597772,62.3,79.38280000000005,1.4200028178766766,545.0371822548029,303.35800000000006,0.9180999999999995
+4282,4289,6534-28-7,O=C1c3ccccc3(C(=O)c2c(ccc(NC(=O)C)c12)NC(=O)C),Training,1,1,120,0.7574201521198222,92.34,88.35640000000002,2.2971449290389065,841.2299343242646,322.32000000000005,2.3788
+4283,4290,65445-60-5,O=NN1CCCC(C1)Cl,Training,1,1,52,0.41575628021801,32.67,36.24300000000001,2.310570132500946,109.13111721021242,148.59300000000002,1.3710000000000002
+4284,4291,65445-61-6,O=NN1CCC(CC1)Cl,Training,1,1,52,0.41575628021801,32.67,36.24300000000001,2.255115324010933,101.13111721021241,148.59300000000002,1.3710000000000002
+4285,4292,65-45-2,O=C(N)c1ccccc1(O),Training,0,1,52,0.5912712208356958,63.32000000000001,36.62470000000002,3.1529414466808685,257.53794892648057,137.13799999999998,0.49110000000000004
+4286,4293,655-86-7,n1c3ccccc3(nc2cc(N)c(N)cc12),Training,1,1,78,0.43881967405074734,77.82,65.86880000000001,2.4649885270272587,630.9788965680245,210.23999999999998,1.9473999999999998
+4287,4294,65-61-2,n1c3cc(ccc3(cc2ccc(cc12)N(C)C))N(C)C,Training,1,1,102,0.6608644011478558,19.370000000000005,87.90300000000006,2.239459442556533,712.6360741161418,265.35999999999996,3.5200000000000022
+4288,4295,65734-38-5,O=C(NNc1ccc(cc1)CO)C,Training,1,1,70,0.5981299254048007,61.36,49.80420000000002,2.5375612644950314,282.1711052507959,180.20699999999997,0.6418999999999999
+4289,4296,65847-03-2,Oc3c2nc1occc1c(OC)c2c(c4OCOc34)CC=C(C)C,Training,0,1,124,0.7347230913948885,73.95000000000002,88.98980000000005,2.1684590876053713,982.3873442686743,327.33600000000007,3.9326000000000025
+4290,4297,65-85-0,O=C(O)c1ccccc1,Training,0,0,46,0.6106035394285075,37.3,33.4013,2.981454614041131,203.415952604261,122.12299999999996,1.3848
+4291,4298,65945-06-4,Oc4ccc1c(ccc2c3ccccc3(ccc12))c4,Training,1,1,90,0.4382001128928585,20.23,80.62480000000004,2.2553383038441863,922.3919838784873,244.293,4.851800000000003
+4292,4299,659-70-1,O=C(OCCC(C)C)CC(C)C,Training,0,0,72,0.5957782183942469,26.3,49.86900000000003,3.3197808606558685,127.80026905978025,172.26799999999997,2.6218000000000012
+4293,4300,66041-61-0,O=[N+]([O-])c1cc(ccc1(O))c2ccc(O)c(c2)[N+](=O)[O-],Training,0,1,102,0.6546924960522635,126.74000000000001,68.5164,2.57177028883416,651.5888897363245,276.204,2.5812
+4294,4301,6606-59-3,O=C(OCCCCCCOC(=O)C(=C)C)C(=C)C,Training,0,0,102,0.36049668460833456,52.6,70.01400000000004,3.3162010440941296,285.7556811171552,254.32599999999994,2.785400000000001
+4295,4302,66212-60-0,OC3c1c4ccc6cccc5ccc(cc1C2OC2C3(O))c4c56,Training,1,1,112,0.38635993495173776,52.989999999999995,88.72660000000003,1.862473726522413,1084.6259786701926,302.329,3.431800000000003
+4296,4303,6623-66-1,O=C2Oc1ccc(cc1c3ccccc23)[N+](=O)[O-],Training,1,1,88,0.28396376553205804,73.35,66.6444,2.539244947197444,835.1288097672251,241.20199999999997,2.854400000000001
+4297,4304,66-27-3,O=S(=O)(OC)C,Training,1,1,38,0.43093918963957045,43.370000000000005,21.85279999999999,3.8506216389836694,110.75488750216347,110.13399999999999,-0.40759999999999996
+4298,4305,6628-97-3,O=C2C=C(Nc1ccccc1)C(=O)c3ccccc23,Training,1,0,92,0.8892819370574402,46.17,73.25070000000002,1.9720304165287623,686.9049381134768,249.269,3.061600000000001
+4299,4306,66291-31-4,c1ccc3c(c1)ccc2ccc(c(c23)C)C,Training,0,1,78,0.4710734601666233,0.0,70.92800000000004,2.628150791487622,677.9984465766784,206.28799999999995,4.609840000000003
+4300,4307,6629-29-4,O=[N+]([O-])c1cc(N)cc(N)c1C,Training,1,1,64,0.37116878927500957,95.17999999999999,46.6582,3.3738590108748685,335.66852769827057,167.16799999999998,1.06762
+4301,4308,6633-40-5,O=[N+]([O-])c2ccc3c1ccc(O)cc1Cc3(c2),Training,1,1,84,0.5131891447458878,63.370000000000005,63.00320000000003,2.1547918675956335,634.5568559110059,227.21899999999997,2.871600000000001
+4302,4309,66357-59-3,O=[N+]([O-])C=C(NC)NCCSCc1oc(cc1)CN(C)C,Training,0,0,118,0.38410287831471035,83.58,84.40080000000003,2.218277243493725,473.7363586621032,314.41100000000006,1.4589999999999999
+4303,4310,6638-64-8,O=C2Oc1cc(ccc1c3ccccc23)[N+](=O)[O-],Training,1,1,88,0.28396376553205804,73.35,66.6444,2.5011147904629647,835.1288097672251,241.20199999999997,2.854400000000001
+4304,4311,6639-36-7,O=[N+]([O-])c1ccc3c(c1)c2ccccc2s3,Training,1,1,78,0.467863471386403,43.14,65.98540000000003,2.441228666577131,702.3776755816397,229.26,3.9627000000000008
+4305,4312,66452-61-7,Nc1ccc(cc1SC(C)C)Cc2ccc(N)c(c2)SC(C)C,Training,1,1,124,0.5397585066109672,52.04,106.50080000000003,2.2163062230042434,608.9143431199732,346.56500000000005,5.4428000000000045
+4306,4313,6653-71-0,O=C(NCc1ccccc1)C(C)Br,Training,1,0,70,0.8076344712962408,29.1,56.67770000000003,2.398383565524446,271.5130516555259,242.11599999999999,2.0862
+4307,4314,66552-77-0,c1ccc3c(c1)c(c2cc(c(cc2c3C)C)C)C,Training,1,1,90,0.4673147828071939,0.0,80.40200000000004,2.6244174700734337,697.929493017487,234.34199999999996,5.2266800000000035
+4308,4315,66-56-8,O=[N+]([O-])c1cccc(O)c1[N+](=O)[O-],Training,1,1,68,0.5485201907500785,106.51000000000002,41.41560000000001,3.427344204506423,375.28740254995904,184.10699999999997,1.2086000000000003
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+4316,4323,66-81-9,O=C1NC(=O)CC(C1)CC(O)C2C(=O)C(C)CC(C)C2,Training,0,0,112,0.7571556004572341,83.47,72.55650000000004,1.96219554115596,404.0965760348747,281.35200000000003,1.041499999999999
+4317,4324,66842-41-9,O1CC1c3cc4c5ccccc5(ccc4(c2ccccc23)),Training,1,1,100,0.3411566068688213,12.53,87.65300000000003,2.045476980655139,996.3409862979379,270.331,5.217500000000003
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+4319,4326,66850-95-1,O=C(O)CCC(NC(=O)COc1cc(c(cc1Cl)Cl)Cl)C(=O)O,Training,0,0,126,0.5934376593817702,112.93000000000002,83.40330000000004,2.5993812586762464,621.972574323106,384.59900000000005,2.4597999999999995
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+4324,4331,66-97-7,O=C1Oc2cc3occc3(cc2(C=C1)),Training,0,0,68,0.5064832269036607,43.35,52.256000000000014,2.564584551206422,660.6550392395076,186.16599999999997,2.5392
+4325,4332,67019-19-6,O=C(Nc1c2ccccc2(ns1))CCl,Training,1,1,72,0.7998072888567352,41.99,58.969700000000024,2.38201468779506,468.53482316385254,226.68799999999996,2.4736000000000002
+4326,4333,67019-20-9,O=C(Nc1c2ccccc2(ns1))CC,Training,0,0,72,0.8203122302220168,41.99,58.54070000000003,2.38201468779506,463.8448672279597,206.26999999999995,2.644800000000001
+4327,4334,67019-21-0,O=C(Nc1c2ccccc2(ns1))CCC,Training,0,0,78,0.8634338261781711,41.99,63.157700000000034,2.2470093153797634,478.1475866267328,220.29699999999994,3.0349000000000013
+4328,4335,67019-22-1,O=C(Nc1c2ccccc2(ns1))C(C)C,Training,0,0,78,0.8451325182426709,41.99,63.087700000000034,2.3263664306161425,490.0485079143073,220.29699999999997,2.8908000000000014
+4329,4336,67019-24-3,O=C(Nc1c2ccccc2(ns1))CC(C)C,Training,0,0,84,0.8851121780393203,41.99,67.70470000000003,2.1822587952930994,504.4429988769885,234.32399999999996,3.2809000000000017
+4330,4337,67019-26-5,O=C(Nc1c2ccccc2(ns1))CCCCCCC,Training,0,0,102,0.7511207416630833,41.99,81.62570000000005,1.818984460446359,535.6800253725353,276.405,4.5953000000000035
+4331,4338,67019-28-7,O=C(Nc1c2ccccc2(ns1))c3ccccc3,Training,1,0,88,0.7595295574164945,41.99,74.01520000000004,1.9119934577470852,691.0951903975501,254.314,3.5486000000000013
+4332,4339,67019-29-8,O=C(Nc1ccccc1)Nc2c3ccccc3(ns2),Training,0,1,94,0.7399872871753871,54.02,78.70340000000003,1.7622484327675187,708.7976385449673,269.32899999999995,3.9403000000000015
+4333,4340,67019-30-1,O=C(N(c1c2ccccc2(ns1))C)C,Training,0,0,72,0.7168030612749143,33.2,58.70400000000003,2.579889378228137,477.6816634575481,206.26999999999995,2.279
+4334,4341,67019-32-3,O=C(Nc1c2cc(cc(c2(ns1))Cl)Cl)C,Training,0,1,78,0.8522288314862938,41.99,63.94370000000002,2.628752673368357,538.1370204680552,261.133,3.5615000000000006
+4335,4342,67028-20-0,n3c2c(ccc1ccccc12)cc4cccc(c34)C,Training,0,1,90,0.31760721028739625,12.89,81.49200000000003,2.271705497329529,922.3919838784873,243.30899999999997,4.8496200000000025
+4336,4343,67-03-8,OCCc1c([n+](cs1)Cc2cnc(nc2(N))C)C,Training,0,1,96,0.79412732636072,75.91,70.32420000000002,2.230916753508816,553.005593291334,265.36199999999997,0.6077399999999998
+4337,4344,670-54-2,N#CC(C#N)=C(C#N)C#N,Training,0,0,44,0.4401949082641678,95.16,29.478,5.121564652353458,256.7202171133866,128.094,0.3773199999999999
+4338,4345,67151-57-9,O=[N+]([O-])c2ccc(c(N=[N+]([O-])c1cc(ccc1C)[N+](=O)[O-])c2)C,Training,0,0,118,0.3639139604555908,124.71000000000001,81.04220000000002,2.5188217104539397,831.912493409467,316.273,4.045540000000003
+4339,4346,67199-66-0,O=C2c4ccccc4(C3=Nc1ccc(N)cc1CN23),Training,1,1,92,0.7282603659683625,58.690000000000005,73.36690000000002,1.9424679226399333,748.8059484657315,249.27299999999997,2.3164999999999996
+4340,4347,67-20-9,O=C2NC(=O)CN2(N=Cc1oc(cc1)[N+](=O)[O-]),Training,1,1,88,0.34574784602990005,118.05000000000001,53.201100000000004,2.0702875864987447,519.7401440929854,238.159,0.07350000000000012
+4341,4348,67-21-0,O=C(O)C(N)CCSCC,Training,0,0,60,0.580617675155612,63.31999999999999,43.22720000000002,3.214876896824448,107.9209386162151,163.242,0.5415000000000001
+4342,4349,67274-48-0,O=C(N(O)c1ccc(cc1)Br)C,Training,0,0,64,0.5929250847385491,40.540000000000006,49.08850000000002,2.8925610901856844,283.6142639365964,230.06099999999998,2.1912000000000003
+4343,4350,67274-52-6,O=C(N(O)c1ccc(cc1)[N+](=O)[O-])C,Training,1,1,74,0.4390764145976317,83.68,48.04290000000002,2.9351285584212463,360.1089581038585,196.16199999999998,1.3369
+4344,4351,6728-26-3,O=CC=CCCC,Training,1,1,40,0.3862877991333781,17.07,30.111999999999988,2.9211959005655155,64.58027134782355,98.14500000000001,1.5415999999999999
+4345,4352,6730-83-2,O=C(O)C4(C)(CCCC2(C)(C4(CCC13(CC(=C)C(CCC12)C3)))),Training,0,0,122,0.6889234165472609,37.3,87.44580000000005,1.7479165986252938,537.8253337815046,302.4580000000001,5.040100000000005
+4346,4353,67392-87-4,O=C1OC5(CC1)(C2CC2C4C6C7CC7(C3=CC(=O)CCC3(C)C6(CCC45(C)))),Training,0,0,144,0.6002668837960434,43.370000000000005,99.49300000000007,1.3334926927509605,827.4829214489886,366.5010000000002,4.305900000000004
+4347,4354,67410-22-4,n1c(N)ccc2ccc3ccccc3(c12),Training,1,1,72,0.558615089468334,38.91,63.66140000000003,2.573833591681612,644.1543647116673,194.237,2.970200000000001
+4348,4355,67411-86-3,OCc4cc1ccccc1c3ccc2ccccc2c34,Training,1,1,96,0.4930974027908845,20.23,84.88280000000005,2.332741310688639,937.9563134380709,258.32,4.638500000000003
+4349,4356,67450-45-7,O=C(N(c1ccc(c(c1)Cl)Cl)C2CCCC2(N(C)C))CC,Training,0,0,116,0.8256683925739744,23.550000000000004,89.35300000000005,2.3820063207266333,518.9984822252637,329.271,4.219100000000003
+4350,4357,67-45-8,O=C2OCCN2(N=Cc1oc(cc1)[N+](=O)[O-]),Training,1,1,84,0.4333097720182961,98.18,51.01040000000001,2.0507091679266773,452.2811888785661,225.16,0.9739
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+4353,4360,67-48-1,OCC[N+](C)(C)C,Training,0,0,44,0.47618393148924243,20.23,29.98519999999998,3.154490065368808,46.532068975639476,104.17299999999999,-0.31510000000000016
+4354,4361,674-82-8,O=C1OC(=C)C1,Training,0,0,32,0.3980844137850428,26.3,19.848999999999997,2.470214660304168,82.11571282193985,84.074,0.44699999999999995
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+4356,4363,67508-87-6,O=C1c5cccc(OC)c5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)C)CC4(OC3OC(C)C(O)C(N(C)C)C3)),Training,1,1,214,0.33850261070174364,163.06,139.8421999999999,1.6637280305587114,1418.2552492843668,555.5800000000002,1.6317999999999995
+4357,4364,6754-13-8,O=C1OC2CC(C)C3C=CC(=O)C3(C)(C(O)C2(C1(=C))),Training,0,0,102,0.5268622725609776,63.60000000000001,68.04180000000002,2.082001336742861,506.27496377854544,262.305,1.2463000000000002
+4358,4365,6755-13-1,O=C(C=Cc1oc(cc1)[N+](=O)[O-])N(C)C,Training,1,1,80,0.4275605640787182,76.58999999999999,53.090400000000024,2.7289986600576412,405.9997727342192,210.18899999999996,1.2891999999999997
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+4361,4368,6756-41-8,Oc2ccc3ccccc3(c2(N=Nc1ccc(cc1)C)),Training,0,1,98,0.6280993481969629,44.95,80.96780000000003,2.0557724140718667,776.6019254477185,262.312,5.269220000000003
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+4363,4370,67604-48-2,O=C2c3c(O)cc(O)cc3(OC(c1ccc(O)cc1)C2),Training,0,0,102,0.7421139126791214,86.99000000000001,70.19490000000002,1.9989096999227665,675.40838289424,272.25600000000003,2.5099
+4364,4371,67616-44-8,O=NSCCO,Training,1,0,36,0.3222745089893105,49.66,25.338799999999992,2.488403771876112,40.529325012980806,107.134,0.3932999999999999
+4365,4372,67-63-0,OC(C)C,Training,0,0,26,0.42840479403162834,20.23,17.3548,2.3237900077244498,8.0,60.096000000000004,0.3871
+4366,4373,67634-00-8,O=C(OCC=C)COCCC(C)C,Training,0,0,76,0.34518732522478596,35.53,51.430000000000035,3.2141171591560145,152.24884793672035,186.25099999999998,1.7783
+4367,4374,67-64-1,O=C(C)C,Training,0,0,24,0.3982369618339747,17.07,16.355,2.8030394876740514,26.264662506490403,58.08,0.5952999999999999
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+4369,4376,67-68-5,O=S(C)C,Training,0,0,26,0.3981850774633207,17.07,19.990399999999998,2.8030394876740514,29.019550008653873,78.136,-0.005299999999999971
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+4378,4385,67910-07-0,O=CC2=CC=C1C2(=COC=C1COC(=O)CC(C)C),Training,1,0,100,0.6111279655757167,56.51,69.96850000000003,2.0950921663706885,553.4275164929195,260.28899999999993,3.286200000000002
+4379,4386,6795-16-0,O=C1c5c(O)cccc5(Oc3c1c(OC)cc2OC4OCCC4(c23)),Training,0,0,122,0.692891038291953,78.13000000000001,85.93280000000003,1.9782114292523512,1050.9730674438058,326.3040000000001,2.8828000000000005
+4380,4387,6795-23-9,O=C4Oc2c(c(OC)cc1OC3OC=CC3(O)(c12))C5=C4C(=O)CC5,Training,1,1,122,0.7901573426740779,95.20000000000002,80.22530000000002,1.9701597323104814,1015.9966196497429,328.2760000000001,1.3804999999999998
+4381,4388,67-97-0,OC3CC(=CC=C1CCCC2(C)(C1CCC2(C(C)CCCC(C)C)))C(=C)CC3,Training,0,0,158,0.49910402699484796,20.23,121.1888000000001,1.6958985314070005,609.7518254928542,384.64800000000025,7.619000000000009
+4382,4389,67976-98-1,n2c6ccc1ccccc1c6(cc3c2C5OC5(c4ccccc34)),Training,1,1,108,0.3297066124745332,25.42,91.25200000000002,1.766018414871457,1115.2543257336224,295.341,5.181000000000003
+4383,4390,67-99-2,O=C2N(C)C4(C(=O)N3C1C(=CC=CC1(O))CC23SS4)(CO),Training,0,1,112,0.6439312178290959,81.08000000000001,78.98060000000001,1.8995701742172306,621.2925177262188,326.39900000000006,-0.30370000000000025
+4384,4391,68006-83-7,n1c(N)c(cc3c1[nH]c2ccccc23)C,Training,1,1,74,0.5816562035642182,54.699999999999996,62.74910000000001,2.5559481078052437,652.3207036761831,197.24099999999999,2.606720000000001
+4385,4392,680-31-9,O=P(N(C)C)(N(C)C)N(C)C,Training,0,1,68,0.5980680831968047,26.790000000000006,48.667500000000025,4.690791012693442,138.6810057963953,179.204,0.7793000000000001
+4386,4393,6807-96-1,O=C3c5cc(O)cc(O)c5(C(=O)c4c(O)c1c(OC2OC=CC12)cc34),Training,1,1,124,0.5737237860984008,113.29,82.1254,1.8019643698601324,1034.4505932955108,338.271,1.9247999999999996
+4387,4394,6810-26-0,ONc1ccc(cc1)c2ccccc2,Training,1,1,70,0.7042156722210636,32.26,57.28720000000002,2.3429680041070835,394.42672290326925,185.226,3.154700000000001
+4388,4395,68-11-1,O=C(O)CS,Training,0,0,30,0.4466266407897091,37.3,21.488799999999998,2.8473789230876716,42.91260938324327,92.119,0.0008000000000000229
+4389,4396,68-12-2,O=CN(C)C,Training,0,0,30,0.3902682398861675,20.310000000000002,19.750999999999998,2.825749368745867,33.87430298092722,73.095,-0.2956000000000001
+4390,4397,68140-48-7,O=C(c1cc2c(cc1C)C(C)(C)C(C)C2C(C)C)C,Training,0,0,104,0.6919735642013547,17.07,80.95250000000006,2.694649304122811,522.7369751653058,258.405,4.864520000000005
+4391,4398,68162-37-8,O=C(OC)C(=Cc1oc(cc1)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,90,0.332937760583068,125.72,52.349799999999995,3.085269327024349,501.726901696519,242.14299999999997,0.9783999999999999
+4392,4399,68162-38-9,O=C(OC)C(=Cc1oc(cc1)Br)[N+](=O)[O-],Training,0,0,80,0.36377762517343226,82.58,53.3954,3.039281861280666,422.4214488418507,276.04200000000003,1.8327000000000004
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+4402,4409,68268-44-0,O=C(N(c1c2ccccc2(ns1))CC(C)C)CCCl,Training,0,1,102,0.783730561272968,33.2,82.14800000000004,2.3899927347484717,567.3262355556587,296.823,3.914200000000003
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+4404,4411,68302-57-8,O=C(O)c1cc2C(=O)c3cc(ccc3(Oc2(nc1(N))))C(C)C,Training,0,0,112,0.7044218634482015,106.41999999999999,83.24570000000003,2.4259921320675346,973.1896128999356,298.298,2.745000000000001
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+4411,4418,68641-49-6,O=C1OCCN1P(=O)(N2C(=O)OCC2)Cl,Training,1,1,84,0.693034350038367,76.15,49.56750000000002,2.2151698125248447,331.43141666038713,254.56599999999997,1.2377
+4412,4419,68688-86-8,OC5C=Cc4ccc2c(cc1ccc(c3c1c2CC3)C)c4C5(O),Training,1,1,114,0.6197713541573014,40.46,93.59960000000004,1.9631510417992448,1013.6863758675851,302.373,3.8211200000000036
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+4415,4422,687-47-8,O=C(OCC)C(O)C,Training,0,0,48,0.5161288838079469,46.53,28.313799999999986,3.329150037184473,77.74296763342026,118.13199999999998,-0.06970000000000015
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+4417,4424,6884-87-3,O=C(Nc1ccc(cc1)S(=O)(=O)NC)C,Training,0,0,82,0.7930565445322582,75.27,56.99120000000003,2.953331433757246,450.75073033371376,228.27299999999997,0.5530999999999997
+4418,4425,688-74-4,O(B(OCCCC)OCCCC)CCCC,Training,0,0,96,0.3794780391287241,27.69,68.33400000000006,3.57988974451701,109.65784284662087,230.15699999999993,3.421400000000002
+4419,4426,68884-32-2,O1CC1Cc3cccc2ccccc23,Training,1,1,70,0.6536855239636413,12.53,57.39200000000004,2.1127656702436863,452.2471457744983,184.238,2.7811000000000012
+4420,4427,68906-23-0,O=CNc2ccc(Oc1c(cc(cc1Cl)Cl)Cl)cc2,Training,1,1,98,0.8053930286040696,38.33,77.67470000000002,2.2341892885615082,576.332479012947,316.571,5.007400000000001
+4421,4428,68931-03-3,O=C(OC(C)CN(CC)CC)Nc1ccccc1(OCCCCCCC),Training,0,0,148,0.4816453092452651,50.8,108.04970000000009,2.442079923639611,503.7844863437201,364.5300000000003,5.314600000000005
+4422,4429,68941-03-7,Nc1ccc(cc1)N(c2ccc3ccccc3(c2))c4ccc5ccccc5(c4),Training,0,1,134,0.34943010158797994,29.259999999999998,120.54940000000002,1.7164848070595595,1193.4083560315664,360.4600000000001,7.045000000000004
+4423,4430,689-98-5,NCCCl,Training,1,0,26,0.4461740172738645,26.02,19.774399999999996,1.9747448713915894,8.0,79.53,0.1839
+4424,4431,69-09-0,c1ccc3c(c1)N(c2cc(ccc2S3)Cl)CCCN(C)C,Training,0,0,110,0.7918053413291345,6.48,92.19400000000005,1.9437632658356148,642.4372765270095,318.8730000000001,4.894400000000004
+4425,4432,69140-51-8,O2C(c1ccccc1)C2CC,Training,0,1,58,0.586999316743532,12.53,44.34700000000003,2.088602742931174,229.88790998034074,148.20499999999996,2.536500000000001
+4426,4433,69231-25-0,O=C(OC)C=2C(=O)OC(C=2(c1ccccc1))C,Training,0,0,88,0.5732339889640989,52.60000000000001,60.93200000000003,2.5620416483509882,487.4007433166583,232.23499999999999,1.5585
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+4443,4450,69657-88-1,O=C1c3c(O)ccc(O)c3(C(=O)c2c1c(ccc2N(C)C)N(C)C),Training,1,1,124,0.7012477500592834,81.07999999999998,91.73260000000003,2.45029219842834,813.0728783727964,326.35200000000003,2.0052
+4444,4451,69658-13-5,O=C(O)CSc3ccc2c4ccccc4(C(=O)c1cccc3(c12)),Training,1,1,112,0.5740296906723402,54.37,91.17630000000004,2.0133939047912666,975.5107107818686,320.3690000000001,4.227900000000002
+4445,4452,69658-14-6,O=C(OCC)CSc3ccc2c4ccccc4(C(=O)c1cccc3(c12)),Training,1,1,124,0.39575831583376353,43.370000000000005,100.17350000000003,1.8555727282263474,1007.1938372586087,348.4230000000001,4.706400000000003
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+4456,4464,70021-99-7,O=[N+]([O-])c5ccc2ccc3cc1ccccc1c4ccc5(c2c34),Training,1,1,108,0.17366715134946126,43.14,94.30640000000004,2.144352010669374,1240.4324987418463,297.31300000000005,5.645400000000003
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+4458,4466,70092-13-6,O=C4C=Cc1c(ccc3c1c(c2ccccc2c3C)C)C4(=O),Training,0,1,106,0.45352026970527387,34.14,89.29950000000005,2.265167856709748,1022.9769458595871,286.33000000000004,4.388440000000003
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+4460,4468,70140-81-7,O(CC)P(OCC(C)C)(=S)SCCl,Training,0,0,80,0.5122162829086127,18.46,65.01200000000003,3.993597833750557,167.87547739228725,262.764,3.8495000000000035
+4461,4469,70140-82-8,O(CC(C)C)P(OCC(C)C)(=S)SCCl,Training,0,0,92,0.4841128823731723,18.46,74.17600000000004,4.123205767906535,196.28902514118806,290.818,4.485600000000004
+4462,4470,70-18-8,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CS,Training,1,1,114,0.2634372933480748,158.82,71.27440000000001,4.208861414299985,389.18921854622977,307.328,-2.206099999999997
+4463,4471,70249-46-6,OCc2ccc4c1ccccc1c3cccc2c34,Training,0,0,86,0.5260129714795542,20.23,74.30080000000002,2.2345018001350607,742.4121453127872,232.28199999999998,3.9795000000000025
+4464,4472,70-25-7,O=NN(C(=N)N[N+](=O)[O-])C,Training,1,1,56,0.17643951719742762,111.69,31.4148,3.8426833843513837,166.27599848312963,147.094,-0.6843299999999999
+4465,4473,70-30-4,Oc1c(cc(c(c1Cc2c(O)c(cc(c2Cl)Cl)Cl)Cl)Cl)Cl,Training,0,1,112,0.5506929908667572,40.46,89.07959999999999,2.641450020385574,615.5770288071316,406.9069999999999,6.609000000000001
+4466,4474,70-34-8,O=[N+]([O-])c1ccc(F)c(c1)[N+](=O)[O-],Training,1,1,68,0.5184110397384197,86.28,39.70880000000001,3.267052212361692,378.8970430243959,186.09799999999998,1.6421
+4467,4475,703-83-3,n2c1ccccc1c(NCC)s2,Training,0,0,62,0.7644466737562736,24.92,53.783700000000024,2.5484054472393094,380.6639128453302,178.26,2.7281000000000004
+4468,4476,70403-80-4,O(c3ccc4cc2c1c(c(OC)c(OC)cc1CCN2C)c4(c3))C,Training,0,1,124,0.681517008324813,30.93,98.08400000000006,2.2572372212200937,948.9056081068442,323.392,4.011100000000003
+4469,4477,70403-81-5,O=C1c3nccc4cc(OC)c(OC)c(c2ccc(OC)cc12)c34,Training,1,1,120,0.578108451122366,57.650000000000006,90.26750000000004,2.205481149049309,994.3136138124412,321.33200000000005,3.472000000000002
+4470,4478,7040-57-5,O=P(OC(C)C(C)(C)C)(C)Cl,Training,0,0,68,0.6351674350266614,26.3,49.385500000000036,4.097767717974698,167.7696121417746,198.63,3.4993000000000025
+4471,4479,70458-92-3,O=C(O)C1=CN(c2cc(c(F)cc2(C1(=O)))N3CCN(C)CC3)CC,Training,1,1,128,0.9243839877881741,65.78,90.50930000000005,2.183159031345674,854.2600816822634,333.3630000000001,1.6104999999999998
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+4474,4482,70585-52-3,O=C(O)c2cc(cc1cccnc12)[N+](=O)[O-],Training,1,0,80,0.6126425491340495,93.33,55.356700000000004,2.8367375455945996,594.3887652577181,218.16799999999998,1.8411999999999995
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+4477,4485,7068-83-9,O=NN(C)CCCC,Training,1,1,48,0.41053528559297164,32.67,33.33299999999999,2.975409490043988,65.44900955152481,116.164,1.3997
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+4488,4496,70951-83-6,OC4c2c5ccc1ccccc1c5(ccc2C3OC3C4(O)),Training,1,1,104,0.4908991874831261,52.989999999999995,80.03460000000004,1.9038998114188357,886.1504003190425,278.30699999999996,2.840800000000002
+4489,4497,70955-02-1,O=C(NN)CNc1ccc2ccccc2(c1),Training,0,1,82,0.40975962557670664,67.15,64.76780000000001,2.163019121799384,510.34496173485053,215.256,1.2415999999999998
+4490,4498,70987-78-9,O=S(=O)(OCC1OC1)c2ccc(cc2)C,Training,1,1,82,0.571703730768941,55.900000000000006,54.05680000000003,2.090799453019474,430.9951221201622,228.26899999999998,1.0991199999999999
+4491,4499,709-98-8,O=C(Nc1ccc(c(c1)Cl)Cl)CC,Training,0,0,70,0.8096716543147999,29.1,55.38270000000002,2.793568433647237,325.3907822709721,218.08299999999997,3.3419000000000016
+4492,4500,710-25-8,O=C(N)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,68,0.42174604066011884,99.37,43.59080000000001,2.804194668300063,366.32437648269985,182.135,0.6863
+4493,4501,7119-89-3,O=[N+]([O-])C(Cl)Cl,Training,1,1,36,0.22992292410335405,43.14,22.4884,3.2575861612334887,62.568425030288566,129.93,1.0243
+4494,4502,712-12-9,n2c1ccccc1c(NCC(C)C)s2,Training,0,0,74,0.8325339247271516,24.92,62.94770000000003,2.249312357908722,419.89968231042366,206.314,3.364200000000002
+4495,4503,71-23-8,OCCC,Training,0,0,26,0.46378398302396845,20.23,17.3768,1.9747448713915894,5.245112497836532,60.096000000000004,0.3887
+4496,4504,7125-53-3,O1CC12(CCC3CCCCC3(C2)),Training,0,0,68,0.504019093679254,12.53,47.98200000000003,1.7049643266096142,183.44313396035153,166.26399999999998,2.745700000000001
+4497,4505,7132-67-4,Oc2ccc3nc1ccccc1c(N)c3(c2),Training,1,1,78,0.5606550330505325,59.14,65.32620000000001,2.5581440319024598,691.8927302408441,210.236,2.6757999999999997
+4498,4506,71-33-0,O=C1N=CNC(=O)N1,Training,0,1,42,0.42753614508514476,78.61,25.478399999999997,3.5021170388304435,246.85217875774802,113.07599999999998,-1.5418
+4499,4507,71339-55-4,OCc3c1ccccc1c(c2ccccc23)C,Training,1,1,84,0.6209022308920537,20.23,72.11380000000004,2.6317714099038505,641.2790663039683,222.28699999999998,3.793720000000002
+4500,4508,71-36-3,OCCCC,Training,0,0,32,0.5128217987135145,20.23,21.993799999999993,2.19060968716425,11.119415478763749,74.123,0.7787999999999999
+4501,4509,71382-44-0,c1ccc2cc4c(cc2(c1))c3ccccc3C5NC45,Training,1,1,90,0.5869679063753442,21.94,78.00170000000004,1.9008931106640354,818.7881607391033,243.309,4.205800000000003
+4502,4510,71382-46-2,c1ccc4c(c1)c(c3c2ccccc2C5NC5(c3c4C))C,Training,1,1,102,0.5815030070672805,21.94,87.47570000000005,1.9958502869782575,907.1006320004357,271.363,4.822640000000004
+4503,4511,71382-49-5,c1ccc4c(c1)ccc3cc5c2ccccc2C6NC6(c5(cc34)),Training,1,1,108,0.34199974896565355,21.94,95.50770000000003,1.7502417519508082,1109.385496001956,293.369,5.3590000000000035
+4504,4512,71382-50-8,c1ccc6c(c1)cc4c3c6(ccc2cccc(c23)C5NC45),Training,1,1,98,0.3569872566688093,21.94,87.57770000000002,2.002786888436936,1077.2526737358062,267.331,4.845200000000003
+4505,4513,71400-33-4,O=[N+]([O-])c1ccc2Oc3cc(ccc3(Oc2(c1)))[N+](=O)[O-],Training,1,1,100,0.5234054068606357,104.74000000000001,66.34080000000002,2.015052435987679,679.2225607996631,274.18800000000005,3.4010000000000007
+4506,4514,71400-34-5,O=[N+]([O-])c1ccc2Oc3ccc(cc3(Oc2(c1)))[N+](=O)[O-],Training,1,1,100,0.5234054068606357,104.74000000000001,66.34080000000002,2.028316659825984,681.2225607996631,274.18800000000005,3.4010000000000007
+4507,4515,71-41-0,OCCCCC,Training,0,0,38,0.513281356352027,20.23,26.610799999999987,2.3390923149762908,15.900134529890124,88.15,1.1689
+4508,4516,71422-67-8,O=C(NC(=O)c1c(F)cccc1(F))Nc3cc(c(Oc2ncc(cc2Cl)C(F)(F)F)c(c3)Cl)Cl,Training,0,0,178,0.346273747598501,80.32000000000001,113.6279,1.7431910577635747,1244.78451345341,540.6590000000001,7.093000000000001
+4509,4517,71424-66-3,O=C3c2c1C(=C)CCC4C(c1c(c(O)c2CC3C)C)C4(C)(C),Training,0,0,116,0.7580548661514465,37.3,88.32230000000004,2.0707036211499066,738.8095187527033,296.41,4.622120000000004
+4510,4518,71-43-2,c1ccccc1,Training,0,0,30,0.4426283718993647,0.0,26.441999999999993,3.000000000000001,71.96100505779535,78.11399999999999,1.6866
+4511,4519,71432-00-3,O=C1Oc3cccc4ccc2c5ccccc5(cc1c2c34),Training,1,1,98,0.2319919573723225,30.21,86.18800000000005,2.27906791182722,1198.3727718795842,270.28700000000003,4.690400000000002
+4512,4520,71439-68-4,N(=Cc2c4ccccc4(c(C=NNC1=NCCN1)c3ccccc23))NC5=NCCN5,Training,1,0,150,0.3058290518660376,97.56,123.52280000000002,1.5827950261677926,1057.4572908330144,398.4740000000001,1.7584
+4513,4521,7144-65-2,O(c1ccccc1c2ccccc2)CC3OC3,Training,1,1,86,0.7469736205070414,21.759999999999998,67.11300000000003,1.8669007692822677,489.28482335989,226.27499999999998,3.1312000000000015
+4514,4522,71461-13-7,O=C5NCCCN4C(=O)C2c3cc(ccc3(OC2(c1ccc(O)cc1)))C(NCCCNCCCC4)C5,Training,1,0,192,0.48833070042891114,102.93,136.94689999999994,1.580847467703622,1073.7193984767937,492.6200000000004,2.7523
+4515,4523,7151-65-7,O=C(N(c2ccc3c1ccccc1Cc3(c2))Cl)C,Training,1,1,90,0.6079953950134159,20.310000000000002,73.69700000000003,2.0584506803015623,636.1407700417452,257.71999999999997,3.7645000000000026
+4516,4524,71-58-9,O=C(OC3(C(=O)C)(CCC2C4CC(C1=CC(=O)CCC1(C)C4(CCC23(C)))C))C,Training,0,0,154,0.6479725905950843,60.440000000000005,106.43500000000006,1.734944964196879,766.5668378003054,386.53200000000027,4.655200000000004
+4517,4525,716-53-0,c1ccc3c(c1)cc2ccccc2c3Cl,Training,1,1,72,0.476239910717608,0.0,66.46400000000003,2.597968359562711,586.9571121386949,212.67899999999997,4.646400000000002
+4518,4526,7166-19-0,O=[N+]([O-])C(=Cc1ccccc1)Br,Training,1,1,62,0.44325273862482306,43.14,50.34040000000002,2.8853850923674402,308.0937159610996,228.045,2.656600000000001
+4519,4527,71708-92-4,O=C(N(O)c2ccc(Oc1ccccc1)cc2)C,Training,1,1,92,0.664763782197782,49.77000000000001,67.90450000000003,2.108917162710057,522.495184574245,243.262,3.221000000000002
+4520,4528,71711-58-5,n2c1ccccc1c(N)c4c2c3ccccc3c(c4C)C,Training,1,1,102,0.3707144776263095,38.91,90.64140000000005,2.389517548466925,1016.2248613404705,272.351,4.740240000000003
+4521,4529,71712-70-4,O=[N+]([O-])c1cc2Oc3cc(c(cc3(Oc2(cc1Cl)))Cl)Cl,Training,1,1,102,0.43870737828155953,61.60000000000001,74.71640000000001,2.1055893445916682,747.9676732974996,332.52599999999995,5.453
+4522,4530,71721-78-3,O=[N+]([O-])c1ccc2Oc3cc(c(cc3(Oc2(c1)))Cl)Cl,Training,1,1,96,0.47795504324837423,61.60000000000001,69.70640000000002,2.0638674468365306,702.3690056496682,298.081,4.799600000000001
+4523,4531,7177-48-2,O=C(O)C3N2C(=O)C(NC(=O)C(N)c1ccccc1)C2SC3(C)(C),Training,0,0,128,0.674878289478739,112.73,89.02890000000004,1.7112933155712995,693.8227554205864,349.4120000000001,0.3181000000000016
+4524,4532,71989-02-1,O=C4C=Cc3c(ccc2c3(cc1ccccc1c2C))C4(=O),Training,1,1,100,0.4562203384585343,34.14,84.56250000000004,2.199011710626233,977.6850071803799,272.30300000000005,4.080020000000003
+4525,4533,7203-89-6,N(=NN(C)C)c1ccc(cc1)C,Training,1,1,64,0.4860912313592322,27.96,49.38200000000003,2.706956244721752,261.6070662599115,163.224,2.555320000000001
+4526,4534,7203-90-9,N(=NN(C)C)c1ccc(cc1)Cl,Training,1,1,64,0.5119618328537084,27.96,49.65500000000003,2.706956244721752,266.1363912728923,183.642,2.9003000000000014
+4527,4535,720-39-8,Oc1c(cc(cc1CCCC)C)CCCC,Training,0,0,90,0.753691555657265,20.23,70.06780000000005,2.8646651470372144,299.20199071205565,220.35599999999994,4.385820000000003
+4528,4536,720-69-4,O=[N+]([O-])c1oc(cc1)c2nc(nc(n2)N)N,Training,1,1,82,0.5404568565334668,146.99,53.008199999999995,2.4571948403321913,530.5552338152961,222.16399999999996,0.20419999999999994
+4529,4537,72076-98-3,c1ccc5c(c1)cc4c3c5(ccc2cccc(c23)s4),Training,1,1,88,0.3079063166704208,0.0,85.52900000000004,2.2480153075374427,1051.9638030765223,258.34499999999997,5.798700000000003
+4530,4538,7209-38-3,NCCCN1CCN(CC1)CCCN,Training,0,1,84,0.5952506871493568,58.519999999999996,60.222800000000035,2.050711007149777,116.08368795993283,200.32999999999993,-0.6983999999999977
+4531,4539,7213-59-4,O=C1c3cc(OC)c(O)c(O)c3(C(=O)c2c(O)cc(cc12)C),Training,1,1,112,0.5928757043181082,104.06000000000002,76.0324,2.389209314026651,850.445027953344,300.266,1.8958199999999994
+4532,4540,7213-98-1,O=C(Oc2cc3c1ccccc1Cc3(cc2(NC(=O)C)))C,Training,0,0,106,0.5796726912984221,55.4,80.29670000000003,2.1152023422637276,749.695594719366,281.311,3.1415000000000015
+4533,4541,72-14-0,O=S(=O)(Nc1nccs1)c2ccc(N)cc2,Training,0,0,84,0.8143349412643328,85.08,63.77690000000001,2.288913081719446,561.3113832440436,255.324,1.5260999999999998
+4534,4542,7220-79-3,n2c1ccc(cc1[s+]c3cc(ccc23)N(C)C)N(C)C,Training,1,1,102,0.5259574390794158,19.370000000000005,90.18700000000005,2.239459442556533,718.1229424173976,284.408,3.862600000000003
+4535,4543,7220-81-7,O=C4Oc2c(c(OC)cc1OC3OCCC3(c12))C5=C4C(=O)CC5,Training,1,1,118,0.7508817717087567,74.97,79.41350000000004,1.9225336103410824,925.0511164682891,314.29300000000006,2.1529
+4536,4544,7224-61-5,Oc1cc3c(cc1(OC))c2c(O)c(OC)cc4c2C(C3)[N+](C)(C)CC4,Training,0,1,132,0.8239342622955291,58.92,95.43600000000005,2.078323043050076,872.7303670871274,342.41500000000013,3.011700000000001
+4537,4545,7226-23-5,O=C1N(C)CCCN1C,Training,0,1,52,0.4621772024730005,23.550000000000004,35.272999999999996,2.515222059861384,112.22626787690945,128.17499999999998,0.37370000000000014
+4538,4546,72273-04-2,O=C(OC4CCC2(C)(C(CCC1C3CCC(=O)NC3(C)(CCC12))C4))COc5ccc(cc5)N(CCCl)CCCl,Training,1,1,216,0.2799947751444189,67.87,155.6376999999997,1.119121239815919,1016.3462150462826,579.6090000000002,6.1725000000000065
+4539,4547,7227-91-0,N(=NN(C)C)c1ccccc1,Training,1,1,58,0.46784626756697373,27.96,44.64500000000003,2.64692987899982,228.35230342705086,149.19699999999997,2.2469
+4540,4548,7227-92-1,O=[N+]([O-])c1ccc(N=NN(C)C)cc1,Training,1,1,74,0.42015228368007346,71.1,51.29940000000003,2.7843380621672704,344.8638413380406,194.194,2.1551
+4541,4549,7230-71-9,n2c4cc(ccc4(cc3ccc1ccccc1c23))C,Training,1,1,90,0.31760721028739625,12.89,81.49200000000005,2.2321129096615655,922.3919838784873,243.30899999999997,4.849620000000003
+4542,4550,72-33-3,C#CC3(O)(CCC2C4CCc1cc(OC)ccc1C4(CCC23(C))),Training,0,0,122,0.7968347529245803,29.46,91.39380000000006,1.6961562138560808,672.9094096754335,310.4370000000001,3.915600000000003
+4543,4551,723-46-6,O=S(=O)(Nc1noc(c1)C)c2ccc(N)cc2,Training,0,0,90,0.804736706639606,98.22,62.90290000000002,2.2767262836744524,616.5006093542685,253.28300000000002,1.3660199999999998
+4544,4552,7239-21-6,N(=NN(C)C)c1ccc(cc1)Br,Training,1,1,64,0.5643618033023852,27.96,52.34500000000003,2.706956244721752,266.1363912728923,228.093,3.009400000000002
+4545,4553,7241-98-7,O=C4Oc2c(c(OC)cc1OC3OCCC3(c12))C5=C4C(=O)OCC5,Training,0,1,124,0.5814144633232288,84.2,80.74850000000004,1.9098301451070883,942.3302052743265,330.2920000000001,1.7369
+4546,4554,72-43-5,O(c1ccc(cc1)C(c2ccc(OC)cc2)C(Cl)(Cl)Cl)C,Training,0,0,112,0.7085299188898864,18.46,88.12100000000005,2.4145368579066235,526.466238471707,345.65299999999996,5.205900000000002
+4547,4555,7247-89-4,O=NN1CCCCC1C,Training,1,1,52,0.5016490979836264,32.67,35.814,2.3818344572967423,105.2309826803223,128.17499999999998,1.5422
+4548,4556,72-48-0,O=C1c3ccccc3(C(=O)c2c(O)c(O)ccc12),Training,1,1,88,0.5881110894792267,74.60000000000001,63.07860000000002,2.376755012054768,700.9353339687136,240.21399999999997,1.8732000000000002
+4549,4557,72492-12-7,O=C(c1ccc2OC3(C(=O)c2(c1))(CC3))C,Training,0,1,76,0.6539576541194553,43.370000000000005,53.37000000000002,2.112863475792027,483.6406409737161,202.20899999999995,1.9969000000000001
+4550,4558,7251-61-8,n1cc(nc2ccccc12)C,Training,0,1,54,0.5642936655816758,25.78,44.27500000000002,2.8289012156206965,381.97444633457127,144.17699999999996,1.93822
+4551,4559,72-54-8,c1cc(ccc1C(c2ccc(cc2)Cl)C(Cl)Cl)Cl,Training,0,0,94,0.6150214671313038,0.0,80.24100000000003,2.394110502884274,456.8221302041951,320.04599999999994,5.929000000000001
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+4555,4563,7269-58-1,ONc3nc(nc1c3(ncn1C2OC(CO)C(O)C2(O)))N,Training,1,1,114,0.3419937187481579,171.80000000000004,68.15400000000001,2.0748998812312083,662.670852889115,298.25900000000007,-2.1789
+4556,4564,7269-60-5,ONc2ncnc1c2(ncn1C),Training,1,1,62,0.5886566762746205,75.86000000000001,41.71320000000001,2.808944183706691,409.23069144666033,165.156,0.16439999999999994
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+4559,4567,72848-48-7,O=[N+]([O-])c1ccc2nc3cc(ccc3(nc2(c1)))[N+](=O)[O-],Training,1,1,98,0.4015305561084459,112.06,70.35280000000002,2.274801712549187,804.3400089999907,270.204,2.599400000000001
+4560,4568,72917-35-2,O=[N+]([O-])c3cc(c2[nH]c1ccc(O)cc1c2c3C)C,Training,1,1,96,0.5158033651518613,79.16,73.59790000000002,2.5723920546707086,833.6801440616598,256.26099999999997,3.5517400000000015
+4561,4569,7297-53-2,O=[N+]([O-])c2ccc(C=Cc1cccc(c1)Cl)cc2,Training,1,1,90,0.46519105126972965,43.14,73.47640000000003,2.160505591340602,590.9979162169989,259.692,4.418600000000002
+4562,4570,72999-11-2,O=C(OC)C(=Cc1occc1)[N+](=O)[O-],Training,0,1,74,0.31298311367518034,82.58,45.695400000000014,2.9948046311316103,365.0931746965848,197.146,1.0702
+4563,4571,7300-59-6,O=C(O)C(N)CCC(=O)Nc1ccc(cc1)[N+](=O)[O-],Training,0,0,102,0.5130044545298578,135.56,66.57130000000001,2.4821873850316902,485.60895402638675,267.24100000000004,0.7253999999999999
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+4565,4573,73-03-0,OCC3OC(n2cnc1c(ncnc12)N)C(O)C3,Training,1,0,96,0.6289933028308912,119.31,61.35500000000002,2.023736127462716,571.6385353073613,251.246,-0.9508000000000005
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+4567,4575,7319-59-7,O=C(OC4c3c5ccc1ccccc1c5(cc2ccc(c(c23)C4)C))C,Training,1,1,122,0.2578852626927453,26.3,101.90800000000006,1.9662007525025087,1187.2474112917175,326.39500000000015,5.614920000000004
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+4569,4577,732-11-6,O=C1c2ccccc2(C(=O)N1CSP(OC)(OC)=S),Training,1,1,102,0.6141947029028371,55.84,77.70300000000003,2.1502393965191064,534.5685423942925,317.328,2.4906000000000006
+4570,4578,73-22-3,O=C(O)C(N)Cc2c[nH]c1ccccc12,Training,0,0,78,0.7005840997557369,79.10999999999999,57.61390000000001,2.323487371389896,490.0485079143074,204.229,1.1222999999999996
+4571,4579,7330-46-3,O=C(O)c1cc(ccc1(N))Cc2ccc(N)c(c2)C(=O)O,Training,0,1,108,0.6350273335044233,126.64,78.43340000000002,2.343406344129218,664.1087112218187,286.287,1.8382
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+4574,4582,73391-96-5,O=C(N(C)Cc1ccccc1)CBr,Training,0,0,70,0.7425305796785823,20.310000000000002,56.71000000000003,2.5472307422433684,273.51305165552594,242.11599999999996,2.0399
+4575,4583,7350-43-8,O=C(Nc2nc(C=Cc1oc(cc1)[N+](=O)[O-])cs2)C,Training,1,1,98,0.6849634278672869,98.27000000000001,70.70810000000002,2.0661854984558023,643.9158995413609,279.277,2.7731000000000012
+4576,4584,73536-69-3,O=C(OC)c2cc(OC)c1OCOc1c2c3c4OCOc4(c(OC)cc3(C(=O)OC)),Training,0,0,158,0.6717520105490448,107.98000000000003,99.90700000000004,2.134151917831438,959.3583105509791,418.3540000000002,2.4014000000000006
+4577,4585,736-31-2,O=[N+]([O-])c2ccc(C=Cc1ccc(cc1)[N+](=O)[O-])cc2,Training,1,1,100,0.48145243168898105,86.28,75.12080000000002,2.1199984091074437,601.0781883983251,270.24399999999997,3.6734000000000027
+4578,4586,73747-10-1,O=CN(O)c1ccc(cc1)C(=O)OCC,Training,0,1,80,0.35012927426034324,66.84,52.72800000000002,2.800283453172375,346.9449504144883,209.20099999999996,1.2153
+4579,4587,7379-35-3,n1ccc(cc1)Cl,Training,0,0,36,0.4994929876185536,12.89,29.246999999999993,3.0214653097240864,138.00750422530467,113.54699999999998,1.7349999999999999
+4580,4588,73819-63-3,N=C(N)c1ccc2cc([nH]c2(c1))C(=N)N,Training,0,0,76,0.36387605050138516,115.52999999999999,60.33089999999999,2.6167820091918674,539.938131717691,201.23299999999998,0.7360400000000002
+4581,4589,73870-33-4,O=NN1CCSC1,Training,1,1,40,0.47435747774375076,32.67,29.825999999999993,2.261812524676334,71.33515884998701,118.16100000000002,0.6741
+4582,4590,73931-96-1,OC(c1ccc(cc1)CCc2ccccc2)Cn3cncc3,Training,0,1,112,0.7558843983930712,38.05,87.47880000000004,1.5753917798656496,675.2240714463726,292.382,3.4019000000000013
+4583,4591,73936-27-3,O=C(c1ccc(F)cc1)C3OC3(c2ccccc2),Training,1,0,90,0.610905295634544,29.6,64.78650000000003,1.748522067538629,562.8072898380785,242.24900000000002,3.148500000000001
+4584,4592,74006-72-7,O=C2N1C=CCSC1C2,Training,0,0,48,0.4650862458535039,20.310000000000002,36.84900000000001,2.1572338008607796,177.89667380414838,141.195,0.8052999999999999
+4585,4593,74011-58-8,O=C(O)C1=CN(c2nc(c(F)cc2(C1(=O)))N3CCNCC3)CC,Training,1,1,122,0.8639190651701679,87.46,83.67700000000004,2.2435848523617365,827.5622879687312,320.32400000000007,0.6632999999999998
+4586,4594,74014-51-0,O=CCC3CC(C)C(O)C=CC=CCC(OC(=O)CC(O)C(OC)C3(OC2OC(C)C(OC1OC(C)C(OC(=O)CCC)C(OC(=O)CC)(C)C1)C(N(C)C)C2(O)))C,Training,0,0,332,0.1385675399653257,206.04999999999998,209.92139999999918,1.9533192840625249,1375.6409265424259,828.0059999999999,3.157500000000005
+4587,4595,74-11-3,O=C(O)c1ccc(cc1)Cl,Training,0,0,52,0.675780363757627,37.3,38.41130000000001,3.003400684579817,240.28794892648057,156.56799999999998,2.0382
+4588,4596,7417-67-6,O=NN(C(=O)C)C,Training,1,1,40,0.3491384766632692,49.74,24.23899999999999,3.5517136080297,90.93569696954751,102.09299999999999,0.1461
+4589,4597,7422-80-2,NN(CCCC)CCCC,Training,0,1,62,0.4544441388834873,29.259999999999998,45.57640000000002,2.998419094375296,56.27793097483525,144.262,1.7622999999999995
+4590,4598,74-31-7,c1ccc(cc1)Nc2ccc(cc2)Nc3ccccc3,Training,1,0,98,0.6755389731083973,24.06,85.89140000000003,1.686284399522532,585.5180499526653,260.34000000000003,5.173800000000003
+4591,4599,7433-46-7,O=C(NO)NC,Training,0,1,36,0.2719889894485342,61.36,19.377899999999997,2.98816088213427,47.50977500432694,90.082,-0.6954
+4592,4600,74339-98-3,OC6C=Cc2c(cc4c5ccccc5(cc3c1ccccc1c2c34))C6(O),Training,1,1,124,0.3880160938995494,40.46,105.88460000000002,1.9046177446302495,1266.4272064237755,336.3900000000001,5.061500000000003
+4593,4601,74339-99-4,Oc1ccc4c(c1)c6cc2ccccc2c5cc3ccccc3c4c56,Training,1,1,116,0.25024545327083253,20.23,105.05480000000001,1.9810360346207097,1345.208199598747,318.37500000000006,6.499200000000004
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+4595,4603,74367-78-5,O=[N+]([O-])c1cc(cc(c1)CCl)[N+](=O)[O-],Training,1,1,74,0.44043099545835235,86.28,49.30780000000001,3.2679787262619246,361.0262266208624,216.57999999999996,2.2417999999999996
+4596,4604,7437-61-8,O1CC1C(=C)C,Training,0,0,34,0.34031651735635815,12.53,24.553999999999988,2.3076098467926744,72.00763013991067,84.118,0.9613
+4597,4605,74407-28-6,O=C(O)C(NC(=O)C(C)(C)SC)CSC,Training,0,0,88,0.7387087312976244,66.4,65.54250000000003,4.4148412442507885,243.51195590771968,251.37299999999996,1.0604000000000002
+4598,4606,74407-29-7,O=C(O)C(NC(=O)C(C)(C)SC)CS,Training,0,0,82,0.6135307980005817,66.4,61.01350000000003,4.370487188982251,230.6262814412585,237.34599999999998,0.6272000000000002
+4599,4607,74494-65-8,O=C1c5c(O)cc(OC)c(OC)c5(Oc3c1c(OC)cc2OC4OCCC4(c23)),Training,0,0,146,0.6866463541402932,96.59000000000002,99.03680000000003,1.9827929422384551,1178.9764773258244,386.35600000000017,2.9000000000000004
+4600,4608,74518-94-8,N#Cc1ccc(cc1)C=Cc2ccc(cc2)[N+](=O)[O-],Training,1,1,92,0.4741795495940828,66.92999999999999,73.18140000000002,2.13084641342113,650.0400842263577,250.25699999999998,3.6368800000000023
+4601,4609,74518-99-3,Nc1ccc(cc1)C=Cc2ccc(cc2)C(C)(C)C,Training,0,1,98,0.6053747329056725,26.02,84.92440000000005,2.1322056731771823,554.134432824983,251.373,4.7367000000000035
+4602,4610,74550-97-3,O=C1N(C(=O)CN(C1)CCN2CC(=O)N(C(=O)C2)CN3CCOCC3)CN4CCOCC4,Training,1,0,178,0.3690557905658973,106.18,111.10400000000006,1.2101541098882915,627.3687595666211,452.51200000000046,-3.092599999999991
+4603,4611,746-53-2,O=C3c1cc(cc(c1c2c3(cc(cc2[N+](=O)[O-])[N+](=O)[O-]))[N+](=O)[O-])[N+](=O)[O-],Training,1,1,130,0.49644940829710826,189.63,81.92810000000001,2.4791185710100616,992.2697650588468,360.1940000000001,2.530800000000002
+4604,4612,74669-74-2,[N-]=[N+]=NCC(c1ccccc1)C,Training,1,1,62,0.3713248544843179,48.760000000000005,48.87000000000003,2.6469818394117546,275.08493892361554,161.20799999999997,3.1004000000000014
+4605,4613,7467-29-0,N(=Nc1cc(c(N)cc1(N))C)c2ccccc2C,Training,1,1,92,0.6168352408731984,76.75999999999999,75.35880000000003,2.3505773722593326,602.738141212672,240.31,3.8832400000000025
+4606,4614,7470-44-2,O1c2ccc(cc2(OC1))CC3OC3,Training,1,1,68,0.6404645149548036,30.990000000000002,46.00900000000002,1.8575611678121788,330.94178503314396,178.18699999999998,1.3566
+4607,4615,7473-93-0,O=C(C=Cc1ccccc1[N+](=O)[O-])c2ccccc2,Training,0,1,94,0.3624325584082813,60.209999999999994,72.90290000000003,2.243975939121589,632.848763379062,253.257,3.4909000000000026
+4608,4616,74-83-9,CBr,Training,1,1,14,0.3936198519990384,0.0,14.851,1.0,2.0,94.939,1.0110999999999999
+4609,4617,74-85-1,C=C,Training,0,1,12,0.34449676855385364,0.0,11.254000000000001,2.0,0.0,28.053999999999995,0.8022
+4610,4618,74-87-3,CCl,Training,1,1,14,0.3573626606013345,0.0,11.777000000000001,1.0,2.0,50.488,0.855
+4611,4619,74877-25-1,O=C4C=Cc2c(ccc1cc3ccccc3(cc12))C4(=O),Training,0,1,94,0.4540836879842761,34.14,79.82550000000005,2.1481650233800624,932.7045318677233,258.276,3.771600000000002
+4612,4620,74-89-5,NC,Training,0,0,14,0.3846582089034356,26.02,10.111400000000001,1.0,2.0,31.058,-0.42510000000000003
+4613,4621,7493-63-2,O=C(OCC=C)c1ccccc1(N),Training,0,0,68,0.43325930054722267,52.32,51.33390000000002,2.763274759761523,320.4557138372428,177.20299999999997,1.6116
+4614,4622,7493-72-3,O=C(OCC=C)CCCCCCCC,Training,0,0,82,0.32198636276143106,26.3,59.14900000000004,3.1023058070917937,152.40071895207583,198.30599999999995,3.4662000000000024
+4615,4623,74940-61-7,O=C(OC(C(Cl)(Cl)Cl)P(=O)(OC)OC)CCl,Training,0,1,96,0.43950960556111673,61.83000000000001,62.51450000000003,5.097550406333505,283.1337072343085,333.9190000000001,2.9506000000000014
+4616,4624,74-95-3,C(Br)Br,Training,1,1,20,0.49009217871796995,0.0,22.720999999999997,1.6329931618554523,2.7548875021634682,173.83499999999998,1.7337
+4617,4625,74-96-4,CCBr,Training,1,1,20,0.4121785720964007,0.0,19.467999999999996,1.6329931618554523,2.7548875021634682,108.966,1.4012
+4618,4626,74-97-5,C(Cl)Br,Training,1,1,20,0.43570756213837314,0.0,19.647,1.6329931618554523,4.754887502163468,129.38400000000001,1.5776
+4619,4627,74992-96-4,o2c1ccccc1c3cccc(c23)Cl,Training,0,1,68,0.531560836348283,13.14,58.730000000000025,2.6327288472456125,609.8208026305191,202.64,4.239400000000002
+4620,4628,75005-80-0,O=C(O)C(N)CSc1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,0,100,0.4672833841790998,63.31999999999999,77.8272,3.067120111992683,467.3317184446203,369.4839999999999,4.457600000000001
+4621,4629,75-04-7,NCC,Training,0,0,20,0.40623709538988323,26.02,14.728400000000002,1.6329931618554523,2.7548875021634682,45.084999999999994,-0.03499999999999992
+4622,4630,75-05-8,N#CC,Training,0,0,16,0.3869805798690774,23.79,11.287,2.475534205527556,24.264662506490403,41.053,0.52988
+4623,4631,75-07-0,O=CC,Training,0,0,18,0.35500761339323206,17.07,11.738000000000001,2.1874960973678963,10.264662506490405,44.053,0.2052
+4624,4632,75-09-2,C(Cl)Cl,Training,1,1,20,0.3899621067041533,0.0,16.573,1.6329931618554523,2.7548875021634682,84.933,1.4215
+4625,4633,75-11-6,C(I)I,Training,0,1,20,0.46398027064292247,0.0,32.907,1.6329931618554523,2.7548875021634682,267.835,1.8139
+4626,4634,75-12-7,O=CN,Training,0,0,18,0.35232551302052717,43.09,10.2514,2.1874960973678963,12.264662506490405,45.041,-0.8985000000000001
+4627,4635,75-15-0,C(=S)=S,Training,0,1,16,0.3949540667862806,0.0,20.189,3.2659863237109046,23.774437510817343,76.14500000000001,1.0181
+4628,4636,75-21-8,O1CC1,Training,1,1,18,0.3490215851763434,12.53,10.819,2.25,7.509775004326937,44.05299999999999,0.01660000000000006
+4629,4637,75-25-2,C(Br)(Br)Br,Training,1,1,26,0.5812778100557083,0.0,30.569,2.3237900077244498,8.0,252.731,2.4547
+4630,4638,75-26-3,CC(C)Br,Training,1,1,26,0.43047180293883447,0.0,24.06299999999999,2.3237900077244498,8.0,122.993,1.7897
+4631,4639,75-29-6,CC(C)Cl,Training,1,0,26,0.38654183387765095,0.0,20.988999999999994,2.3237900077244498,8.0,78.542,1.6336
+4632,4640,75-31-0,NC(C)C,Training,0,0,26,0.4279299473771721,26.02,19.323399999999996,2.3237900077244498,8.0,59.111999999999995,0.3534999999999999
+4633,4641,75321-20-9,O=[N+]([O-])c4cc(c1ccc3cccc2ccc4(c1c23))[N+](=O)[O-],Training,1,1,106,0.31104141056791274,86.28,83.45480000000005,2.3856373136583957,1009.0603402813747,292.25,4.400400000000002
+4634,4642,75-33-2,CC(C)S,Training,0,0,26,0.4132813626628286,0.0,24.12199999999999,2.3237900077244498,8.0,76.164,1.3246
+4635,4643,75-34-3,CC(Cl)Cl,Training,0,1,26,0.40598289011150185,0.0,21.167999999999992,2.3237900077244498,8.75488750216347,98.96000000000001,1.81
+4636,4644,75-36-5,O=C(C)Cl,Training,0,1,24,0.3913403492364148,17.07,16.534,2.8030394876740514,29.019550008653873,78.498,0.7717
+4637,4645,75-38-7,FC(F)=C,Training,1,0,24,0.3990350582423506,0.0,11.356000000000002,2.8030394876740514,27.019550008653873,64.034,1.3966
+4638,4646,75453-80-4,OC1C=CC=CC1(O),Training,1,0,44,0.45662242737573333,40.46,30.29359999999999,2.593169849673516,110.49022499567306,112.12799999999997,-0.16580000000000011
+4639,4647,75464-10-7,O=C2c1c(O)cccc1C(C(=O)CC)c3cccc(O)c23,Training,1,1,106,0.8877872829455343,74.6,76.78710000000002,2.3710370679971913,705.8805794733357,282.29499999999996,2.753200000000002
+4640,4648,75464-11-8,O=C2c1c(O)cccc1C(C(=O)CCC)c3cccc(O)c23,Training,1,1,112,0.9121086487559602,74.6,81.40410000000003,2.3091366533769264,721.1517782005485,296.322,3.143300000000002
+4641,4649,75476-80-1,O=[N+]([O-])c1ccc2C=CCc2(c1),Training,1,1,60,0.4675506871457863,43.14,45.83440000000002,2.486611500859599,368.7913266885617,161.15999999999997,2.1641000000000004
+4642,4650,75-47-8,C(I)(I)I,Training,1,0,26,0.43826332672952517,0.0,45.848,2.3237900077244498,8.0,393.731,2.575
+4643,4651,75-50-3,N(C)(C)C,Training,0,0,26,0.3844627806876072,3.24,19.610999999999997,2.3237900077244498,8.0,59.111999999999995,0.17779999999999996
+4644,4652,75584-89-3,O=C(OCC)C[n+]2csc1ccccc12,Training,0,0,78,0.5847910260307213,30.18,58.653000000000034,2.2470093153797634,478.1475866267328,222.28900000000002,1.7519
+4645,4653,75586-69-5,Nc1ccc3c(c1)cc2ccccc2[n+]3C,Training,1,1,78,0.3437321503567664,29.9,67.04240000000001,2.5522572697909602,686.695477667872,209.27200000000002,2.3997
+4646,4654,75586-70-8,Nc2ccc3cc1ccccc1[n+](c3(c2))C,Training,1,1,78,0.3437321503567664,29.9,67.04240000000003,2.5581440319024598,686.695477667872,209.272,2.399700000000001
+4647,4655,75605-59-3,Nc3cccc2c3(cc1ccccc1[n+]2C),Training,1,1,78,0.3437321503567664,29.9,67.04240000000001,2.60851239964224,686.695477667872,209.27200000000002,2.3997
+4648,4656,75-62-7,C(Cl)(Cl)(Cl)Br,Training,1,0,32,0.5249350243396338,0.0,29.217,3.0237157840738176,22.364527976600282,198.274,2.709
+4649,4657,75-64-9,NC(C)(C)C,Training,0,0,32,0.4494698079729435,26.02,23.94039999999999,3.0237157840738176,19.11941547876375,73.139,0.7435999999999998
+4650,4658,75-65-0,OC(C)(C)C,Training,0,0,32,0.4498276567484776,20.23,21.971799999999995,3.0237157840738176,19.11941547876375,74.12299999999999,0.7772
+4651,4659,756-79-6,O=P(OC)(OC)C,Training,0,1,44,0.5168665462879803,35.53,27.548499999999986,3.605378627989909,82.18080946738405,124.076,1.1020999999999999
+4652,4660,75-69-4,FC(Cl)(Cl)Cl,Training,0,1,32,0.4494251669146117,0.0,21.398,3.0237157840738176,22.364527976600282,137.368,2.2836
+4653,4661,7570-36-7,Nc1ccc(cc1)C=Cc2ccc(cc2)Cl,Training,1,1,80,0.6092380415361511,26.02,71.23440000000002,2.1451719267172638,435.6487204825034,229.71,4.092600000000002
+4654,4662,7570-37-8,O(c1ccc(cc1)C=Cc2ccc(N)cc2)C,Training,1,1,86,0.6410985982688429,35.25,72.77640000000002,2.1109804944447195,497.4499584541679,225.291,3.447800000000001
+4655,4663,7570-86-7,O=C(c1ccccc1)C3OC3(c2ccccc2),Training,1,0,84,0.5921457375820811,29.6,64.82850000000003,1.7569177897081505,519.1327878285447,224.259,3.009400000000001
+4656,4664,75-75-2,O=S(=O)(O)C,Training,0,1,32,0.4136209139685819,54.370000000000005,17.4726,4.062942298971397,90.06147084052891,96.10699999999999,-0.4959999999999998
+4657,4665,7576-88-7,n1c2ccc(N)cc2(nc(c1C)C),Training,1,1,66,0.6181628753165421,51.8,53.42440000000001,2.811483140521329,462.9216660819962,173.219,1.8288399999999998
+4658,4666,75776-00-0,n3c1ccccc1c(Nc2ccc(cc2)NC)c4ccccc34,Training,1,1,112,0.5121626718912051,36.95,98.52040000000001,1.908519081049725,920.8423481405422,299.37700000000007,5.173300000000004
+4659,4667,758-17-8,O=CN(N)C,Training,0,1,30,0.18653972448946946,46.33,18.0144,2.825749368745867,34.62919048309069,74.083,-1.0517
+4660,4668,75-83-2,CCC(C)(C)C,Training,0,0,38,0.4244820558666797,0.0,29.74599999999998,3.168489872670569,29.793193904479523,86.17799999999998,2.442500000000001
+4661,4669,75-86-5,N#CC(O)(C)C,Training,0,0,34,0.4292284727392028,44.019999999999996,21.91079999999999,3.552734354515761,74.52932501298082,85.106,0.28087999999999996
+4662,4670,75-87-6,O=CC(Cl)(Cl)Cl,Training,1,1,36,0.3753007229893145,17.07,26.353999999999996,3.4459912135188384,54.303762523798156,147.388,1.5555
+4663,4671,75-88-7,FC(F)(F)CCl,Training,0,0,38,0.4255929603251894,0.0,16.775,3.1684898726705697,38.54808140664299,118.48500000000001,1.7874999999999999
+4664,4672,75888-03-8,O=C2NCCCN2(N=Cc1oc(cc1)[N+](=O)[O-]),Training,1,1,90,0.4805386916367579,100.98,57.67810000000001,2.032342451100008,467.31583991002196,238.203,0.9370000000000003
+4665,4673,75-91-2,OOC(C)(C)C,Training,1,1,38,0.3583142880462129,29.46,23.46679999999999,3.168489872670569,35.30296890880646,90.12199999999999,1.2745
+4666,4674,75-95-6,C(C(Br)(Br)Br)(Br)Br,Training,0,1,44,0.5169935219365547,0.0,51.153999999999996,3.541196965079901,51.5907190016011,424.54999999999995,3.9408000000000003
+4667,4675,75965-74-1,O=[N+]([O-])c2oc3ccc1cc(OC)ccc1c3(c2),Training,1,1,90,0.5099675074346546,65.51,66.92640000000003,2.344600291343398,760.112381529298,243.218,3.5028000000000015
+4668,4676,75-96-7,O=C(O)C(Br)(Br)Br,Training,1,1,42,0.6934818139095419,37.3,37.1478,3.7911184170869663,83.42592196522058,296.74,1.9095
+4669,4677,7597-18-4,O=[N+]([O-])c1ccc2c[nH]nc2(c1),Training,1,1,60,0.5106665276804899,71.82,42.748100000000015,2.676772326608393,434.89903839344754,163.13599999999997,1.4710999999999999
+4670,4678,759-73-9,O=NN(C(=O)N)CC,Training,1,1,46,0.41004372556157603,75.76,27.758399999999998,3.6923370937539612,102.70165766734146,117.108,0.06840000000000024
+4671,4679,75-99-0,O=C(O)C(C)(Cl)Cl,Training,0,0,42,0.5606960201798938,37.3,27.746799999999997,3.7911184170869663,83.42592196522058,142.969,1.2648
+4672,4680,759-94-4,O=C(N(CCC)CCC)SCC,Training,0,0,72,0.662395742153617,20.310000000000002,55.68300000000004,3.8107947551711403,121.69694286392863,189.32399999999998,2.9815000000000014
+4673,4681,75996-85-9,O=C(O)c2c1ccccc1n(c2CC(=O)OCC)C,Training,0,0,100,0.8543823201147319,68.53,70.21530000000003,2.581782136032951,642.17853728502,261.27699999999993,1.9821
+4674,4682,76002-91-0,OCC(O)COc1ccc(cc1)C(c3ccc(OCC2OC2)cc3)(C)C,Training,1,0,140,0.6742030578701383,71.45,98.83460000000005,1.6385721299032703,689.346305600797,358.4340000000002,2.522100000000001
+4675,4683,76014-81-8,O=NN(C)CCCC(O)c1cnccc1,Training,1,1,82,0.5693358833751837,65.79,56.85580000000004,2.3054293060687807,291.9787919131967,209.24900000000002,1.5084
+4676,4684,76-01-7,C(C(Cl)(Cl)Cl)(Cl)Cl,Training,0,0,44,0.5292554442591116,0.0,35.784000000000006,3.541196965079901,51.5907190016011,202.29500000000002,3.1603000000000003
+4677,4685,76024-59-4,OC5c3ccc2ccc1ccccc1c2c3C4OC4C5(O),Training,1,1,104,0.4908991874831261,52.989999999999995,80.03460000000004,1.9546826977928322,886.1504003190425,278.307,2.840800000000002
+4678,4686,76-03-9,O=C(O)C(Cl)(Cl)Cl,Training,0,1,42,0.5487853049557158,37.3,27.925800000000002,3.7911184170869663,83.42592196522058,163.387,1.4412
+4679,4687,76-06-2,O=[N+]([O-])C(Cl)(Cl)Cl,Training,1,1,42,0.236106423574705,43.14,27.284399999999998,3.7911184170869663,85.42592196522058,164.37500000000003,1.5908
+4680,4688,76113-31-0,O=[N+]([O-])c3cc4c1ccccc1sc4(c2ccccc23),Training,1,1,96,0.35845854572030267,43.14,83.49140000000003,2.3287180739681013,987.6983552650007,279.32,5.115900000000002
+4681,4689,76-12-0,FC(C(F)(Cl)Cl)(Cl)Cl,Training,1,0,50,0.5747806664420663,0.0,31.090000000000003,4.020391543176799,67.01955000865388,203.83,3.1882
+4682,4690,76-14-2,FC(F)(C(F)(F)Cl)Cl,Training,0,0,50,0.4197132452520627,0.0,21.6,4.020391543176799,67.01955000865388,170.92000000000002,2.6496
+4683,4691,76150-91-9,n1cc(cc(c1Oc3ccc(Oc2ncc(cc2Cl)Cl)cc3)Cl)Cl,Training,0,1,122,0.4888321000837205,44.24,95.104,1.7297894558722613,799.9514197345779,402.06399999999996,6.674800000000001
+4684,4692,76-15-3,FC(F)(F)C(F)(F)Cl,Training,0,0,50,0.3712282730307422,0.0,16.855,4.020391543176799,65.40990953421706,154.46500000000003,2.3803
+4685,4693,76180-96-6,n1cccc3c1ccc2c3(nc(N)n2C),Training,1,1,74,0.5978088445050177,56.73,60.427400000000006,2.6009884638645255,654.0413933819901,198.22899999999996,1.7037
+4686,4694,76215-00-4,O=NN(COC(=O)C)CCCl,Training,1,1,64,0.20580446038354627,58.970000000000006,39.85400000000001,3.5097668826114585,141.68921982841,180.59099999999998,0.7292000000000001
+4687,4695,7627-38-5,n1cc(c(nc1Cl)Cl)CCl,Training,1,0,54,0.39271985817641186,25.78,41.60900000000001,3.0699827149988397,238.33471446962488,197.452,2.5222000000000007
+4688,4696,764-42-1,N#CC=CC#N,Training,0,0,28,0.3979040779127617,47.58,20.366,3.3552584366267686,105.46396159818461,78.07400000000001,0.5897599999999998
+4689,4697,76547-98-3,O=C(O)C(NC(C(=O)N1CCCC1(C(=O)O))CCCCN)CCc2ccccc2,Training,0,0,160,0.3844882105003129,132.96,108.38670000000005,2.0786943325234626,682.1539555768753,405.4950000000002,1.2352000000000023
+4690,4698,765-87-7,O=C1C(=O)CCCC1,Training,1,0,44,0.4320757620323104,34.14,28.48199999999999,2.5168469087605536,110.49022499567306,112.12800000000001,0.6985999999999999
+4691,4699,7661-55-4,n1cccc2c1cccc2C,Training,1,1,54,0.5519055037199659,12.89,46.48000000000002,2.9131611636048604,374.03449039867854,143.18899999999996,2.5432200000000007
+4692,4700,766-40-5,O=C1OC(O)C(=C1Cl)Cl,Training,1,1,50,0.5382396409815671,46.53,30.830800000000004,2.9203676896441446,186.25176926752528,168.963,0.5508
+4693,4701,7681-76-7,O=C(OCc1ncc(n1C)[N+](=O)[O-])N,Training,1,1,76,0.5411513287875153,113.27999999999999,44.23480000000001,2.7930632523454495,371.908451003585,200.154,-0.07640000000000013
+4694,4702,768-52-5,c1ccc(cc1)NC(C)C,Training,0,0,54,0.6566219386652469,12.03,45.200700000000026,2.5872871851548136,179.17957141667623,135.20999999999998,2.506900000000001
+4695,4703,7696-62-0,O=Nc1ccc(OCCCC)cc1,Training,1,1,70,0.5136347657103706,38.66,52.30000000000003,2.4420703463595097,256.13218516584146,179.219,3.2634000000000016
+4696,4704,7700-17-6,O=C(OC(c1ccccc1)C)C=C(OP(=O)(OC)OC)C,Training,0,0,116,0.3312343964616831,71.06,77.41550000000005,2.636640599406943,531.6550310610563,314.27400000000006,3.6121000000000025
+4697,4705,7704-40-7,n1c3ccc(N)cc3(nc2cc(N)ccc12),Training,1,1,78,0.43881967405074745,77.82,65.86880000000001,2.4397721399992816,633.9788965680244,210.24,1.9473999999999998
+4698,4706,77061-07-5,c2cc1cccc4c1c(c2)c3cccc(c34)CBr,Training,1,1,86,0.41338630040837754,0.0,81.00900000000003,2.242019632535894,766.4121453127873,295.179,5.382100000000003
+4699,4707,77-06-5,O=C(O)C4C2C1(OC(=O)C2(C)(C(O)C=C1))C5CCC3(O)(C(=C)CC45(C3)),Training,0,0,134,0.483832595778226,104.06,85.17340000000002,1.7841261782741378,771.8760069846132,346.3790000000002,1.0270999999999992
+4700,4708,77094-11-2,n1cccc3c1cc(c2c3(nc(N)n2C))C,Training,1,1,80,0.619806442081726,56.73,65.16440000000001,2.646249560160261,696.8679005773128,212.25599999999997,2.01212
+4701,4709,77-09-8,O=C3OC(c1ccc(O)cc1)(c2ccc(O)cc2)c4ccccc34,Training,0,0,118,0.709067432457466,66.76,87.95310000000002,2.0302908457637505,865.6287032132534,318.32800000000003,3.560100000000002
+4702,4710,77109-49-0,O=C(OC)C(NC(=O)C)CSCCBr,Training,1,1,82,0.4449982119123507,55.4,60.73970000000003,3.96938550289363,201.02541316335095,284.17499999999995,0.7922
+4703,4711,77121-90-5,O=C1c5cccc(OC)c5(C(=O)c2c(O)c4c(c(O)c12)CC(O)(C(=O)CO)CC4(OC3OC(C)C(OC)C(N)C3)),Training,1,1,214,0.2660540781510531,195.07,136.54459999999995,1.6658506523159247,1393.355073178428,557.5520000000001,0.6553999999999996
+4704,4712,77191-36-7,O=C(Nc1c(cccc1C)C)CN2C(=O)CCC2,Training,0,0,96,0.8846848475123534,49.410000000000004,70.35970000000003,2.008433178256518,462.432377529722,246.30999999999992,1.8643399999999999
+4705,4713,771-97-1,Nc1cc2ccccc2(cc1(N)),Training,1,1,60,0.5760063964521945,52.04,52.77280000000001,2.8395199428108353,380.60813525322834,158.20399999999998,2.0042
+4706,4714,77287-29-7,O=C(OC)C(C)Cl,Training,1,0,42,0.37973348248125377,26.3,27.33099999999999,3.3530759537985286,70.09004635215048,122.55099999999999,0.7867000000000001
+4707,4715,77376-01-3,O=C(OCc1ccccc1[N+](=O)[O-])C,Training,0,0,74,0.41746665731671206,69.44,48.56640000000002,2.844190583560692,361.5845163250598,195.17399999999995,1.6579
+4708,4716,773-76-2,Oc2c1ncccc1c(cc2Cl)Cl,Training,0,0,66,0.7295228001546941,33.120000000000005,53.42780000000002,2.966872933924146,470.3665095200525,214.051,3.2472000000000003
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+4711,4719,77-47-4,C=1(C(=C(C(C=1Cl)(Cl)Cl)Cl)Cl)Cl,Training,0,1,62,0.5675719606767754,0.0,51.90100000000001,3.266578967542274,234.14620796147236,272.773,4.5523
+4712,4720,77500-04-0,n1cc(nc3c1ccc2c3(nc(N)n2C))C,Training,1,1,80,0.6125617576025736,69.62,62.95940000000001,2.5718613150712626,698.2240623065195,213.24399999999994,1.4071199999999997
+4713,4721,7756-96-9,O=C(OCCCC)c1ccccc1(N),Training,0,0,76,0.4529213480251256,52.32,56.04490000000003,2.564465699481562,309.910770563408,193.246,2.2257000000000002
+4714,4722,7763-77-1,O1CC1Cl,Training,1,1,24,0.30506071112281524,12.53,15.593000000000002,2.1710983178735734,25.219280948873624,78.49799999999999,0.5815
+4715,4723,77-65-6,O=C(N)NC(=O)C(CC)(CC)Br,Training,0,1,70,0.7220176852684498,72.19,49.96610000000001,4.318367796433647,189.84539731095856,237.09699999999995,1.135
+4716,4724,77-78-1,O=S(=O)(OC)OC,Training,1,1,44,0.501308312445765,52.60000000000001,22.937799999999992,3.8856046430784614,112.62522105691478,126.13299999999998,-0.476
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+4718,4726,77784-22-6,O(c5ccc4c(cc2c1c4(c3OCOc3(cc1CCN2C)))c5(OC))C,Training,1,0,128,0.6665071939123058,40.16,97.65500000000004,2.028645090463267,1027.7860721010852,337.37500000000006,3.731200000000003
+4719,4727,7779-16-0,O=C(OC1CCCCC1)c2ccccc2(N),Training,0,0,86,0.6143186418088409,52.32,63.14290000000003,1.995397772280171,369.95027285921793,219.28400000000002,2.7583
+4720,4728,77-79-2,O=S1(=O)(CC=CC1),Training,0,0,40,0.41850281066805456,34.14,27.79379999999999,2.875136890617279,161.8664756744443,118.15699999999998,-0.028999999999999915
+4721,4729,7779-30-8,O=C(C=CC1C(=CCCC1(C)(C))C)CC,Training,0,0,84,0.5052741459050272,17.07,64.70000000000005,2.810012610250731,294.4605612693076,206.32899999999998,3.904200000000003
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+4724,4732,77-81-6,N#CP(=O)(OCC)N(C)C,Training,0,0,58,0.5859314569484154,53.330000000000005,38.532500000000006,4.290343871518226,184.57719722681782,162.129,1.25868
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+4731,4739,77-95-2,O=C(O)C1(O)(CC(O)C(O)C(O)C1),Training,0,0,76,0.3180309828296054,118.22000000000001,39.84000000000001,2.7866006884073427,203.02830685572664,192.167,-2.3214000000000006
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+4738,4746,78281-06-8,O=CN(O)c1ccc(cc1)c2ccccc2,Training,1,1,80,0.4834982138665525,40.540000000000006,62.20750000000003,2.295921475776914,465.0510842985346,213.23600000000002,2.7056000000000004
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+4758,4766,78-85-3,O=CC(=C)C,Training,1,1,28,0.32859625570390477,17.07,20.877999999999993,3.204805417886435,54.668290500398435,70.091,0.7614
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+4799,4807,8003-22-3,O=C1c4ccccc4(C(=O)C1c2nc3ccccc3(cc2)),Training,1,0,100,0.6383289551201906,47.03,79.58700000000002,1.8649637073068857,863.3687317678385,273.291,3.3976000000000015
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+4801,4809,80-05-7,Oc1ccc(cc1)C(c2ccc(O)cc2)(C)C,Training,0,0,88,0.8263814942234684,40.46,68.34160000000004,2.412580781491558,447.94995845416787,228.291,3.423700000000002
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+4805,4813,80115-73-7,O=C(N(O)c1ccc(cc1)c2ccccc2)CC,Training,1,1,92,0.6597647156497598,40.540000000000006,71.44150000000003,2.230935489231471,519.9496820510872,241.29,3.485800000000002
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+4815,4823,80440-44-4,O=C2c5cccc4cccc(c3ccc1ccccc1c23)c45,Training,0,0,102,0.38060960390257786,17.07,90.32250000000005,2.044254806836147,1084.2088411303923,280.3260000000001,5.204400000000003
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+4818,4826,80556-89-4,O=NN(CC(=O)O)CCO,Training,1,1,58,0.38705749519358257,90.2,32.08959999999999,3.592884119114175,126.42599881712918,148.118,-0.9533
+4819,4827,80-56-8,C1=C(C)C2CC(C1)C2(C)(C),Training,0,0,56,0.44898299940434644,0.0,43.75200000000002,2.296626579720339,186.21499122004107,136.238,2.9987000000000013
+4820,4828,8062-14-4,O=S(=O)(N)c3ccc(N=Nc2cc(N=Nc1ccc(cc1)S(=O)(=O)N)c(N)cc2(N))cc3,Training,1,1,166,0.3099538638971925,221.8,119.2492,1.8395401433762266,1310.3014800209107,474.52800000000025,2.9766000000000004
+4821,4829,80-62-6,O=C(OC)C(=C)C,Training,0,0,40,0.35850815039012257,26.3,26.829999999999988,3.577919926272439,94.25327665163483,100.11699999999999,0.7355
+4822,4830,80-63-7,O=C(OC)C(=C)Cl,Training,1,1,40,0.3799164772238561,26.3,27.00899999999999,3.577919926272439,97.86291712607165,120.535,0.9119
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+4824,4832,80-71-7,O=C1C(O)=C(C)CC1,Training,0,1,44,0.5105500844865745,37.3,29.56979999999999,2.8648876586152845,155.9114705065293,112.128,1.1813
+4825,4833,80-78-4,OC6CC5=CCC4C(CCC3(C)(C4(CC2N1CC(C)CCC1C(C)C23)))C5(C)CC6,Training,0,0,162,0.5335471062647691,23.47,118.42680000000009,1.3269326590844708,715.3263577733084,397.6470000000002,5.6550000000000065
+4826,4834,80-82-0,O=[N+]([O-])c1ccccc1S(=O)(=O)O,Training,0,0,70,0.4359959731213461,97.51,42.911000000000016,3.4619307556830026,438.0927627293939,203.17499999999995,0.8414999999999999
+4827,4835,80830-42-8,O=C(O)C2N(C(=O)CCS)C(c1ccccc1(O))SC2,Training,0,0,108,0.7381312554171041,77.84,80.04560000000004,2.343480465175831,522.8475494109863,313.4000000000001,1.7392999999999998
+4828,4836,80909-78-0,O1CC1(c2ccc(cc2)Br)C,Training,0,1,58,0.6530748296630113,12.53,47.446000000000026,2.3317889985327622,261.39615155843137,213.07399999999993,2.6945000000000006
+4829,4837,809-73-4,O=C2C(=CC(=CC=C1C=C(C(=O)C(=C1)C(C)(C)C)C(C)(C)C)C=C2C(C)(C)C)C(C)(C)C,Training,0,0,174,0.4202104164625441,34.14,136.332,2.6748664920961933,846.6635091412685,434.6640000000002,7.8946000000000085
+4830,4838,80984-66-3,c1cc4c3c(c1)C6NC6(c2cccc(c23)C5NC45),Training,1,1,86,0.6858425622371918,43.88,69.11340000000003,1.8604577366717403,617.8719739408582,232.286,2.7516000000000007
+4831,4839,80984-67-4,c1ccc3c(c1)c2cc6c(cc2C4NC34)c5ccccc5C7NC67,Training,1,1,114,0.6038237842728201,43.88,94.54940000000003,1.552867106000555,966.3356068503196,308.384,4.418600000000003
+4832,4840,81-07-2,O=C1NS(=O)(=O)c2ccccc12,Training,0,0,62,0.62091720771658,63.24,41.094000000000015,2.8283976971285636,449.4742221869951,183.18800000000002,0.11869999999999997
+4833,4841,81-11-8,O=S(=O)(O)c2cc(N)ccc2(C=Cc1ccc(N)cc1S(=O)(=O)O),Training,0,0,128,0.3576146794946529,160.77999999999997,90.26600000000003,2.586773510100684,943.725349530695,370.4080000000001,1.5148000000000001
+4834,4842,81-13-0,O=C(NCCCO)C(O)C(C)(C)CO,Training,0,1,84,0.412780402657381,89.79,51.58610000000004,3.988878924622364,181.65076769132014,205.254,-1.1356000000000002
+4835,4843,81-14-1,O=C(c1c(c(c(c(c1C)[N+](=O)[O-])C(C)(C)C)[N+](=O)[O-])C)C,Training,0,0,114,0.4807898082802458,103.35,77.92930000000003,4.1661356749355996,615.3038176152639,294.307,3.6199400000000033
+4836,4844,81-15-2,O=[N+]([O-])c1c(c(c(c(c1C)[N+](=O)[O-])C(C)(C)C)[N+](=O)[O-])C,Training,0,0,114,0.6208885983122051,129.42000000000002,74.57920000000001,4.1661356749356,618.9322144833629,297.26700000000005,3.325540000000003
+4837,4845,81-16-3,O=S(=O)(O)c2c(N)ccc1ccccc12,Training,1,0,78,0.5688803218109532,80.39,58.17500000000002,2.9910434101807177,619.6001475530924,223.25300000000001,1.6687
+4838,4846,811-97-2,FCC(F)(F)F,Training,0,0,38,0.40653794072819166,0.0,12.030000000000003,3.168489872670569,35.30296890880646,102.03000000000002,1.5182000000000002
+4839,4847,812-00-0,O=P(O)(O)OC,Training,0,0,38,0.45777198227928484,66.76,19.053099999999993,3.4788087181133602,71.61727061434749,112.02099999999999,-0.27449999999999997
+4840,4848,81-20-9,O=[N+]([O-])c1c(cccc1C)C,Training,0,1,58,0.4558415924169074,43.14,42.57040000000002,3.318913173486669,273.89357423078934,151.16499999999996,2.21164
+4841,4849,81316-80-5,O=[N+]([O-])c3ccc2c4cc5ccccc5(cc4(c1cccc3(c12))),Training,1,1,108,0.3005930888318143,43.14,92.53840000000002,1.9645868965349091,1096.3672174770745,297.31300000000005,5.548600000000002
+4842,4850,81340-58-1,O=[N+]([O-])c5ccc2c1ccccc1c4cccc3ccc5(c2c34),Training,1,1,108,0.17366715134946126,43.14,94.30640000000004,2.233584194975542,1240.4324987418463,297.31300000000005,5.645400000000003
+4843,4851,813-78-5,O=P(O)(OC)OC,Training,0,1,44,0.5431172517623009,55.760000000000005,23.843299999999992,3.605378627989909,81.69058447171099,126.04799999999999,0.37959999999999994
+4844,4852,81407-76-3,O=C1C=C(C=CC)C(=O)C3(O)(OC(C)(C)C2CC123),Training,1,1,96,0.7555980319208266,63.60000000000001,63.564800000000034,2.152880862586641,527.9120811863864,248.27799999999996,1.1443999999999999
+4845,4853,81424-67-1,O=C(ON(C(=O)NC)C(=O)C)NC,Training,1,1,74,0.5000707895810634,87.74000000000001,42.51640000000002,4.351205679620967,227.9192538639593,189.171,-0.5547000000000002
+4846,4854,814-78-8,O=C(C(=C)C)C,Training,0,1,34,0.43543001604271575,17.07,25.49499999999999,3.567703455043203,69.93923454719788,84.118,1.1515
+4847,4855,81-48-1,O=C1c4ccccc4(C(=O)c2c(ccc(O)c12)Nc3ccc(cc3)C),Training,0,1,122,0.5404324754978631,66.4,95.87550000000002,1.8805845311359684,1019.8111975374047,329.355,4.219620000000002
+4848,4856,81-49-2,O=C1c3ccccc3(C(=O)c2c1c(N)c(cc2Br)Br),Training,1,1,94,0.6062275493326759,60.16,79.5614,2.4251758065888405,753.3514509888895,381.0229999999999,3.5692000000000013
+4849,4857,81542-82-7,Oc1ccc(OCC(O)CNC(C)(C)C)c(c1)C2CCCC2,Training,0,0,124,0.7552003432461755,61.72,88.57330000000006,1.9414538637984127,475.71087949013526,307.43400000000014,3.1776000000000018
+4850,4858,81-54-9,O=C1c3ccccc3(C(=O)c2c(O)c(O)cc(O)c12),Training,1,1,94,0.419013529976834,94.83000000000001,64.74340000000002,2.4251758065888405,745.7418105144527,256.21299999999997,1.5788000000000004
+4851,4859,81-55-0,O=C1c3c(O)ccc(c3(C(=O)c2c(ccc(O)c12)[N+](=O)[O-]))[N+](=O)[O-],Training,1,1,120,0.529547512415044,160.88000000000002,76.3874,2.4784400340055566,903.7251146892182,330.208,1.6896000000000004
+4852,4860,81593-11-5,O=S(=O)(N2C3c4ccccc4(c1ccccc1C23))C,Training,1,1,96,0.7478204185108677,37.15,74.04280000000003,2.0104581198020144,730.737513122321,271.341,2.7246000000000006
+4853,4861,81593-13-7,O=P(OCC)(OCC)N2C3c4ccccc4(c1ccccc1C23),Training,1,1,120,0.5747660359818129,38.54,90.05750000000005,1.8391451816782003,729.841095082003,329.33600000000007,4.946100000000004
+4854,4862,81593-15-9,c1ccc3c(c1)c2ccccc2C4N(C34)Cl,Training,1,1,78,0.4870701584107767,3.01,65.05200000000002,2.0677811738324574,526.952954145295,227.694,3.918800000000002
+4855,4863,81-61-8,O=C1c3ccc(O)c(O)c3(C(=O)c2c(O)ccc(O)c12),Training,1,1,100,0.3618010266707362,115.06,66.40820000000001,2.430752510835327,786.7365172769805,272.212,1.2843999999999998
+4856,4864,816-57-9,O=NN(C(=O)N)CCC,Training,1,1,52,0.4458130396635203,75.76,32.3754,3.67532946882013,114.38037532843023,131.13500000000002,0.4585000000000002
+4857,4865,81760-45-4,O=C(OCC3(O)(CC24(CCC1c5ccoc5(C=CC1(C)C4(CCC3(C2))))))CCCCCCCCCCCCCCC,Training,0,0,224,0.1637338630424066,59.67,161.92579999999964,0.9951423228786687,994.6758501362007,552.8400000000006,9.752099999999997
+4858,4866,81789-85-7,OC(COc2cccc1c2(C=CC1))CNC(C)C,Training,0,0,98,0.8075449057794266,41.49,73.82050000000004,1.869688120837454,426.50182000908245,247.33799999999997,1.9936
+4859,4867,817-99-2,[N-]=[N+]=CC(=O)NCC(=O)N,Training,1,1,54,0.2668652307359673,108.58999999999999,31.887500000000003,3.595897016064833,193.4342721689147,142.11799999999997,-2.1114999999999995
+4860,4868,81840-15-5,O=C2Nc1ccc(cc1CC2)N4CCN(C(=O)c3ccc(OC)c(OC)c3)CC4,Training,0,0,152,0.8615923399478468,71.11000000000001,111.05520000000004,1.4169707207547786,935.649774373323,395.4590000000002,2.5509000000000004
+4861,4869,81851-68-5,OC4c2ccc1c5ccccc5(cc(c1c2C3OC3C4(O))C),Training,1,1,110,0.4941691551560917,52.989999999999995,84.77160000000003,1.9389946711315902,930.7555430877238,292.334,3.1492200000000015
+4862,4870,818-61-1,O=C(OCCO)C=C,Training,0,0,46,0.4067615269019466,46.53,28.24179999999999,3.1114301208164354,87.67457204070747,116.11599999999999,-0.2921
+4863,4871,81-88-9,O=C(O)c1ccccc1c3c4ccc(cc4([o+]c2cc(ccc23)N(CC)CC))N(CC)CC,Training,1,0,170,0.2364461045644184,55.08,137.64429999999996,2.0863089706821594,1237.5317406230079,443.5670000000003,6.924700000000006
+4864,4872,81924-79-0,O=C(Nc2cc(c(OC)cc2(N=Nc1ccc(cc1)[N+](=O)[O-]))N(CC)CC)C,Training,1,1,148,0.39773690578908866,109.42999999999999,108.13110000000005,2.4521569193074146,876.6378779735248,385.4240000000002,4.823400000000005
+4865,4873,81943-37-5,O=NN(c1ccccc1)COC(=O)C,Training,1,1,74,0.3165353285774501,58.970000000000006,51.34900000000003,2.631007124436809,313.0929223461078,194.18999999999994,1.695
+4866,4874,82017-48-9,O=C(O)C1NC(=O)C(C)(C)SSC1,Training,0,0,74,0.6389434056537789,66.4,53.69450000000002,2.720514311668257,241.89215386800367,221.30299999999997,0.7294
+4867,4875,82-05-3,O=C2c1ccccc1c4cccc3cccc2c34,Training,1,0,84,0.44509506734612314,17.07,72.81650000000002,2.280715240101624,794.3191953307492,230.266,4.051200000000002
+4868,4876,820-75-7,[N-]=[N+]=CC(=O)NCC(=O)NN,Training,1,1,60,0.10384883136168442,120.61999999999999,35.023199999999996,3.6200192527392256,206.52795730919604,157.13299999999998,-2.6068999999999996
+4869,4877,82085-94-7,O=C(O)CCc1ccc(cc1)C(=O)C2CCC(CN)CC2,Training,0,0,114,0.7889033534799729,80.39,81.23170000000005,1.920756106348273,487.26161392400803,289.37500000000006,2.651600000000001
+4870,4878,821-95-4,C=CCCCCCCCCC,Training,0,0,66,0.36073349676483174,0.0,52.80700000000004,2.7376715685719475,74.10749561002055,154.297,4.313100000000003
+4871,4879,822-36-6,n1c[nH]cc1C,Training,0,0,32,0.49044689078380066,28.68,23.324699999999993,3.049648321313926,109.10850553448522,82.10600000000001,0.71812
+4872,4880,82-28-0,O=C1c3ccccc3(C(=O)c2c(N)c(ccc12)C),Training,1,1,88,0.6103905941174068,60.16,68.89840000000001,2.376755012054768,701.6349439433923,237.25799999999995,2.352620000000001
+4873,4881,82298-37-1,O=C(O)C6OC(Oc5cccc1c5(cc2ccc3cccc4ccc1c2c34))C(O)C(O)C6(O),Training,0,0,166,0.2496944524444294,116.45000000000002,122.59720000000004,1.5108687653884043,1512.1202045568725,444.43900000000014,3.0082000000000018
+4874,4882,82-33-7,O=C1c3cccc(c3(C(=O)c2c(N)ccc(N)c12))[N+](=O)[O-],Training,1,1,104,0.39551220084207855,129.32,75.2282,2.4188533572995423,842.3530313482822,283.243,1.5346
+4875,4883,823-40-5,Nc1cccc(N)c1C,Training,1,1,48,0.5071584204162337,52.04,40.00380000000001,3.2478347337367026,197.9061775999341,122.171,1.1594200000000001
+4876,4884,823-86-9,ONc1ccc(cc1)Cl,Training,0,1,48,0.5907443468878203,32.26,36.86120000000002,2.8815558776461367,184.7542779872738,143.57299999999998,2.1411
+4877,4885,82389-34-2,O=C(c1ccccc1)C4OC4(c2ccc(cc2)c3ccccc3),Training,0,0,112,0.517131056193553,29.6,90.26450000000003,1.4933367824127857,807.4800107853699,300.35699999999997,4.676400000000004
+4878,4886,82389-37-5,O=C(c1ccc(cc1)c2ccccc2)C4OC4(c3ccccc3),Training,0,0,112,0.517131056193553,29.6,90.26450000000003,1.500137202941693,807.4800107853698,300.357,4.676400000000004
+4879,4887,82389-38-6,O=C(Nc1ccc(cc1)C(=O)C3OC3(c2ccccc2))C,Training,1,1,106,0.6920639753203398,58.7,79.13220000000004,1.6809748684134487,664.1943929864825,281.311,2.9678000000000013
+4880,4888,82-39-3,O=C1c3ccccc3(C(=O)c2c(OC)cccc12),Training,1,1,88,0.6537294443078558,43.370000000000005,66.30100000000003,2.3388778647071136,671.188973620311,238.24199999999996,2.4706
+4881,4889,82414-02-6,O=Nc1cc(ccc1C)[N+](=O)[O-],Training,1,0,62,0.3840324131563308,72.57,43.28840000000001,3.220764099640558,335.42341520043396,166.13599999999997,2.30112
+4882,4890,82-45-1,O=C1c3ccccc3(C(=O)c2c(N)cccc12),Training,1,1,82,0.5931316338727306,60.16,64.16140000000001,2.3740939300606247,659.0218277807028,223.23099999999997,2.0442
+4883,4891,824-69-1,Oc1cc(c(O)cc1Cl)Cl,Training,0,0,54,0.5999129152866219,40.46,39.79160000000001,3.2824629074535228,209.9198833722299,179.00199999999998,2.4045999999999994
+4884,4892,82486-82-6,O=[N+]([O-])OCCN([N+](=O)[O-])CCCC,Training,1,1,82,0.423863505321737,98.75,46.42180000000003,3.7303296496577047,197.9059976845872,207.18599999999998,0.48849999999999993
+4885,4893,824-94-2,O(c1ccc(cc1)CCl)C,Training,0,1,54,0.5980455029351426,9.23,42.55100000000002,2.7972512629697874,169.91749419417292,156.612,2.434
+4886,4894,82-50-8,O=C1c3cccc(c3(C(=O)c2cccc(c12)[N+](=O)[O-]))S(=O)(=O)O,Training,1,1,116,0.4278603215762689,131.64999999999998,76.21800000000002,2.4092637433298982,1007.7810056714928,333.27700000000004,1.6169
+4887,4895,82617-23-0,O=C(OC1OC1)N,Training,1,1,40,0.45211498979427284,64.85,20.4084,2.0834885586684715,88.18080946738405,103.07700000000001,-0.562
+4888,4896,82-62-2,O=[N+]([O-])c1c(O)c(cc(c1Cl)Cl)Cl,Training,0,1,70,0.4668738715865058,63.370000000000005,49.79120000000001,3.5551420285916255,353.627493015742,242.445,3.2605999999999993
+4889,4897,82-68-8,O=[N+]([O-])c1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,1,76,0.3211574810089494,43.14,58.14640000000001,3.682463305848331,390.1682702160744,295.336,4.861799999999999
+4890,4898,82-71-3,O=[N+]([O-])c1cc(c(O)c(c1(O))[N+](=O)[O-])[N+](=O)[O-],Training,0,1,90,0.5813310714041707,169.88,49.73479999999999,3.756255091963571,500.30232072844126,245.10299999999998,0.8224000000000002
+4891,4899,82789-18-2,O=C(O)C4NC(c1ccccc1)c3[nH]c2ccccc2c3C4,Training,0,0,110,0.6802337777304761,65.12,84.84720000000004,1.9120639419375767,838.6742582395441,292.3380000000001,2.856200000000001
+4892,4900,82856-97-1,O=[N+]([O-])c1cc(N)c(cc1(N))C(C)C,Training,1,0,76,0.42754273424040024,95.17999999999999,56.01020000000001,3.3091111102439332,374.56497058438725,195.22199999999998,1.8826
+4893,4901,82-86-0,O=C1C(=O)c3cccc2cccc1c23,Training,1,0,66,0.5852028460377094,34.14,52.60900000000002,2.6175547832361596,533.1414651067442,182.178,2.2188
+4894,4902,830-07-9,O=[N+]([O-])C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,68,0.5220624223652901,99.42,41.39080000000001,2.804194668300063,366.8564454583393,184.107,1.4351999999999998
+4895,4903,83053-57-0,O=C3c2cc(OCC)c1c4ccccc4(ccc1c2CC3),Training,0,0,104,0.6431474410246798,26.3,85.27450000000005,2.189576268307075,877.498427589576,276.3350000000001,4.520600000000003
+4896,4904,83053-58-1,O=C3c2cc(OCCC)c1c4ccccc4(ccc1c2CC3),Training,0,0,110,0.6405293700500452,26.3,89.89150000000005,2.110147109143392,892.9823242681482,290.36200000000014,4.910700000000004
+4897,4905,83053-60-5,O=C3c2cc(OCCCC)c1c4ccccc4(ccc1c2CC3),Training,0,0,116,0.48265678662698147,26.3,94.50850000000005,2.0179687848506633,908.4978739607216,304.3890000000001,5.300800000000004
+4898,4906,830-96-6,O=C(O)CCc2c[nH]c1ccccc12,Training,0,0,72,0.7770851256408983,53.089999999999996,54.25550000000002,2.2907699211707824,459.01040037182304,189.21400000000003,2.1851000000000003
+4899,4907,83-26-1,O=C2c1ccccc1C(=O)C2C(=O)C(C)(C)C,Training,0,0,88,0.6954072783130925,51.21,63.05500000000003,2.473696164244312,485.51401432612516,230.26299999999995,2.2970000000000006
+4900,4908,832-69-9,c1ccc3c(c1)ccc2c3(cccc2C),Training,1,1,72,0.46568308489933063,0.0,66.19100000000003,2.6048627936520328,635.6567221133736,192.26099999999997,4.301420000000003
+4901,4909,83287-02-9,O=C1c4cc(OC)ccc4(c2nccc3cc(OC)c(OC)c1c23),Training,1,1,120,0.5781084511223659,57.650000000000006,90.26750000000004,2.1740361003818105,994.3136138124412,321.3320000000001,3.472000000000002
+4902,4910,83-32-9,c2cc1cccc3c1c(c2)CC3,Training,0,0,58,0.5469607763108971,0.0,51.35600000000002,2.580405551126642,401.9826286215576,154.21199999999993,2.9384000000000015
+4903,4911,833-50-1,n1c(oc2ccccc12)c3ccccc3,Training,0,0,72,0.5936046836183697,26.03,59.44500000000003,2.206101422811211,550.5529818043093,195.221,3.4948000000000023
+4904,4912,83-38-5,O=Cc1c(cccc1Cl)Cl,Training,0,0,52,0.5993581530925117,17.07,41.84950000000001,3.296882075817547,237.5330614243171,175.01399999999998,2.805900000000001
+4905,4913,83407-42-5,n1cccc2c1cc(c(NC)c2(N))C,Training,0,1,72,0.6725463509923384,50.94,60.43910000000002,2.8566877605625978,477.1614928905081,187.24599999999998,2.1671199999999997
+4906,4914,83-41-0,O=[N+]([O-])c1cccc(c1C)C,Training,1,1,58,0.4558415924169074,43.14,42.57040000000002,3.273580821537543,294.1435742307893,151.16499999999996,2.21164
+4907,4915,83435-67-0,O=C(O)CN(C(=O)C(NC(C(=O)OCC)CCc1ccccc1)C)C3Cc2ccccc2C3,Training,0,0,176,0.5090783649876793,95.94000000000001,124.76850000000006,1.697402271098123,937.1644215700314,452.55100000000016,2.6096000000000013
+4908,4916,83-46-5,OC4CC3=CCC1C(CCC2(C)(C(CCC12)C(C)CCC(CC)C(C)C))C3(C)CC4,Training,0,0,172,0.43609564173751103,20.23,128.2168000000001,1.4731460038129802,634.2748374972687,414.7180000000003,8.02480000000001
+4909,4917,83473-93-2,O=C(O)C2N(C(=O)CCSC)C(c1ccccc1(O))SC2,Training,0,0,114,0.8629051800882795,77.84,84.57460000000005,2.2924976778930772,537.4602218965407,327.4270000000001,2.1725000000000003
+4910,4918,83504-80-7,O=Nc1ccc(cc1)Sc2ccccc2,Training,1,1,74,0.7166330348962393,29.43,62.46200000000003,2.146108592777894,438.9391154828053,215.277,4.235700000000002
+4911,4919,835-64-3,Oc1ccccc1c2nc3ccccc3(o2),Training,0,0,78,0.6718631564136741,46.260000000000005,61.10980000000003,2.2327237062441556,609.9825666252442,211.22,3.200400000000001
+4912,4920,835-71-2,n1c(oc2ccccc12)c3ccc(cc3)C,Training,0,0,78,0.6088199043422198,26.03,64.18200000000003,2.150228179083263,589.535314052272,209.248,3.8032200000000023
+4913,4921,83621-06-1,n1ccn(c1)C(=C(OCCOc2ccc(cc2)Cl)c3ccc(cc3Cl)Cl)C,Training,0,0,140,0.33106277556353675,36.28,110.37200000000001,1.7615059691719601,922.9096992869861,423.72700000000015,6.284600000000004
+4914,4922,836-30-6,O=[N+]([O-])c1ccc(cc1)Nc2ccccc2,Training,0,1,80,0.6293026950858532,55.17,62.82110000000003,2.143385024320089,480.13176398410815,214.224,3.338400000000001
+4915,4923,836-37-3,N#CC(=Cc1oc(cc1)[N+](=O)[O-])C(=O)OC,Training,1,1,82,0.25036134751801997,106.36999999999999,50.96840000000001,3.0120111015257467,494.24277735792185,222.15599999999995,1.26778
+4916,4924,83-67-0,O=C1NC(=O)N(c2ncn(c12)C)C,Training,0,0,68,0.5624722357827983,72.68,46.57570000000001,3.1784609855062733,574.1705593822572,180.16699999999997,-1.0397
+4917,4925,83-75-0,O=C(OCC)OC(c2ccnc1ccc(OC)cc12)C3N4CCC(C3)C(C=C)C4,Training,0,0,154,0.5342571823101413,60.89000000000001,110.91500000000009,1.7468133640687722,899.5768740631887,396.48700000000025,4.354000000000004
+4918,4926,83-79-4,O=C3c5ccc1OC(C(=C)C)Cc1c5(OC4COc2cc(OC)c(OC)cc2C34),Training,0,0,150,0.7399961156347875,63.22000000000001,105.90450000000004,1.581624927135841,1040.1489593987324,394.4230000000001,3.703300000000003
+4919,4927,838-88-0,Nc1ccc(cc1C)Cc2ccc(N)c(c2)C,Training,1,1,88,0.7731606081006569,52.04,73.98880000000001,2.2491822930475696,495.1132378198908,226.323,3.0586400000000014
+4920,4928,838-95-9,c1ccc(cc1)C=Cc2ccc(cc2)N(C)C,Training,1,1,86,0.7127170547742487,3.24,76.13900000000004,2.1154755667127603,480.6934451947291,223.31899999999996,3.9230000000000027
+4921,4929,83905-01-5,O=C3OC(CC)C(O)(C)C(O)C(N(C)CC(C)CC(O)(C)C(OC1OC(C)CC(N(C)C)C1(O))C(C)C(OC2OC(C)C(O)C(OC)(C)C2)C3C)C,Training,0,0,306,0.23847544119122638,180.07999999999996,194.17899999999932,2.1748976743674855,1143.2996076325867,748.9960000000002,1.9007000000000092
+4922,4930,839-90-7,O=C1N(C(=O)N(C(=O)N1CCO)CCO)CCO,Training,0,0,102,0.4809270956967134,126.69000000000001,60.47940000000003,3.591130573602719,457.8646125297857,261.2339999999999,-3.851399999999997
+4923,4931,84-11-7,O=C2C(=O)c1ccccc1c3ccccc23,Training,0,0,76,0.6236328777971427,34.14,60.53900000000003,2.414775645683774,556.1373359552138,208.21599999999998,2.7326000000000006
+4924,4932,841-18-9,O=C(Nc2ccc(C=Cc1ccccc1)cc2)C,Training,1,1,90,0.8078197267494154,29.1,76.11570000000003,2.064095347708759,541.0694605822265,237.302,3.815400000000002
+4925,4933,84-15-1,c1ccc(cc1)c3ccccc3(c2ccccc2),Training,0,0,86,0.5794896680157822,0.0,77.31400000000004,2.177338239934605,565.9660655475085,230.30999999999997,5.0206000000000035
+4926,4934,84-17-3,Oc1ccc(cc1)C(=CC)C(=CC)c2ccc(O)cc2,Training,0,0,102,0.7966718656376947,40.46,83.51560000000003,2.4386154465710357,572.6233694045893,266.34,4.604600000000004
+4927,4935,84174-20-9,O=NN(C)Cc1ccc(OC)cc1,Training,0,1,70,0.5238223865463411,41.900000000000006,50.25600000000003,2.6341061805197863,271.44812008925527,180.207,1.8084
+4928,4936,84174-21-0,O=NN(C)Cc1ccc(F)cc1,Training,1,1,64,0.5099930797095618,32.67,43.66200000000003,2.6400206596775657,260.26529978753473,168.171,1.9389
+4929,4937,84174-22-1,O=NN(C)Cc1ccc(cc1)Cl,Training,1,1,64,0.5341205329856572,32.67,48.71400000000003,2.6400206596775657,260.26529978753473,184.626,2.4532000000000007
+4930,4938,84174-24-3,O=NN(C)Cc1ccc(cc1)[N+](=O)[O-],Training,1,1,74,0.4159775038569022,75.81,50.35840000000002,2.730085891322884,336.18967030834256,195.178,1.708
+4931,4939,842-07-9,Oc2ccc3ccccc3(c2(N=Nc1ccccc1)),Training,1,0,92,0.639788018341975,44.95,76.23080000000003,2.0981399181131093,736.079927306224,248.285,4.9608000000000025
+4932,4940,84-24-2,O=C(O)c2c(O)cc1OC(=O)c3c(Oc1c2CCCCC)cc(O)cc3CC(=O)CCCCC,Training,0,0,182,0.22146037917152125,130.36,124.28740000000006,2.0724796189596675,1102.7099546898423,470.51800000000037,5.545500000000005
+4933,4941,84305-41-9,O=C(O)C3=C(CSc1nnnn1C)CSC2N3(C(=O)C2(OC)(NC(=O)CSCC(N)C(=O)O)),Training,0,0,180,0.14413634042305323,202.86,118.09470000000005,1.7012650700915477,1002.8439728730551,519.5870000000003,-1.8399999999999954
+4934,4942,843-23-2,O=C(N(O)c2ccc(C=Cc1ccccc1)cc2)C,Training,1,1,96,0.5155420926684045,40.540000000000006,76.75850000000004,2.110679358473779,573.4577453574351,253.30100000000002,3.5991000000000026
+4935,4943,843-55-0,Oc1ccc(cc1)C3(c2ccc(O)cc2)(CCCCC3),Training,0,0,104,0.8498106993450174,40.46,80.07860000000004,2.0799122197278628,515.8721469716291,268.356,4.3480000000000025
+4936,4944,844-26-8,O=S(c1cc(cc(c1(O))Cl)Cl)c2cc(cc(c2(O))Cl)Cl,Training,1,0,106,0.7904469532848388,57.53,80.928,2.6356020512911487,658.8340022341611,372.05600000000004,4.878100000000002
+4937,4945,84434-42-4,N(=Nc1ccc(N)c(c1(N))C)c2ccccc2,Training,1,1,86,0.6061542858315557,76.75999999999999,70.62180000000001,2.3129561732073043,546.8459624622882,226.28300000000002,3.5748200000000017
+4938,4946,84434-45-7,N(=Nc1ccccc1C)c2ccc(N)c(c2(N))C,Training,1,1,92,0.6168352408731984,76.75999999999999,75.35880000000002,2.3565227075107873,602.738141212672,240.30999999999997,3.8832400000000016
+4939,4947,84498-34-0,Oc3cc1ccccc1c4ccc2ccccc2c34,Training,0,1,90,0.4382001128928585,20.23,80.62480000000004,2.3547447512611064,922.3919838784873,244.29299999999998,4.851800000000003
+4940,4948,84506-41-2,[N-]=[N+]=NCC(C(=O)OC)C,Training,1,1,56,0.25657383105654047,75.06000000000002,35.193,3.715744852276975,162.27599848312957,143.14599999999996,1.1058
+4941,4949,84-54-8,O=C1c3ccccc3(C(=O)c2cc(ccc12)C),Training,0,1,82,0.5857579681776477,34.14,64.48600000000002,2.3304909398632216,653.7214377553814,222.24299999999997,2.7704200000000005
+4942,4950,84-56-0,n2cccc3ccc1cc4ccccc4(cc1c23),Training,1,1,84,0.31841665410737346,12.89,76.75500000000004,2.268265813130303,871.8244038631086,229.28199999999998,4.541200000000002
+4943,4951,84-60-6,O=C1c3ccc(O)cc3(C(=O)c2ccc(O)cc12),Training,0,1,88,0.628686275140444,74.6,63.07860000000002,2.314758854452267,639.4353339687133,240.21399999999997,1.8732
+4944,4952,84-61-7,O=C(OC1CCCCC1)c3ccccc3(C(=O)OC2CCCCC2),Training,0,0,130,0.753113862533664,52.60000000000001,91.01900000000006,1.6657948843748238,517.7565100703199,330.4240000000002,4.665600000000004
+4945,4953,84-64-0,O=C(OCCCC)c2ccccc2(C(=O)OC1CCCCC1),Training,0,0,120,0.5854121200271813,52.60000000000001,83.92100000000005,2.025997892843666,503.56354943313227,304.38600000000014,4.133000000000004
+4946,4954,84-65-1,O=C1c3ccccc3(C(=O)c2ccccc12),Training,1,1,76,0.5683365592539452,34.14,59.749000000000024,2.348767905791676,506.13733595521376,208.21599999999998,2.4620000000000006
+4947,4955,84-66-2,O=C(OCC)c1ccccc1(C(=O)OCC),Training,0,0,86,0.7313625096648502,52.60000000000001,58.35500000000003,2.9975148158911993,347.3600796599688,222.23999999999995,2.04
+4948,4956,84-68-4,Nc2ccc(c1ccc(N)cc1Cl)c(c2)Cl,Training,1,1,82,0.7586739279140474,52.04,70.7228,2.5856376418759384,489.037124074059,253.13199999999998,3.8248000000000006
+4949,4957,84-69-5,O=C(OCC(C)C)c1ccccc1(C(=O)OCC(C)C),Training,0,0,110,0.7490451628929792,52.60000000000001,76.68300000000005,2.815925753105677,420.29960603265533,278.348,3.3122000000000016
+4950,4958,84736-60-7,O=CN(O)c1ccc(cc1)[N+](=O)[O-],Training,1,1,68,0.326127691128572,83.68,43.42590000000001,2.9286313201136123,321.76935653194136,182.135,0.9468000000000001
+4951,4959,84-74-2,O=C(OCCCC)c1ccccc1(C(=O)OCCCC),Training,0,0,110,0.5382823793200492,52.60000000000001,76.82300000000005,2.7123913375014235,398.85794216890986,278.348,3.600400000000003
+4952,4960,84-75-3,O=C(OCCCCCC)c1ccccc1(C(=O)OCCCCCC),Training,0,0,134,0.3911537223261821,52.60000000000001,95.29100000000007,2.5016837685957376,451.1671451721298,334.45600000000024,5.160800000000005
+4953,4961,84761-86-4,o2c1ccccc1c3c2cccc3Cl,Training,0,1,68,0.531560836348283,13.14,58.73000000000002,2.653366534614703,609.8208026305191,202.64000000000001,4.2394000000000025
+4954,4962,84-79-7,O=C1C(O)=C(C(=O)c2ccccc12)CC=C(C)C,Training,0,1,92,0.8098555814916355,54.37,68.80580000000002,2.4977328243712242,587.5112067701165,242.27399999999997,3.2340000000000018
+4955,4963,84807-61-4,O=CC3=CCC1C(C)(CCC2C(C)(C)CCCC12(C))C3(C=O),Training,0,0,122,0.6996806927821261,34.14,88.37800000000006,2.0561138002926462,517.8002857699712,302.45799999999997,4.579400000000004
+4956,4964,84-88-8,O=S(=O)(O)c2ccc(O)c1ncccc12,Training,1,0,78,0.7115197155561584,87.49000000000001,53.22240000000002,2.961958871524338,621.0449909911487,225.225,1.1871
+4957,4965,84987-77-9,O(CC(=CCl)Cl)CCCl,Training,1,1,54,0.4878330107241008,9.23,41.32800000000002,3.0721410452504934,92.20389705368828,189.46899999999997,2.5608000000000004
+4958,4966,85-02-9,n1cccc3c1ccc2ccccc23,Training,1,1,66,0.48189757611829237,12.89,59.249000000000024,2.610318687415942,544.2063511621126,179.22199999999998,3.3880000000000017
+4959,4967,85048-96-0,OCC7OC(O)C(O)C(Op3(np(OC1C(O)C(O)OC(CO)C1(O))(OC2C(O)C(O)OC(CO)C2(O))np(n3)(OC4C(O)C(O)OC(CO)C4(O))OC5C(O)C(O)OC(CO)C5(O))OC6C(O)C(O)OC(CO)C6(O))C7(O),Training,0,0,456,0.05667574984690443,633.3600000000004,237.1571999999997,1.6716667390674913,1778.6914732616408,1209.8310000000013,-13.262400000000017
+4960,4968,85068-73-1,O=[N+]([O-])OCCN([N+](=O)[O-])CC,Training,1,1,70,0.409933157839789,98.75,37.1878,3.5860501081205802,172.07626754290982,179.132,-0.29169999999999985
+4961,4969,852-20-0,O=[N+]([O-])c1cc(cc(c1(O))Sc2cc(cc(c2(O))[N+](=O)[O-])Cl)Cl,Training,0,0,120,0.598126137606915,126.74000000000001,83.66539999999999,2.561540670531213,762.1835890324272,377.16100000000006,4.372200000000002
+4962,4970,85-22-3,c1(c(c(c(c(c1Br)Br)Br)Br)Br)CC,Training,0,0,72,0.32479726755718646,0.0,74.32000000000001,3.5637576760479117,315.8730022566066,500.648,6.061500000000001
+4963,4971,85-33-6,O=CC2=CC=C1C2(=CC(=CC=C1C)C(=C)C),Training,1,1,80,0.6858836229422394,17.07,67.89650000000002,2.7805150415977042,537.5359766083808,210.27599999999995,3.945420000000002
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+4968,4976,85-60-9,Oc1cc(c(cc1C(C)(C)C)C(c2cc(c(O)cc2C)C(C)(C)C)CCC)C,Training,0,0,154,0.5847521499983155,40.46,119.83860000000007,2.7452745469500632,778.7023668799607,382.58800000000025,7.241640000000007
+4969,4977,85-68-7,O=C(OCc1ccccc1)c2ccccc2(C(=O)OCCCC),Training,0,0,120,0.5725760438710946,52.60000000000001,87.19400000000005,2.0339510201933932,649.4290056264637,312.3650000000001,4.000500000000002
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+4972,4980,85-83-6,Oc3ccc4ccccc4(c3(N=Nc2ccc(N=Nc1ccccc1C)cc2C)),Training,1,1,142,0.3579882549863993,69.67,116.3228,1.6113552576802548,1244.8199327647787,380.45100000000014,7.993040000000007
+4973,4981,85-84-7,N(=Nc1c(N)ccc2ccccc12)c3ccccc3,Training,0,1,92,0.5110313318713332,50.739999999999995,78.97840000000004,2.098139918113109,733.3250398040603,247.30100000000002,4.837400000000002
+4974,4982,85-86-9,Oc3ccc4ccccc4(c3(N=Nc2ccc(N=Nc1ccccc1)cc2)),Training,1,1,130,0.38243920550506705,69.67,106.84879999999998,1.5543223550054939,1120.0913243602474,352.39700000000005,7.376200000000005
+4975,4983,85-91-6,O=C(OC)c1ccccc1(NC),Training,0,0,64,0.6749581754269858,38.33,47.328200000000024,3.0445058359443866,283.61195376207496,165.19199999999998,1.5149
+4976,4984,85977-49-7,O=NN(C(=O)NCCS(=O)(=O)N(C)C)CCCl,Training,1,1,100,0.3981922747983305,99.14999999999999,64.09350000000002,4.129959543213716,358.8851950330002,286.741,-0.1903999999999999
+4977,4985,85-98-3,O=C(N(c1ccccc1)CC)N(c2ccccc2)CC,Training,0,0,104,0.8163956137247435,23.550000000000004,84.32000000000005,2.2755760491533783,489.93116659984844,268.35999999999996,4.159400000000003
+4978,4986,859-97-2,O=C(O)CCC(C)C3CCC2C4C(=O)CC1CC(=O)CCC1(C)C4(CCC23(C)),Training,0,0,156,0.7438094577761155,71.44,106.64780000000007,1.5717787283422344,684.0926332351031,388.54800000000023,4.894300000000005
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+4980,4988,86247-86-1,OC(COc2cccc1c2(OCC(O)C1))CNC(C)C,Training,0,0,112,0.716550866167302,70.95,76.28830000000005,1.9166124730143042,435.8817318808681,281.352,0.7201
+4981,4989,86-26-0,O(c1ccccc1c2ccccc2)C,Training,0,0,70,0.6949649441287624,9.23,58.43000000000003,2.513020981657148,406.59055657608906,184.238,3.3622000000000023
+4982,4990,86412-49-9,O=C(N(O)c1ccc(c(c1)Cl)Cl)C,Training,0,0,70,0.5833849870336031,40.540000000000006,51.40850000000002,3.0339285782867043,340.91595348418105,220.05499999999998,2.735500000000001
+4983,4991,86-42-0,Oc1ccc(cc1CN(CC)CC)Nc3ccnc2cc(ccc23)Cl,Training,0,1,130,0.5980257885078601,48.39,104.76750000000003,1.9078862505736287,877.9443065405388,355.869,5.179200000000003
+4984,4992,86439-49-8,O=[N+]([O-])c1cc3c(cc1(N))[nH]c2ccccc23,Training,1,1,84,0.3805104475471705,84.94999999999999,66.87150000000001,2.473765347462536,745.925182405841,227.22299999999998,2.8115000000000006
+4985,4993,86-50-0,O=C1c2ccccc2(N=NN1CSP(OC)(OC)=S),Training,1,0,102,0.7813603331085346,66.24000000000001,79.69200000000002,2.296294907633669,683.0193670634868,317.332,1.9994999999999998
+4986,4994,86-57-7,O=[N+]([O-])c2cccc1ccccc12,Training,1,1,64,0.49116998683506796,43.14,50.60240000000002,2.8309756583676706,459.93632858848656,173.171,2.748000000000001
+4987,4995,86-59-9,O=C(O)c2cccc1cccnc12,Training,0,0,64,0.7163650797494612,50.19,48.702300000000015,2.8309756583676706,459.93632858848656,173.171,1.9329999999999998
+4988,4996,86607-81-0,O=[N+]([O-])c3cccc2c3(oc1ccccc12),Training,1,1,78,0.4588339118278573,56.28,60.37440000000002,2.535467545905305,699.6227880794761,213.19199999999998,3.494200000000001
+4989,4997,86674-49-9,O=[N+]([O-])c1cc(O)c2ccc3cccc4ccc1c2c34,Training,1,1,96,0.3178220983140643,63.370000000000005,78.46520000000004,2.4067438554328846,975.3896317656959,263.252,4.197800000000001
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+4991,4999,86674-51-3,O=Nc1ccc2ccc3cccc4ccc1c2c34,Training,1,1,84,0.33522539382200983,29.43,75.60100000000004,2.4348318688991455,879.5385637415335,231.254,4.981900000000003
+4992,5000,86711-50-4,O=C(c1ccccc1)C4OC4(c3ccc(Oc2ccccc2)cc3),Training,0,0,118,0.5010589102683636,38.83,91.34450000000002,1.422939487778694,825.9774163627143,316.356,4.801700000000004
+4993,5001,86-73-7,c1ccc3c(c1)c2ccccc2C3,Training,0,1,62,0.48057199184742155,0.0,54.684000000000026,2.320727984740838,411.60041905516795,166.22299999999996,3.2578000000000014
+4994,5002,86803-19-2,c2cc3ccc4cc1cccc(c1c5ccc(c2)c3c45)CCl,Training,1,0,104,0.1888098175126323,0.0,97.20900000000003,2.179379719792447,1138.5980587215813,300.788,6.4760000000000035
+4995,5003,86827-66-9,O=C4C=Cc2c(ccc1c3ccccc3(cc(c12)C))C4(=O),Training,1,1,100,0.4562203384585343,34.14,84.56250000000004,2.2297467925602836,977.6850071803799,272.30300000000005,4.080020000000002
+4996,5004,86853-91-0,O=C1c4cccc3ccc2c5ccccc5(cc1c2c34),Training,1,1,92,0.3708285641589474,17.07,85.10800000000005,2.305234307901189,1154.5540911632888,254.28799999999998,4.535200000000002
+4997,5005,86853-93-2,O=C5c1ccccc1c4c5(ccc3ccc2ccccc2c34),Training,0,0,102,0.35604519721286687,17.07,90.32250000000003,2.073613433020056,1089.4588411303923,280.326,5.204400000000003
+4998,5006,86853-97-6,O=C3c2ccc1ccccc1c2c4c5ccccc5(ccc34),Training,1,0,102,0.38060960390257786,17.07,90.32250000000002,2.050891063717667,1002.2088411303916,280.326,5.204400000000003
+4999,5007,86854-01-5,O=C2c4c5ccccc5(ccc4(c3ccc1ccccc1c23)),Training,0,0,102,0.38060960390257786,17.07,90.32250000000003,1.956954555890792,1002.2088411303916,280.326,5.204400000000003
+5000,5008,86854-03-7,O=C4c1ccccc1c5ccc3ccc2ccccc2c3c45,Training,0,0,102,0.35604519721286687,17.07,90.32250000000005,2.028954841649709,1089.4588411303923,280.3260000000001,5.204400000000003
+5001,5009,86-86-2,O=C(N)Cc2cccc1ccccc12,Training,1,0,70,0.7621016980168943,43.09,56.84640000000002,2.58753091711869,471.210353193355,185.226,1.8676
+5002,5010,86-87-3,O=C(O)Cc2cccc1ccccc12,Training,0,0,70,0.7817752108880086,37.3,55.287800000000026,2.58753091711869,469.210353193355,186.21,2.4669000000000008
+5003,5011,868-77-9,O=C(OCCO)C(=C)C,Training,0,0,52,0.43500205372548345,46.53,32.85879999999999,3.3940489484742136,117.47138037474598,130.14299999999997,0.09800000000000009
+5004,5012,86-88-4,NC(Nc2cccc1ccccc12)=S,Training,1,0,70,0.69767747219757,38.05,64.35610000000001,2.58753091711869,474.1761553969986,202.28199999999998,2.4953000000000003
+5005,5013,868-85-9,O=P(OC)OC,Training,1,0,38,0.48980677730190436,35.53,23.01949999999999,2.98816088213427,46.75488750216347,110.04899999999999,0.6688999999999999
+5006,5014,869-01-2,O=NN(C(=O)N)CCCC,Training,1,1,58,0.4698950252440345,75.76,36.99240000000001,3.604664544468616,126.06147084052891,145.162,0.8486000000000002
+5007,5015,87009-12-9,[N-]=[N+]=NCC(O)CN1C=CC(=O)NC1(=O),Training,1,1,80,0.38474851091306,123.85,51.34250000000001,2.763388259262306,483.88929104920294,211.18099999999998,-0.7922
+5008,5016,87-10-5,O=C(Nc1ccc(cc1)Br)c2cc(cc(c2(O))Br)Br,Training,0,1,98,0.682461219511321,49.33,85.602,2.2738749441989667,626.5306103651783,449.924,4.932000000000001
+5009,5017,87185-24-8,O=[N+]([O-])c2cccc1cc(c(cc12)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,96,0.6173203294788904,129.42000000000002,63.91120000000001,2.8908129004587027,726.5219247803661,263.16499999999996,2.564400000000002
+5010,5018,872-05-9,C=CCCCCCCCC,Training,0,0,60,0.3711511006880485,0.0,48.190000000000026,2.7037899012453233,64.43856189774723,140.27,3.9230000000000027
+5011,5019,872-50-4,O=C1N(C)CCC1,Training,0,0,40,0.4256862105726386,20.310000000000002,26.870999999999988,2.478438739390956,90.08094399727418,99.133,0.2385999999999998
+5012,5020,87-25-2,O=C(OCC)c1ccccc1(N),Training,0,0,64,0.5326180793674542,52.32,46.81090000000002,2.8720351100312476,283.61195376207496,165.19199999999998,1.4455
+5013,5021,87259-00-5,O=[N+]([O-])c3c4ccc1ccccc1c4(cc2C=CC(O)C(O)c23),Training,1,1,114,0.41019521370161605,83.60000000000001,88.10900000000004,2.2119591457612624,993.1402390208038,307.305,3.3223000000000025
+5014,5022,87261-28-7,O=[N+]([O-])c2c4ccccc4(cc1c3C=CC(O)C(O)c3(ccc12)),Training,1,1,114,0.41019521370161605,83.60000000000001,88.10900000000001,2.186269681574211,993.1402390208038,307.30500000000006,3.322300000000002
+5015,5023,87-29-6,O=C(OCC=Cc1ccccc1)c2ccccc2(N),Training,0,0,96,0.6723859128633121,52.32,76.61290000000002,1.8818538387339279,576.3126215016728,253.301,3.139000000000001
+5016,5024,873-69-8,ON=Cc1ncccc1,Training,0,0,46,0.3412981946073336,45.480000000000004,33.61750000000001,2.8479481764153847,195.47265075611662,122.12699999999998,0.8896999999999999
+5017,5025,873-75-6,OCc1ccc(cc1)Br,Training,0,0,48,0.711668437608915,20.23,40.06480000000002,2.8815558776461367,180.61256853719752,187.03599999999997,1.9414
+5018,5026,873-76-7,OCc1ccc(cc1)Cl,Training,0,0,48,0.6345311514904847,20.23,37.374800000000015,2.8815558776461367,180.61256853719752,142.58499999999998,1.8323
+5019,5027,87425-68-1,OC3C=Cc2c4cc1ccccc1c(c4(ccc2C3(O)))Br,Training,1,0,104,0.6025439064718486,40.46,89.15460000000003,2.1485535643340357,898.4934064082672,341.204,4.176600000000003
+5020,5028,87425-69-2,OC3C=Cc2cc1c4ccccc4(ccc1c(c2C3(O))Br),Training,0,1,104,0.6025439064718487,40.46,89.15460000000003,2.158140301545759,898.4934064082672,341.204,4.176600000000002
+5021,5029,87436-71-3,OC4C=Cc2c(cc1c3ccccc3(ccc1c2Br))C4(O),Training,0,1,104,0.6025439064718487,40.46,89.15460000000003,2.166887664907346,898.4934064082672,341.204,4.176600000000002
+5022,5030,874-42-0,O=Cc1ccc(cc1Cl)Cl,Training,0,0,52,0.5993581530925117,17.07,41.84950000000001,3.1881704863349904,257.78306142431705,175.01399999999998,2.805900000000001
+5023,5031,87-44-5,C=C1CCC=C(C)CCC2C1CC2(C)(C),Training,0,0,84,0.5005620426274199,0.0,66.74300000000005,2.119623126378003,293.1601712439863,204.35699999999997,4.7252000000000045
+5024,5032,874-60-2,O=C(c1ccc(cc1)C)Cl,Training,1,1,52,0.5679905040929671,17.07,41.36250000000001,3.003400684579817,237.9394333808838,154.59599999999998,2.3740200000000007
+5025,5033,87480-50-0,OC3c4ccccc4(c2cc1ccccc1c(c2C3(O))Br),Training,0,0,104,0.6382299911419955,40.46,87.00360000000002,2.1503314105097457,856.9612954585153,341.204,4.349700000000003
+5026,5034,874-86-2,N#Cc1ccc(cc1)CCl,Training,0,0,50,0.5653797994002799,23.79,40.71400000000001,2.9302756154154803,244.9552557234275,151.59599999999998,2.2970800000000002
+5027,5035,874-89-5,N#Cc1ccc(cc1)CO,Training,0,0,50,0.6218652440680145,44.019999999999996,37.079800000000006,2.9302756154154803,244.9552557234275,133.14999999999998,1.05058
+5028,5036,87-51-4,O=C(O)Cc2c[nH]c1ccccc12,Training,0,0,66,0.7306784882005591,53.089999999999996,49.638500000000015,2.5139618271787234,444.8764011192855,175.187,1.795
+5029,5037,87-56-9,O=CC(=C(C(=O)O)Cl)Cl,Training,1,1,50,0.4941788070447885,54.370000000000005,32.4318,4.471772749925975,172.6515613063118,168.963,0.9590999999999998
+5030,5038,87-59-2,Nc1cccc(c1C)C,Training,1,1,48,0.5209726320693896,26.02,40.328400000000016,3.2478347337367026,195.55766205433733,121.18299999999999,1.88564
+5031,5039,87-61-6,c1cc(c(c(c1)Cl)Cl)Cl,Training,0,0,48,0.5361021552744022,0.0,41.47200000000001,3.2478347337367026,199.2929995478469,181.44899999999998,3.6468000000000007
+5032,5040,87619-82-7,O=C(O)C(N)CSC(=C(C(=C(Cl)Cl)Cl)Cl)Cl,Training,1,1,92,0.7465118951542504,63.31999999999999,71.3862,4.567247890691682,339.6688869488179,345.462,3.6637000000000013
+5033,5041,87625-62-5,O=C3C(C)CC4(OC1OC(CO)C(O)C(O)C1(O))(C=C(C)C2(CC2)C(O)(C)C34),Training,1,1,158,0.39216910965820334,136.68,95.90900000000003,1.7250264728278797,696.3192557445628,398.4520000000002,-0.7420999999999998
+5034,5042,87-62-7,Nc1c(cccc1C)C,Training,1,1,48,0.5209726320693896,26.02,40.328400000000016,3.2478347337367026,195.5576620543373,121.18299999999998,1.88564
+5035,5043,87633-43-0,O(C)CC4C=C3c1cccc2c1c(cn2C)CC3N(C)C4,Training,1,1,110,0.842401078182942,17.4,86.38400000000004,1.9179187856841997,728.1387080369994,282.38700000000006,2.694400000000001
+5036,5044,87638-04-8,O=C(OCC2N(C(=O)C2(NC(=O)C(=NOCC(=O)O)c1nc(N)sc1))S(=O)(=O)O)N,Training,0,0,164,0.10642466777499184,253.9,96.29990000000001,2.241507356838387,1004.8898085426491,466.41000000000014,-2.8756999999999984
+5037,5045,87-65-0,Oc1c(cccc1Cl)Cl,Training,0,0,48,0.6227397221533862,20.23,38.12680000000001,3.2478347337367026,202.04788705001036,163.003,2.6990000000000007
+5038,5046,87-66-1,Oc1cccc(O)c1(O),Training,1,0,48,0.45046629553451434,60.69,31.436399999999992,3.2478347337367026,199.2929995478469,126.11099999999998,0.8033999999999997
+5039,5047,87679-37-6,O=C(O)C2N(C(=O)C(NC(C(=O)OCC)CCc1ccccc1)C)C3CCCCC3(C2),Training,0,0,170,0.5851031637925749,95.94000000000001,116.41450000000009,1.6957215363829774,768.4929777374001,430.5450000000002,2.7733000000000017
+5040,5048,87812-99-5,O=[N+]([O-])c3cccc2oc1ccccc1c23,Training,1,1,78,0.4588339118278573,56.28,60.37440000000002,2.5746889557811086,699.6227880794761,213.19199999999998,3.494200000000001
+5041,5049,87-82-1,c1(c(c(c(c(c1Br)Br)Br)Br)Br)Br,Training,0,0,66,0.26388633801887934,0.0,72.642,3.6035674514745475,226.30309024251744,551.49,6.2616000000000005
+5042,5050,87-83-2,c1(c(c(c(c(c1Br)Br)Br)Br)Br)C,Training,0,0,66,0.3208671630012448,0.0,69.679,3.6035674514745475,226.06151532233127,486.621,5.807520000000001
+5043,5051,87-84-3,C1(C(C(C(C(C1Br)Br)Br)Br)Br)Cl,Training,0,0,72,0.42136236280904593,0.0,73.21600000000001,2.7602520756252087,107.48810956883254,513.087,4.424900000000002
+5044,5052,87-86-5,Oc1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,0,66,0.5346401235008618,20.23,53.15680000000001,3.6035674514745475,230.20322477240757,266.33799999999997,4.659199999999999
+5045,5053,87-90-1,O=C1N(C(=O)N(C(=O)N1Cl)Cl)Cl,Training,0,1,66,0.58673601434942,66.0,42.975,3.998306133327459,380.52036012943194,232.41,-0.8226
+5046,5054,87919-37-7,O=C(Nc1ccc(c(c1)Cl)Cl)N(C)CCO,Training,0,0,88,0.879564153117855,52.57000000000001,65.19650000000001,2.658540869183674,385.0818207440149,263.12399999999997,2.449400000000001
+5047,5055,879-39-0,O=[N+]([O-])c1cc(c(c(c1Cl)Cl)Cl)Cl,Training,0,1,70,0.32860672164954696,43.14,53.13640000000001,3.4973813605379935,379.3872680200689,260.89099999999996,4.208399999999999
+5048,5056,87976-77-0,O=S(=O)(O)OCc2c4ccccc4(cc1c3ccccc3(ccc12)),Training,1,1,120,0.34008707973421237,63.60000000000001,95.29760000000005,2.09587760337673,1180.0311838028674,338.38400000000007,4.465600000000003
+5049,5057,88020-91-1,OCc2cc3cccc4c1ccccc1c(c2)c34,Training,0,0,86,0.5260129714795542,20.23,74.30080000000002,2.223610435656089,771.6621453127873,232.28199999999998,3.9795000000000025
+5050,5058,88-05-1,Nc1c(cc(cc1C)C)C,Training,1,1,54,0.5420721160262785,26.02,45.06540000000002,3.310532874722407,227.90033336357604,135.20999999999998,2.1940600000000003
+5051,5059,880-93-3,O=[N+]([O-])c2ccc(c1ccccc12)C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.8831748525258547,505.61373284730047,187.19799999999998,3.056420000000001
+5052,5060,881-03-8,O=[N+]([O-])c1c2ccccc2(ccc1C),Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.895160176988298,505.61373284730047,187.19799999999998,3.056420000000002
+5053,5061,88133-11-3,n2cnn3c(nc(c1ccccc1)c(c23)CCOCC)N,Training,0,0,108,0.7240418013725355,78.33,80.82740000000003,2.144919650069128,738.4087209005584,283.335,1.9524999999999997
+5054,5062,88-14-2,O=C(O)c1occc1,Training,0,1,42,0.5885978352786928,50.44,25.667299999999997,2.9283752374267684,175.56366915733074,112.08399999999997,0.9778
+5055,5063,88-16-4,FC(F)(F)c1ccccc1Cl,Training,0,0,60,0.5744156718960564,0.0,36.454000000000015,3.1411091905317954,254.1077532761268,180.55599999999998,3.3588000000000005
+5056,5064,88169-60-2,O=C(OC)C(N)CSCCCl,Training,1,1,66,0.3953969081465025,52.32,48.03640000000002,3.3561943340641003,123.14991061829625,197.68699999999998,0.4587000000000002
+5057,5065,88-17-5,FC(F)(F)c1ccccc1(N),Training,0,0,60,0.5801714244373364,26.02,35.8564,3.1411091905317954,254.1077532761268,161.12599999999998,2.2876
+5058,5066,88193-04-8,c1ccc5c(c1)c(cc4[nH]c3cc(c2ccccc2c3c45)C)C,Training,1,1,110,0.34762877497243516,15.79,100.29070000000004,2.178260739121324,1128.8549984657855,295.38500000000005,6.244340000000004
+5059,5067,88-19-7,O=S(=O)(N)c1ccccc1C,Training,0,0,60,0.6737401345200019,60.16,42.55220000000002,3.3721948109608206,356.4582525456591,171.221,0.64242
+5060,5068,88-21-1,O=S(=O)(O)c1ccccc1(N),Training,1,0,60,0.47878844311221247,80.39,40.66900000000001,3.3721948109608206,357.84507449357193,173.19299999999998,0.5155000000000003
+5061,5069,88-23-3,O=S(=O)(O)c1cc(cc(N)c1(O))Cl,Training,0,0,72,0.37270161731964074,100.62,47.34380000000001,3.5578708456539703,442.1926281995039,223.63699999999997,0.8745
+5062,5070,88321-09-9,O=C(OCC)C1OC1(C(=O)NC(C(=O)NCCC(C)C)CC(C)C),Training,0,0,138,0.4561046117139158,97.03,89.14440000000005,2.5174622579484964,450.26185562029815,342.4360000000001,1.0101000000000002
+5063,5071,88381-44-6,O=NN1CSCC1(C(=O)O),Training,0,0,56,0.5841128483002742,69.97,36.3828,2.576503855517954,162.5816934986334,162.17,0.12730000000000014
+5064,5072,88-44-8,O=S(=O)(O)c1cc(ccc1(N))C,Training,0,0,66,0.5036025797131188,80.39,45.40600000000001,3.434493908900649,397.1125573446092,187.21999999999997,0.8239200000000002
+5065,5073,88488-97-5,Oc1ccc3c(c1)c2ccccc2c4cc5ccccc5(cc34),Training,1,1,108,0.273953292715243,20.23,98.13080000000002,2.153615726702301,1218.4603210655944,294.35300000000007,6.0050000000000034
+5066,5074,88492-34-6,[N-]=[N+]=NCC(O)Cn2cnc1c(ncnc12)N,Training,1,1,88,0.43772827433928296,138.61,59.75520000000001,2.245425062685412,571.9089083137105,234.22299999999998,0.0797
+5067,5075,885-11-0,O=NC=2C(=O)N(c1ccccc1)N(C=2C)C,Training,1,0,82,0.7209789623551803,56.36,61.20200000000002,2.769432405150685,581.2674104433603,217.22799999999998,1.88232
+5068,5076,88-51-7,O=S(=O)(O)c1cc(c(cc1(N))Cl)C,Training,1,0,72,0.5560897475312012,80.39,50.41600000000001,3.501552734477128,441.2960312472641,221.66499999999996,1.4773200000000002
+5069,5077,88-53-9,O=S(=O)(O)c1cc(c(cc1(N))C)Cl,Training,0,0,72,0.5560897475312012,80.39,50.41600000000001,3.501552734477128,441.2960312472641,221.66499999999996,1.4773200000000002
+5070,5078,88552-47-0,O=C1C=C(C(=O)C1(Cl)Cl)Cl,Training,1,0,54,0.43687178543672933,34.14,38.38700000000001,3.1029714206551287,241.2776183156102,199.42000000000002,1.4347999999999999
+5071,5079,885-62-1,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])S(=O)(=O)O,Training,0,0,86,0.47206901221814923,140.64999999999998,49.56540000000001,3.551357292442046,564.2398249898658,248.17199999999997,0.7496999999999998
+5072,5080,885-82-5,O=[N+]([O-])c1cc(ccc1(O))c2ccccc2,Training,0,1,80,0.6182866860352763,63.370000000000005,60.19720000000003,2.5219240579176367,523.0420115762224,215.208,2.9674000000000005
+5073,5081,88598-56-5,O=[N+]([O-])c4ccc1ccc2cc5c(c3ccc4(c1c23))CCCC5,Training,1,1,112,0.2692893128834907,43.14,93.44240000000005,2.0436273832294076,1097.3759786701924,301.34500000000014,5.371000000000003
+5074,5082,88598-57-6,O=[N+]([O-])c3ccc1ccc4c2c(ccc3(c12))cc5c4CCCC5,Training,1,1,112,0.2692893128834907,43.14,93.44240000000005,2.0425721244585398,1097.3759786701924,301.34500000000014,5.371000000000004
+5075,5083,88598-58-7,O=[N+]([O-])c4c1ccc2cccc3ccc(c1c23)c5c4CCCC5,Training,0,1,112,0.2692893128834907,43.14,93.44240000000005,2.1262546800039464,1081.6259786701924,301.34500000000014,5.371000000000003
+5076,5084,88598-59-8,O=[N+]([O-])c2ccc3ccc4cc1c(C=CC(O)C1(O))c5ccc2c3c45,Training,1,1,122,0.3145439536000152,83.60000000000001,96.80100000000002,2.0169993757912423,1211.0899966672882,331.3270000000001,3.913300000000002
+5077,5085,88598-60-1,O=[N+]([O-])c2ccc3ccc4cc1C=CC(O)C(O)c1c5ccc2c3c45,Training,1,1,122,0.3145439536000152,83.60000000000001,96.80100000000002,2.034363147075647,1211.0899966672882,331.3270000000001,3.9133000000000013
+5078,5086,88-72-2,O=[N+]([O-])c1ccccc1C,Training,0,0,52,0.43791186569144913,43.14,37.83340000000001,3.1529414466808685,257.53794892648057,137.13799999999998,1.90322
+5079,5087,88-73-3,O=[N+]([O-])c1ccccc1Cl,Training,1,1,52,0.46360210314198946,43.14,38.106400000000015,3.1529414466808685,261.67965837655686,157.55599999999998,2.2482000000000006
+5080,5088,88741-67-7,O=C1c4ccc(OC)cc4(c2nccc3cc(OC)c(O)c1c23),Training,1,1,114,0.6158077912919036,68.65,85.38030000000003,2.1827615755533905,978.4077960091716,307.30500000000006,3.1690000000000027
+5081,5089,88741-68-8,O=C1c4ccc(OC)cc4(c2nccc3cc(OC)c(OC)c1c23),Training,1,1,120,0.5781084511223659,57.650000000000006,90.26750000000004,2.1818221458067653,994.3136138124412,321.3320000000001,3.472000000000002
+5082,5090,88-74-4,O=[N+]([O-])c1ccccc1(N),Training,0,1,52,0.3595436090070912,69.16,37.50880000000001,3.1529414466808685,259.67965837655686,138.12599999999995,1.1769999999999998
+5083,5091,88746-58-1,c1ccc2c(c1)c4cccc3cc(cc2c34)CBr,Training,1,1,86,0.41338630040837765,0.0,81.00900000000003,2.2236104356560897,771.6621453127873,295.179,5.382100000000002
+5084,5092,88-75-5,O=[N+]([O-])c1ccccc1(O),Training,0,1,52,0.47072821158342537,63.370000000000005,34.76120000000001,3.1529414466808685,258.9247708743934,139.10999999999999,1.3003999999999998
+5085,5093,88847-41-0,Oc4ccc5ccc1c(ccc3c1C2OC2C(O)C3(O))c5(c4),Training,1,1,110,0.4399009222672225,73.22,81.69940000000001,1.8853140344121382,933.162403319354,294.30600000000004,2.546400000000001
+5086,5094,88-85-7,O=[N+]([O-])c1cc(c(O)c(c1)C(C)CC)[N+](=O)[O-],Training,0,0,92,0.6426558619443419,106.51000000000002,60.12160000000002,3.480470536455777,472.0092160085263,240.21499999999997,2.722100000000001
+5087,5095,88-88-0,O=[N+]([O-])c1cc(c(c(c1)[N+](=O)[O-])Cl)[N+](=O)[O-],Training,1,1,84,0.5933590498652713,129.42000000000002,51.4152,3.5727545380551327,466.032394537425,247.54999999999995,2.0646
+5088,5096,88-89-1,O=[N+]([O-])c1cc(c(O)c(c1)[N+](=O)[O-])[N+](=O)[O-],Training,1,1,84,0.60162696436169,149.65000000000003,48.07,3.5727545380551327,461.8906850873487,229.10399999999998,1.1168
+5089,5097,88-95-9,O=C(c1ccccc1(C(=O)Cl))Cl,Training,1,1,62,0.6913536643201288,34.14,46.80900000000001,3.2670761957037717,300.58467465916425,203.02399999999997,2.4446000000000003
+5090,5098,88-96-0,O=C(N)c1ccccc1(C(=O)N),Training,0,0,62,0.6381913843399302,86.18,43.4778,3.2670761957037717,300.58467465916425,164.16399999999996,-0.11560000000000004
+5091,5099,88-99-3,O=C(O)c1ccccc1(C(=O)O),Training,0,0,62,0.6889088084368349,74.6,40.360600000000005,3.2670761957037717,296.58467465916425,166.13199999999998,1.083
+5092,5100,89021-88-5,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CSC(=C(C(=C(Cl)Cl)Cl)Cl)Cl,Training,1,1,164,0.23961145710287507,158.82,113.1964,5.154353354450377,713.856056793663,531.629,2.1295
+5093,5101,892-17-1,O=C3c2cc(c1c4ccccc4(ccc1c2CC3))C,Training,1,1,92,0.5361667709880622,17.07,78.84250000000004,2.2555480999386894,843.0530656994204,246.30899999999994,4.430320000000003
+5094,5102,892-21-7,O=[N+]([O-])c4ccc3c1ccccc1c2cccc4(c23),Training,1,1,90,0.36942414737519014,43.14,75.03240000000002,2.229657655500842,823.2419023615514,247.253,4.395400000000002
+5095,5103,89-25-8,O=C1N(N=C(C)C1)c2ccccc2,Training,0,0,66,0.6385441833835214,32.67,51.654000000000025,2.3262386182068613,356.4473120841761,174.203,1.7992
+5096,5104,89300-15-2,OCC(O)COC=CC=CC=CC=CC=CCC,Training,1,1,100,0.48809506847327944,49.69,75.03560000000003,3.6367914993196857,311.7004035896704,250.33800000000002,2.5047000000000006
+5097,5105,89-40-7,O=C1NC(=O)c2cc(ccc12)[N+](=O)[O-],Training,1,1,70,0.39771571415786955,89.31,44.8931,2.6076190147194995,466.409125541551,192.12999999999997,0.4784
+5098,5106,89415-69-0,O=C(OCCBr)C(=O)OCCBr,Training,1,1,70,0.43911013558330186,52.60000000000001,49.506000000000014,3.547260332536222,141.6270750562502,303.93399999999997,0.8626
+5099,5107,894-52-0,O=C3c2c(c(c1c4ccccc4(ccc1c2CC3))C)C,Training,1,1,98,0.5335340936480253,17.07,83.57950000000004,2.2992497676584014,887.2864421960305,260.33599999999996,4.738740000000003
+5100,5108,89459-25-6,O=C(NCCN(C)C)c2cccc1cc3ccccc3(nc12),Training,1,1,112,0.7522609255785978,45.230000000000004,90.13620000000004,1.9830656319339797,826.7947486922409,293.37000000000006,2.679400000000001
+5101,5109,89459-43-8,O=C(NCCN(C)C)c3cccc2c3(nc1ccccc1c2(N)),Training,1,1,118,0.7253218934992408,71.25,94.54860000000005,2.057227900366642,873.4042720742472,308.3850000000001,2.2616
+5102,5110,89-57-6,O=C(O)c1cc(N)ccc1(O),Training,0,0,58,0.4087158551274257,83.55,39.478500000000004,3.232208870305491,295.73720227422257,153.137,0.6726000000000001
+5103,5111,89-58-7,O=[N+]([O-])c1cc(ccc1C)C,Training,1,1,58,0.4558415924169074,43.14,42.57040000000002,3.2322088703054925,294.1435742307893,151.16499999999996,2.21164
+5104,5112,89-59-8,O=[N+]([O-])c1cc(ccc1C)Cl,Training,0,1,58,0.4815186208815348,43.14,42.84340000000002,3.2322088703054925,298.492089776386,171.58299999999997,2.5566200000000006
+5105,5113,89-61-2,O=[N+]([O-])c1cc(ccc1Cl)Cl,Training,1,1,58,0.5065691418971878,43.14,43.11640000000001,3.2322088703054925,300.6337992264623,192.00099999999998,2.9016
+5106,5114,89-62-3,O=[N+]([O-])c1cc(ccc1(N))C,Training,1,1,58,0.37618304623671805,69.16,42.24580000000001,3.2322088703054925,296.492089776386,152.15299999999996,1.4854199999999997
+5107,5115,89-63-4,O=[N+]([O-])c1cc(ccc1(N))Cl,Training,1,1,58,0.39921483447818135,69.16,42.518800000000006,3.2322088703054925,300.6337992264623,172.57099999999997,1.8303999999999998
+5108,5116,89641-97-4,O=[N+]([O-])c2cccc1cnsc12,Training,1,1,60,0.49897453872292347,56.03,46.274400000000014,2.8189069531314526,437.653925895611,180.18799999999996,2.2045000000000003
+5109,5117,89-69-0,O=[N+]([O-])c1cc(c(cc1Cl)Cl)Cl,Training,1,1,64,0.4173619816787872,43.14,48.12640000000001,3.3258841466405986,339.81023714834686,226.44599999999997,3.5550000000000006
+5110,5118,89-73-6,O=C(NO)c1ccccc1(O),Training,1,1,58,0.4064039562591135,69.56,37.35950000000002,3.0326621558006566,272.1431256273244,153.13699999999997,0.5112000000000003
+5111,5119,89-75-8,O=C(c1ccc(cc1Cl)Cl)Cl,Training,1,1,58,0.6482200511419867,17.07,46.64550000000001,3.196069662125921,295.73720227422257,209.459,3.3724000000000007
+5112,5120,89784-39-4,O=C(O)C(NC(=O)C)CSC(=C(C(=C(Cl)Cl)Cl)Cl)Cl,Training,1,1,108,0.6797921437025076,66.4,81.0155,4.775905555169892,433.5710173568361,387.4989999999999,3.8411000000000017
+5113,5121,89786-04-9,O=C(O)C3N1C(=O)CC1S(=O)(=O)C3(C)(Cn2nncc2),Training,0,0,108,0.6721670015102428,122.46000000000001,64.02160000000002,2.0974986838829364,684.5109353405426,300.296,-1.5231999999999983
+5114,5122,89795-79-9,n2cc1cccc(N)c1s2,Training,1,1,50,0.58218565873613,38.91,44.0324,2.9500903053225893,353.1335934262615,150.206,1.8785
+5115,5123,89811-25-6,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NCC(C)C,Training,1,1,92,0.48244963472092695,85.38,62.24410000000003,2.5177527743896517,434.434759926564,238.24299999999997,1.9731999999999998
+5116,5124,89-82-7,O=C1C(=C(C)C)CCC(C)C1,Training,0,0,62,0.48764805589875265,17.07,46.39600000000003,2.7359157457166745,196.91831683475922,152.23699999999997,2.711900000000001
+5117,5125,89837-94-5,O=NN(COC(=O)C)CC(=O)C,Training,1,1,68,0.2551115617188231,76.04,39.81500000000001,3.7486580781089165,191.98710676103488,174.15599999999998,0.07939999999999969
+5118,5126,89-83-8,Oc1cc(ccc1C(C)C)C,Training,0,0,60,0.652274035834769,20.23,46.93280000000003,3.092719758380193,251.04973178598337,150.22099999999998,2.824020000000001
+5119,5127,89-86-1,O=C(O)c1ccc(O)cc1(O),Training,0,0,58,0.5585391396988667,77.76,36.730900000000005,3.1960696621259195,292.492089776386,154.12099999999998,0.7959999999999998
+5120,5128,89-87-2,O=[N+]([O-])c1ccc(cc1C)C,Training,1,1,58,0.4558415924169074,43.14,42.57040000000002,3.1960696621259204,294.1435742307893,151.16499999999996,2.21164
+5121,5129,89873-24-5,[N-]=[N+]=Nc1ccc(cc1)Nc3c4ccccc4(nc2ccccc23),Training,1,1,114,0.21555043138751617,73.68,97.77970000000002,1.8808799614831913,1025.8137356883315,311.348,6.073400000000003
+5122,5130,89925-00-8,O=C(N)C1(OC1)(C),Training,1,1,40,0.4421328669955202,55.620000000000005,23.551399999999997,2.5466113409770674,106.25742227201614,101.10499999999999,-0.7394000000000001
+5123,5131,89930-59-6,c2cc1c3c(cn1CCC)CC4N(C)CC(=CC4(c3(c2)))C,Training,1,1,110,0.7561872584164455,8.17,88.84900000000005,1.938268198669593,722.4867353075332,280.41499999999996,3.9513000000000025
+5124,5132,89-98-5,O=Cc1ccccc1Cl,Training,0,0,46,0.5466495888095015,17.07,36.83950000000001,3.1479791300397526,219.91106510209755,140.56899999999996,2.1525
+5125,5133,90-00-6,Oc1ccccc1CC,Training,0,0,48,0.6032549150365024,20.23,37.48480000000001,3.0065240073265844,193.51405299160075,122.16699999999999,1.9546000000000001
+5126,5134,90-02-8,O=Cc1ccccc1(O),Training,0,0,46,0.5681374031144324,37.3,33.494299999999996,3.1479791300397526,217.91106510209755,122.12299999999996,1.2047
+5127,5135,9003-39-8,O=C1N(C=C)CCC1,Training,0,0,44,0.4886920431591795,20.310000000000002,31.143999999999988,2.5366819793063398,119.69694286392863,111.144,0.7523
+5128,5136,90-05-1,Oc1ccccc1(OC),Training,0,0,48,0.6127725486570803,29.46,34.6588,3.0065240073265844,195.86256853719752,124.13899999999998,1.4007999999999998
+5129,5137,90-12-0,c1ccc2c(c1)cccc2C,Training,0,0,54,0.5297256591150028,0.0,48.685000000000024,2.9131611636048604,369.2000235425419,142.20099999999996,3.148220000000001
+5130,5138,90-13-1,c1ccc2c(c1)cccc2Cl,Training,1,0,54,0.5564479696593142,0.0,48.95800000000002,2.9131611636048604,374.03449039867854,162.61899999999997,3.4932000000000007
+5131,5139,90147-18-5,O=C(OCCC)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,86,0.33159310604906395,82.58,55.646400000000014,2.5504375256066574,407.09681738976184,225.2,2.1542000000000003
+5132,5140,90147-19-6,O=C(OCCCC)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,92,0.2502697064528114,82.58,60.26340000000002,2.4609371403251274,421.2512104039684,239.22699999999998,2.5443000000000007
+5133,5141,90147-21-0,O=C(OC(C)C)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,86,0.3390717932666686,82.58,55.624400000000016,2.619814138754851,418.5988089588493,225.2,2.1525999999999996
+5134,5142,90147-31-2,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NCCC,Training,1,1,86,0.4684807404455294,85.38,57.69710000000003,2.550437525606658,408.7064578641986,224.21599999999995,1.7271999999999998
+5135,5143,90-19-7,O=C1C(O)=C(Oc2cc(OC)cc(O)c12)c3ccc(O)c(O)c3,Training,1,1,118,0.5352134345240502,120.36000000000001,81.13119999999999,2.355955517104805,972.3051865764031,316.26500000000004,2.2910000000000004
+5136,5144,90223-04-4,Oc2ccc1c(nc(N)n1C)c2,Training,0,1,62,0.605044094071027,64.07,46.79120000000001,2.8681725874822215,433.04074784352383,163.18,0.8611
+5137,5145,90301-75-0,O=C1N=C(N)C(=CN1C2OC(CO)C(O)C2)CCCl,Training,0,0,106,0.6289788094841774,110.60000000000001,68.95300000000003,2.2983776885514007,507.203931994333,289.71899999999994,-0.7525000000000004
+5138,5146,90301-92-1,C(=CCl)c1c(c(c(c(c1Cl)Cl)Cl)Cl)Cl,Training,0,0,76,0.43002129025781544,0.0,66.379,3.5911849881344478,366.3033571541583,310.822,6.1631
+5139,5147,90-30-2,c1ccc(cc1)Nc3cccc2ccccc23,Training,0,0,82,0.6646509169781277,12.03,73.67270000000003,2.063095014249582,623.8561251510307,219.287,4.583400000000002
+5140,5148,90-33-5,O=C2Oc1cc(O)ccc1C(=C2)C,Training,0,0,66,0.6225239946244195,50.44,48.88580000000002,2.9445242725786405,511.0490520651429,176.17099999999996,1.8070199999999998
+5141,5149,90421-79-7,n3c(OCC1OC1)c2ccccc2s3,Training,1,1,72,0.7225493112983317,34.65,54.85500000000003,1.8736356918855221,450.0736536922578,207.25400000000002,2.0739
+5142,5150,90421-84-4,O=C2c1ccccc1SN2CC3OC3,Training,0,1,72,0.6986582654504206,34.53,55.825000000000024,2.1431807466445982,524.146674506841,207.25399999999996,1.4618
+5143,5151,90-44-8,O=C2c1ccccc1Cc3ccccc23,Training,1,0,72,0.537490837646928,17.07,59.122500000000024,2.242810620815754,493.03989348241106,194.233,2.8218000000000005
+5144,5152,90-46-0,OC2c3ccccc3(Oc1ccccc12),Training,1,0,74,0.7048711790158257,29.46,57.01980000000003,2.19639342717164,459.8940690888921,198.221,2.8740000000000014
+5145,5153,90509-02-7,O=C(OC)Nc2nc3cc(OS(=O)(=O)c1ccc(F)cc1)ccc3([nH]2),Training,0,0,130,0.6878919485668906,110.38,86.33520000000003,1.8588423501846485,1031.0063770106108,365.34200000000004,2.6480000000000006
+5146,5154,90594-13-1,n2cc(N)cc3nc1ccccn1c23,Training,1,1,68,0.5751285017935849,56.209999999999994,54.905400000000014,2.5668411342691444,611.6210716902993,184.202,1.4647
+5147,5155,90597-22-1,O=C1N=C(N)C=CN1C2C=C(CO)C(O)C2(O),Training,0,0,92,0.44365802876154425,121.60000000000001,59.12880000000002,2.4123326825941547,510.517628694965,239.231,-1.9793000000000005
+5148,5156,90625-53-9,O=C4C=CC(=Nc2c3ccccc3(nc1ccccc12))C(OC)=C4,Training,0,1,116,0.5276989840171091,51.55,95.58300000000006,2.040598389255929,1007.615271422829,314.3440000000001,4.129700000000002
+5149,5157,90745-27-0,O=[N+]([O-])c2cccc1cccc(c12)C,Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.909384091740965,500.36373284730047,187.19799999999998,3.056420000000002
+5150,5158,90811-87-3,O=C(C=Cc2ccc(Oc1ccccc1)cc2)c3ccccc3,Training,0,0,112,0.46717291705826947,26.3,92.76450000000003,1.6549465329515838,788.264830203947,300.357,5.375000000000004
+5151,5159,90866-04-9,OC2COC(O)(CNc1ccc(cc1)C)C(O)C2(O),Training,0,1,106,0.4926631647915645,102.18,68.59090000000003,1.992313847137857,423.54668236456916,269.297,-0.7915800000000006
+5152,5160,90-94-8,O=C(c1ccc(cc1)N(C)C)c2ccc(cc2)N(C)C,Training,1,1,104,0.7962697212458443,23.550000000000004,84.97050000000004,2.2190020999743023,529.8919984605118,268.36,3.0496000000000016
+5153,5161,91085-62-0,c1ccc(cc1)CSC(=CCl)Cl,Training,1,1,64,0.7336978725201128,0.0,57.526000000000025,2.4385806713485856,256.4908622767174,219.136,4.196300000000002
+5154,5162,91-08-7,O=C=Nc1cccc(N=C=O)c1C,Training,1,1,64,0.5076416678350385,58.86,46.74200000000002,3.328074010294771,377.37292024010196,174.15899999999996,1.92962
+5155,5163,91-13-4,c1ccc(c(c1)CBr)CBr,Training,0,0,54,0.7171470176457416,0.0,51.70400000000002,2.9640000939238016,185.1674941941729,263.96,3.4764000000000017
+5156,5164,91134-58-6,O=C(OCC(C)C)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,92,0.34074661343513074,82.58,60.19340000000002,2.517752774389651,432.8251194521273,239.22699999999998,2.4002000000000008
+5157,5165,91137-27-8,O=[N+]([O-])c2cccc1c2(cccc1C),Training,1,1,70,0.5082749800477625,43.14,55.339400000000026,2.878388742216642,505.61373284730047,187.19799999999998,3.056420000000001
+5158,5166,91137-28-9,O=[N+]([O-])c1ccc2ccc(cc2(c1))C,Training,1,1,70,0.5082749800477625,43.14,55.33940000000002,2.6924724834935283,505.61373284730047,187.19799999999998,3.056420000000001
+5159,5167,91-15-6,N#Cc1ccccc1(C#N),Training,0,0,46,0.5302033439887756,47.58,35.872000000000014,3.2849777388829176,281.76485559073006,128.13399999999996,1.4299600000000001
+5160,5168,91-17-8,C1CCC2CCCCC2(C1),Training,0,0,58,0.4811931969340536,0.0,43.91600000000002,1.9253677344386608,80.60593781761291,138.254,3.3668000000000022
+5161,5169,91182-09-1,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NCCCC,Training,1,1,92,0.3557345766216318,85.38,62.31410000000003,2.4609371403251283,422.86085087840524,238.24299999999994,2.1172999999999997
+5162,5170,91-19-0,n1ccnc2ccccc12,Training,1,0,48,0.5412819114011972,25.78,39.53800000000002,2.888051601657992,278.23446335792846,130.14999999999998,1.6298
+5163,5171,91-20-3,c1ccc2ccccc2(c1),Training,0,0,48,0.5114311994891171,0.0,43.94800000000003,2.8880516016579914,271.01518240905483,128.17399999999995,2.839800000000001
+5164,5172,91-22-5,n1cccc2ccccc12,Training,1,0,48,0.5311915584041306,12.89,41.74300000000002,2.888051601657992,275.7051383449476,129.16199999999998,2.2348
+5165,5173,91-23-6,O=[N+]([O-])c1ccccc1(OC),Training,1,1,58,0.4786228959968397,52.370000000000005,39.648400000000024,3.121219318886156,272.1431256273244,153.13699999999997,1.6034
+5166,5174,91254-92-1,O=[N+]([O-])c1ccc2ccc3cccc4cc(O)c1c2c34,Training,1,1,96,0.3178220983140643,63.370000000000005,78.46520000000002,2.4211312733767154,991.1396317656959,263.252,4.197800000000002
+5167,5175,91254-93-2,O=[N+]([O-])c1ccc2ccc3cccc4c(O)cc1c2c34,Training,1,1,96,0.3178220983140643,63.370000000000005,78.46520000000002,2.4109446347911314,991.1396317656959,263.252,4.197800000000002
+5168,5176,91254-96-5,O=[N+]([O-])c1ccc2c(O)cc4cccc3ccc1c2c34,Training,1,1,96,0.3178220983140643,63.370000000000005,78.46520000000004,2.4036512163751045,991.1396317656959,263.252,4.197800000000001
+5169,5177,91254-97-6,O=[N+]([O-])c1ccc2cc(O)c4cccc3ccc1c2c34,Training,1,1,96,0.3178220983140643,63.370000000000005,78.46520000000004,2.39428497047225,991.1396317656959,263.252,4.197800000000001
+5170,5178,91259-16-4,O=[N+]([O-])c5ccc2ccc3cccc4c1ccccc1c5(c2c34),Training,1,1,108,0.17366715134946129,43.14,94.30640000000005,2.2836195863668385,1240.4324987418463,297.3130000000001,5.645400000000003
+5171,5179,91379-15-6,OCC(O)COC=CC=CC=CC=CC=CCCCC,Training,1,1,112,0.346269864925439,49.69,84.26960000000004,3.6272387380632747,338.1442792993511,278.39200000000005,3.284900000000002
+5172,5180,91-44-1,O=C2Oc1cc(ccc1C(=C2)C)N(CC)CC,Training,0,0,90,0.7614050902888262,33.45,70.78200000000004,2.60748727943089,582.2821705947141,231.29499999999993,2.9476200000000015
+5173,5181,91-53-2,O(c1ccc2NC(C=C(c2(c1))C)(C)C)CC,Training,0,0,86,0.8153192987016581,21.259999999999998,68.96370000000003,2.4152699754678197,432.36152386019273,217.31199999999998,3.692700000000002
+5174,5182,91540-29-3,c1ccc3c(c1)c2ccccc2C4N(CCCCC)C34,Training,1,1,102,0.5565699993186879,3.01,83.59100000000005,1.7201973789755527,579.6683055943938,263.3839999999999,4.955200000000004
+5175,5183,91540-30-6,C=CCN2C3c4ccccc4(c1ccccc1C23),Training,1,1,88,0.5603645818004411,3.01,74.26300000000003,1.939069258870873,577.5121481767807,233.314,3.951000000000003
+5176,5184,91549-70-1,O=C(NCCN(C)C)c2ccc3nc1ccccc1c(N)c3(c2),Training,0,1,118,0.7253218934992408,71.25,94.54860000000005,1.9619618675252568,873.4042720742472,308.3850000000001,2.2616000000000005
+5177,5185,91549-71-2,O=C(NCCN(C)C)c3ccc2c(nc1ccccc1c2(N))c3,Training,0,1,118,0.7253218934992408,71.25,94.54860000000005,1.9516599610785574,873.4042720742472,308.3850000000001,2.2616000000000005
+5178,5186,91575-28-9,O=C(Nc1ccc(cc1Cl)Cc2ccc(N)c(c2)Cl)C,Training,1,1,104,0.8378039146227932,55.120000000000005,84.42610000000002,2.1919030613806063,656.3169275170541,309.19599999999997,4.124800000000001
+5179,5187,91575-29-0,O=C(Nc1ccc(cc1Cl)Cc2ccc(NC(=O)C)c(c2)Cl)C,Training,1,1,120,0.8520527476002205,58.2,94.31740000000002,2.157433581692651,696.7537413324869,351.2330000000001,4.501000000000002
+5180,5188,91-58-7,c1ccc2cc(ccc2(c1))Cl,Training,0,1,54,0.5564479696593142,0.0,48.95800000000003,2.828901215620696,379.2844903986785,162.61899999999997,3.4932000000000007
+5181,5189,91-59-8,Nc1ccc2ccccc2(c1),Training,1,1,54,0.5629544406745023,26.02,48.36040000000002,2.8289012156206956,379.28449039867843,143.189,2.4220000000000006
+5182,5190,91598-91-3,O=C(Nc1ccc2ccc4c(O)ccc3ccc1c2c34)C,Training,1,1,102,0.5101656163816406,49.33,86.11450000000004,2.2380833838318606,1004.2583586166578,275.307,4.248000000000001
+5183,5191,91598-92-4,O=C(Nc1ccc2ccc3ccc(O)c4ccc1c2c34)C,Training,1,1,102,0.5101656163816406,49.33,86.11450000000004,2.2391171484367853,1004.2583586166578,275.307,4.248000000000002
+5184,5192,91-62-3,n1cccc2cc(ccc12)C,Training,1,1,54,0.5519055037199659,12.89,46.48000000000002,2.828901215620696,379.2844903986785,143.18899999999996,2.5432200000000007
+5185,5193,91626-52-7,O=C1C(=C(C=NN1S(=O)(=O)C)Cl)Cl,Training,1,0,72,0.7134800927091108,69.03,48.758800000000015,3.637136179410331,492.9912297018169,243.071,0.3577999999999999
+5186,5194,91-63-4,n1c2ccccc2(ccc1C),Training,1,1,54,0.5519055037199659,12.89,46.48000000000002,2.8289012156206956,379.2844903986785,143.18899999999996,2.5432200000000007
+5187,5195,91642-47-6,O=C(OCCCCC)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,98,0.24511311859576107,82.58,64.88040000000002,2.3777737567290287,435.4310989731894,253.254,2.934400000000001
+5188,5196,91-64-5,O=C1Oc2ccccc2(C=C1),Training,1,0,54,0.5302216682110639,30.21,42.484000000000016,2.9353507979720246,428.5108208761056,146.14499999999998,1.793
+5189,5197,91-66-7,c1ccc(cc1)N(CC)CC,Training,0,0,60,0.6380073577226646,3.24,50.003000000000036,2.738498942719903,189.2875676035994,149.23699999999997,2.532800000000001
+5190,5198,91687-67-1,O=C(NCc1ccc(cc1)Cl)C(C)Br,Training,1,0,76,0.8452085466410404,29.1,61.68770000000003,2.459473724017714,310.4029664102151,276.561,2.739600000000001
+5191,5199,91-68-9,Oc1cccc(c1)N(CC)CC,Training,1,1,66,0.7420806150852876,23.47,51.667800000000035,2.8535996003017368,243.34882468182084,165.236,2.2383999999999995
+5192,5200,918-00-3,O=C(C)C(Cl)(Cl)Cl,Training,1,1,42,0.4963889883221809,17.07,30.971,3.7911184170869663,82.67103446305711,161.41500000000002,1.9456
+5193,5201,91828-72-7,O=[N+]([O-])c4cc2c(ccc1c2(C=CC(O)C1(O)))c3ccccc34,Training,1,1,114,0.41019521370161605,83.60000000000001,88.10900000000001,2.1796497885102086,993.1402390208038,307.305,3.322300000000001
+5194,5202,91-84-9,n1ccccc1N(Cc2ccc(OC)cc2)CCN(C)C,Training,0,0,112,0.7817668594270732,28.6,86.83500000000005,2.1048843505456873,525.491301034188,285.391,2.658400000000001
+5195,5203,91-93-0,O=C=Nc1ccc(cc1(OC))c2ccc(N=C=O)c(OC)c2,Training,1,1,110,0.6261606368107588,77.32000000000001,80.54500000000003,2.5169828031274624,721.2279699067143,296.282,3.3054000000000014
+5196,5204,91-95-2,Nc1ccc(cc1(N))c2ccc(N)c(N)c2,Training,1,1,82,0.5419332134305994,104.08,69.52759999999999,2.5020803743746223,485.037124074059,214.27200000000002,1.6824000000000001
+5197,5205,919-86-8,O=P(OC)(OC)SCCSCC,Training,0,0,74,0.49613529513681476,35.53,57.081500000000034,3.5223947479401634,145.72862410467502,230.29099999999997,2.8736000000000015
+5198,5206,91991-18-3,O=C(Nc1c2cc(ccc2(ns1))Cl)C,Training,1,1,72,0.8125677228540185,41.99,58.93370000000002,2.549412673749696,494.51765317885213,226.688,2.908100000000001
+5199,5207,91991-19-4,O=C(Nc1c2cc(ccc2(ns1))Cl)CCl,Training,1,1,78,0.8436546927985612,41.99,63.97970000000002,2.430381208251517,511.78169530462594,261.133,3.1270000000000007
+5200,5208,91991-21-8,O=C(Nc1c2cc(ccc2(ns1))Cl)CCC,Training,0,0,84,0.9077495839980055,41.99,68.16770000000002,2.30366072386033,523.678961590002,254.74199999999996,3.6883000000000017
+5201,5209,91991-22-9,O=C(Nc1c2cc(ccc2(ns1))Cl)CCCC,Training,0,0,90,0.9078486935459708,41.99,72.78470000000003,2.181419406351245,538.2851923416736,268.76899999999995,4.078400000000002
+5202,5210,91991-23-0,O=C(Nc1c2cc(ccc2(ns1))Cl)CC(C)C,Training,0,0,90,0.9162691850537703,41.99,72.71470000000004,2.239598475574878,550.4292465958555,268.769,3.934300000000002
+5203,5211,920-37-6,N#CC(=C)Cl,Training,0,1,26,0.4082646396599957,23.79,20.605999999999995,3.348800763644439,79.38407798525417,87.50899999999999,1.26248
+5204,5212,920-66-1,FC(F)(F)C(O)C(F)(F)F,Training,0,0,62,0.5427331254389618,20.23,18.1168,4.231132186198015,97.14178630198491,168.03599999999997,1.4718999999999995
+5205,5213,92-06-8,c1ccc(cc1)c2cccc(c2)c3ccccc3,Training,0,0,86,0.5794896680157822,0.0,77.31400000000004,2.0535802172902335,569.7160655475085,230.30999999999997,5.0206000000000035
+5206,5214,92072-09-8,O=[N+]([O-])c3ccc1c5cccc4ccc(c(c2cccc3(c12))c45)[N+](=O)[O-],Training,1,1,124,0.18196342363134224,86.28,100.96080000000005,2.2127213939771546,1391.290208613586,342.3100000000001,5.553600000000002
+5207,5215,921-14-2,NN(C(C)C)C(C)C,Training,1,0,50,0.43019405172621317,29.259999999999998,36.2984,3.4642268472310964,51.54887502163468,116.20799999999998,0.9788999999999999
+5208,5216,92116-66-0,n1cc(nc3c1ccc2c3(ncn2C))C,Training,0,1,74,0.5531133866977562,43.6,58.54700000000002,2.57492824054448,654.0413933819901,198.22899999999996,1.8249199999999999
+5209,5217,92116-67-1,n1cc(nc2c1ccc(NC)c2(N))C,Training,0,1,72,0.6665008162018184,63.83,58.23410000000001,2.7935163503653833,478.7508472488082,188.23399999999995,1.56212
+5210,5218,92130-56-8,n1cccc3c1cc(c2c3(ncn2C))C,Training,0,1,74,0.5538186600366665,30.71,60.752000000000024,2.6480914186940554,652.3207036761831,197.24099999999999,2.42992
+5211,5219,92134-94-6,O=NN1CCSC1C(O)C(O)C(O)CO,Training,0,0,88,0.41432773810256385,113.59000000000002,53.85320000000004,2.5789338622743014,219.5572252253288,238.26500000000004,-1.8823000000000003
+5212,5220,92134-95-7,O=NN1CCSC1C(O)C(O)C(O)C(O)C,Training,0,0,94,0.4405414499223423,113.59000000000002,58.44820000000004,2.616912083190218,242.46855956017873,252.29200000000006,-1.4938000000000007
+5213,5221,92134-97-9,O=NN1C(C(=O)O)CSC1C(O)C(O)C(O)C(O)CO,Training,0,0,116,0.26490774653264804,171.11999999999998,66.41680000000002,2.7827529731655885,358.83924876242435,312.30000000000007,-3.0681999999999996
+5214,5222,92180-79-5,n2c(N)n(c3ccc1nc(c(nc1c23)C)C)C,Training,1,1,86,0.6344439144723893,69.62,67.69640000000001,2.5484083620362994,741.5606544292406,227.27099999999996,1.7155399999999996
+5215,5223,92-24-0,c1ccc2cc3cc4ccccc4(cc3(cc2(c1))),Training,1,1,84,0.36517781288626455,0.0,78.96000000000002,2.1970695771462623,728.2526221384028,228.29399999999998,5.146200000000003
+5216,5224,922-63-4,O=CC(=C)CC,Training,1,1,34,0.36208456954875373,17.07,25.49499999999999,3.234390866915873,64.33869642763739,84.118,1.1515
+5217,5225,92279-99-7,n2c1ccccc1c(NCCCNCCCl)c3cccc(OC)c23,Training,1,1,126,0.3681191699242243,46.18000000000001,102.49740000000004,1.932243137079227,822.175561288235,343.85800000000006,4.027000000000003
+5218,5226,92280-01-8,n2c1ccccc1c(NCCCN(CC)CCCl)c3c2CCCC3,Training,1,1,130,0.5645826506610008,28.160000000000004,104.32570000000005,1.7328036230488995,671.226702442427,345.9180000000001,4.476300000000005
+5219,5227,92-31-9,n2c1ccc(cc1[s+]c3cc(N)c(cc23)C)N(C)C,Training,1,1,96,0.41642782717775,42.15,85.00940000000003,2.3182962891427334,781.0367568387873,270.381,3.6872200000000026
+5220,5228,92339-11-2,O=C(NCC(O)CO)c1c(c(C(=O)NCC(O)CO)c(c(c1I)N(C(=O)C)CC(O)CN(C(=O)C)c2c(c(C(=O)NCC(O)CO)c(c(C(=O)NCC(O)CO)c2I)I)I)I)I,Training,0,0,346,0.059188514179741025,339.09,272.94999999999993,2.8415643659853815,1756.239980385607,1550.1879999999996,-1.5868999999999969
+5221,5229,92-36-4,n2c1ccc(cc1sc2c3ccc(N)cc3)C,Training,1,1,84,0.6559923549408446,38.91,74.20540000000001,2.142938436784814,668.2549997559121,240.331,3.8539200000000022
+5222,5230,924-16-3,O=NN(CCCC)CCCC,Training,1,1,66,0.4211123102525865,32.67,47.184000000000026,3.326343011048127,88.09284782231802,158.24499999999998,2.570000000000001
+5223,5231,92433-40-4,O=C(Nc1cc3c(cc1Cl)c2ccccc2C3)C,Training,1,1,90,0.7044872667569393,29.1,73.99770000000002,2.1084219938290802,648.9370156452684,257.71999999999997,3.869600000000002
+5224,5232,924-42-5,O=C(C=C)NCO,Training,0,0,40,0.35451915637473846,49.33,25.425499999999992,3.172899533850818,79.75898006442378,101.10499999999999,-0.7616000000000003
+5225,5233,92-48-8,O=C1Oc2ccc(cc2(C=C1))C,Training,0,1,60,0.5522573011862888,30.21,47.22100000000002,2.873950478406101,468.46742834865574,160.17199999999997,2.10142
+5226,5234,92-52-4,c1ccc(cc1)c2ccccc2,Training,0,0,58,0.5905018880213778,0.0,51.87800000000003,2.457149480139045,297.4313204906765,154.21199999999996,3.353600000000002
+5227,5235,92-54-6,c1ccc(cc1)N2CCNCC2,Training,0,1,64,0.664835869226176,15.27,51.52470000000003,2.082510086938828,226.8537121839843,162.23599999999996,1.0961999999999996
+5228,5236,92-55-7,O=C(OC(OC(=O)C)c1oc(cc1)[N+](=O)[O-])C,Training,1,1,92,0.3390763961589275,108.88000000000002,51.63540000000001,2.9046603319294886,433.9517756890382,243.171,1.3126
+5229,5237,92569-05-6,O=C1N(C(=O)C(Cl)Cl)CCN1c2ncc([N+](=O)[O-])s2,Training,1,1,102,0.47784790458270016,96.65,68.71740000000001,2.1701502848365894,548.606170470816,325.13300000000004,1.6236
+5230,5238,92569-06-7,O=C(Nc1ncc([N+](=O)[O-])s1)NS(=O)(=O)c2ccc(cc2)C,Training,0,1,116,0.6438264183874844,131.29999999999998,79.28760000000003,2.0681458239005077,813.2628933005835,342.3580000000001,1.87012
+5231,5239,92-59-1,c1ccc(cc1)N(Cc2ccccc2)CC,Training,0,0,82,0.744779946368489,3.24,69.60800000000005,2.129412813255698,407.9647893410623,211.308,3.7131000000000016
+5232,5240,926-06-7,O=S(=O)(OC(C)C)C,Training,1,1,50,0.5176932527374469,43.370000000000005,31.064799999999984,3.7525745580592127,144.66635800869278,138.188,0.371
+5233,5241,92-66-0,c1ccc(cc1)c2ccc(cc2)Br,Training,0,0,64,0.6945848540367182,0.0,59.57800000000003,2.4238559727704243,375.62904776215686,233.10799999999998,4.116100000000002
+5234,5242,92-67-1,Nc1ccc(cc1)c2ccccc2,Training,1,1,64,0.6524355721249985,26.02,56.29040000000002,2.4238559727704247,375.62904776215686,169.227,2.9358000000000013
+5235,5243,92-69-3,Oc1ccc(cc1)c2ccccc2,Training,1,0,64,0.6969384886852025,20.23,53.54280000000003,2.4238559727704247,375.62904776215686,170.211,3.0592000000000015
+5236,5244,92758-43-5,Nc2ccc3ccc4cc1ccccc1c5ccc2c3c45,Training,1,1,98,0.22923894487916932,26.02,92.06440000000005,2.2149901622360453,1138.300167721219,267.331,5.319400000000003
+5237,5245,92-84-2,c1ccc3c(c1)Nc2ccccc2S3,Training,0,1,68,0.5890750135634363,12.03,60.289700000000025,2.1249183216771557,391.75287485739244,199.278,3.894800000000001
+5238,5246,928-73-4,O=C(O)C=NNC(=O)N,Training,0,0,50,0.32091534172599806,104.77999999999999,28.8469,3.4840511574968125,152.38196255841365,131.09099999999998,-1.2749
+5239,5247,92-88-6,Oc1ccc(cc1)c2ccc(O)cc2,Training,0,0,70,0.7184688940221797,40.46,55.20760000000003,2.396509039726096,371.5796467381504,186.21,2.764800000000001
+5240,5248,92887-88-2,N#CCCN(c3ccc(N=Nc1ccc2ncsc2(c1))cc3)C,Training,1,1,114,0.6167564396654837,64.64,93.73800000000001,1.7062424778692773,860.571153663573,321.40900000000005,5.061580000000003
+5241,5249,92911-19-8,N(=Nc1ccc2ncsc2(c1))c3ccc(cc3)NC,Training,1,1,94,0.6964971103307306,49.64,79.78470000000003,1.8361792369321415,715.6489857236501,268.345,4.753400000000003
+5242,5250,92-93-3,O=[N+]([O-])c1ccc(cc1)c2ccccc2,Training,1,1,74,0.5499294237699656,43.14,58.53240000000003,2.361069147232481,462.7406095598427,199.209,3.261800000000002
+5243,5251,92-94-4,c1ccc(cc1)c2ccc(cc2)c3ccccc3,Training,0,0,86,0.5794896680157823,0.0,77.31400000000004,1.951466168669556,548.7160655475084,230.31,5.0206000000000035
+5244,5252,93-05-0,Nc1ccc(cc1)N(CC)CC,Training,1,1,66,0.6932084973043754,29.259999999999998,54.415400000000034,2.798428921163266,224.09882468182084,164.25199999999998,2.115
+5245,5253,93-08-3,O=C(c1ccc2ccccc2(c1))C,Training,0,1,64,0.601009735328557,17.07,53.95250000000002,2.6860346638769905,457.3860595287063,170.21099999999998,3.0424000000000015
+5246,5254,93106-60-6,O=C(O)C1=CN(c2cc(c(F)cc2(C1(=O)))N3CCN(CC)CC3)C4CC4,Training,1,1,138,0.9075489986969112,65.78,97.72330000000005,1.834238302456375,927.751757198637,359.4010000000002,2.3156
+5247,5255,93-15-2,O(c1ccc(cc1(OC))CC=C)C,Training,0,0,70,0.6591252605281698,18.46,53.44700000000003,2.9753267561054875,292.141794956603,178.23099999999997,2.4323000000000006
+5248,5256,931-97-5,N#CC1(O)(CCCCC1),Training,0,0,50,0.4942945434148664,44.019999999999996,33.64779999999999,2.4892566858759495,130.34180215676218,125.171,1.20518
+5249,5257,93261-88-2,O=C(c3oc(c(c1ccccc1)c3(c2ccccc2))[N+](=O)[O-])CBr,Training,1,1,120,0.26472457129027,73.35,94.35890000000003,2.3858621225093963,888.1420467205954,386.2010000000001,5.099400000000003
+5250,5258,93-27-6,O=C(Nc1ccc(cc1(OC))[N+](=O)[O-])C,Training,1,1,80,0.605871107393287,81.47,53.95210000000001,3.084745947349959,403.0988596773161,210.18899999999996,1.5617999999999999
+5251,5259,932-83-2,O=NN1CCCCCC1,Training,1,1,52,0.501667610280594,32.67,35.836,2.2587454754143512,87.05865002596163,128.175,1.5438
+5252,5260,93285-74-6,c1ccc6c(c1)cc4c3c6(cc2ccccc2c3C5=C4CCCC5),Training,1,1,114,0.24356069761674506,0.0,104.24200000000005,1.9339724990140494,1190.9993615762612,306.40800000000013,6.944400000000004
+5253,5261,932-97-8,[N-]=[N+]=C1C=CC(=O)C=C1,Training,1,0,44,0.2583402619044026,53.470000000000006,31.91339999999999,2.9414405676539888,225.7834751254812,120.11099999999998,0.35229999999999995
+5254,5262,933-75-5,Oc1c(ccc(c1Cl)Cl)Cl,Training,0,0,54,0.6324908101043021,20.23,43.13680000000001,3.3421538077705124,232.4149958700664,197.448,3.3524000000000003
+5255,5263,933-78-8,Oc1cc(cc(c1Cl)Cl)Cl,Training,0,0,54,0.6324908101043021,20.23,43.13680000000001,3.3105328747224085,236.16499587006643,197.448,3.3524000000000003
+5256,5264,933-88-0,O=C(c1ccccc1C)Cl,Training,1,1,52,0.5679905040929671,17.07,41.36250000000001,3.1529414466808685,255.1894333808838,154.59599999999998,2.3740200000000007
+5257,5265,934-32-7,n1c(N)[nH]c2ccccc12,Training,0,1,50,0.5658999712435825,54.699999999999996,40.5061,2.876510166944625,317.37870592409797,133.15399999999997,1.1451
+5258,5266,93-45-8,Oc1ccc(cc1)Nc2ccc3ccccc3(c2),Training,0,0,88,0.6493162984990817,32.26,75.33750000000003,1.9239063256573465,674.0015750695981,235.28600000000003,4.289000000000002
+5259,5267,93-46-9,c1ccc2cc(ccc2(c1))Nc3ccc(cc3)Nc4ccc5ccccc5(c4),Training,1,1,134,0.34698219281138976,24.06,120.90340000000002,1.3247987440768205,1156.1923057852443,360.46000000000004,7.480200000000004
+5260,5268,934-73-6,O=S(c1ccc(cc1)Cl)C,Training,0,0,54,0.63737277323457,17.07,43.78440000000002,3.003400684579817,242.28794892648057,174.65199999999996,2.0774
+5261,5269,93-52-7,c1ccc(cc1)C(CBr)Br,Training,1,0,54,0.7166938223823025,0.0,51.90400000000002,2.746978188530898,183.70889642965702,263.96,3.517500000000002
+5262,5270,93535-04-7,Nc1ccc(cc1)C=Cc2cccc(c2)Cl,Training,1,1,80,0.6092380415361511,26.02,71.23440000000002,2.177634284106821,500.3987204825034,229.71,4.092600000000002
+5263,5271,93-58-3,O=C(OC)c1ccccc1,Training,0,0,52,0.546322425537599,26.3,37.781500000000015,2.8526279288191434,215.9590174505521,136.14999999999998,1.4732
+5264,5272,935-95-5,Oc1c(c(cc(c1Cl)Cl)Cl)Cl,Training,0,0,60,0.6695808979155974,20.23,48.14680000000001,3.4555464838177836,270.8740242221354,231.89299999999997,4.005799999999999
+5265,5273,93673-31-5,O4C5c3cccc2cc1c6ccccc6(ccc1c(c23)C45),Training,1,1,98,0.24022938167536195,12.53,85.52700000000004,1.9340005445493977,1077.2526737358062,268.315,5.272200000000003
+5266,5274,93673-33-7,O5C6c4cccc3cc2ccc1ccccc1c2c(c34)C56,Training,1,1,98,0.24022938167536195,12.53,85.52700000000004,1.9666321234010864,1077.2526737358062,268.315,5.272200000000003
+5267,5275,93673-34-8,O3C4c2cccc1c5cc6ccccc6(cc5(cc(c12)C34)),Training,1,1,98,0.24022938167536195,12.53,85.52700000000003,1.8902664209884465,1077.2526737358062,268.315,5.272200000000003
+5268,5276,93673-37-1,OC2C=Cc1c3cc5cccc4C=Cc(c3(ccc1C2(O)))c45,Training,1,1,106,0.4813060414077057,40.46,90.38260000000002,1.9662504190942554,1011.3069379710645,286.33000000000004,3.897900000000003
+5269,5277,93673-39-3,Oc5cccc1c5(ccc2c4C=Cc3cccc(cc12)c34),Training,1,1,98,0.29688126759726985,20.23,89.55280000000003,2.1110603906581766,1087.3305725938344,268.31500000000005,5.335600000000003
+5270,5278,93-68-5,O=C(Nc1ccccc1C)CC(=O)C,Training,0,0,74,0.7416579046219026,46.17,55.106700000000025,2.649628786208871,358.0600935330302,191.22999999999993,1.91262
+5271,5279,93-72-1,O=C(O)C(Oc1cc(c(cc1Cl)Cl)Cl)C,Training,0,0,82,0.8543653385157547,46.53,59.197800000000015,2.952681123248563,392.4341135811158,269.511,3.4987000000000013
+5272,5280,937-40-6,O=NN(C)Cc1ccccc1,Training,1,1,58,0.4858304123477697,32.67,43.70400000000003,2.5732138592946923,222.79348430668875,150.18099999999998,1.7998
+5273,5281,93-76-5,O=C(O)COc1cc(c(cc1Cl)Cl)Cl,Training,0,0,76,0.8442550207983773,46.53,54.602800000000016,2.8666294689758747,365.0942913293867,255.484,3.1102000000000007
+5274,5282,93780-95-1,OC3c2ccc1cc5ccc6ccccc6(c5(nc1c2C4OC4(C3(O)))),Training,1,1,122,0.2947796237914451,65.88000000000001,95.33560000000001,1.7469841452895,1186.0293815265875,329.3550000000001,3.3890000000000033
+5275,5283,93793-83-0,O=C(OCC(=O)NCCCOc1cccc(c1)CN2CCCCC2)C,Training,0,0,138,0.5468456379677686,67.87,95.32470000000006,1.6263946586255487,556.1100035826124,348.4430000000002,2.1206999999999994
+5276,5284,93-79-8,O=C(OCCCC)COc1cc(c(cc1Cl)Cl)Cl,Training,0,0,100,0.4444426509694634,35.53,72.83400000000003,2.480800590764234,421.27381680333934,311.592,4.368900000000003
+5277,5285,938-55-6,N=1C=NC=2C=1N=CNC=2N(C)C,Training,1,1,62,0.6595004135767215,57.7,45.126700000000014,2.6276828215443184,352.85932312414513,163.18399999999997,0.3704999999999999
+5278,5286,938-73-8,O=C(N)c1ccccc1(OCC),Training,0,0,64,0.7308083074639656,52.32000000000001,46.128900000000016,2.9976300631078683,283.61195376207496,165.19199999999995,1.1842
+5279,5287,93943-58-9,O=CC2=C(CC(C1=CCC(C)(C)C1)C)C(O)OC2,Training,0,1,100,0.6159769935371611,46.53,69.92780000000003,2.03912889729415,403.9617766609257,250.33799999999994,2.6031000000000004
+5280,5288,939-99-1,FC(F)(F)c1ccc(cc1)CCl,Training,0,0,66,0.6010637518598146,0.0,41.00100000000002,2.92530549887868,250.00063728104428,194.583,3.4442000000000013
+5281,5289,940-14-7,O=[N+]([O-])c1ccc(OC=C)cc1,Training,1,1,62,0.3912613052669894,52.370000000000005,43.92140000000002,2.846340723505505,291.67621196610224,165.14799999999997,2.1170999999999998
+5282,5290,94-11-1,O=C(OC(C)C)COc1ccc(cc1Cl)Cl,Training,0,0,88,0.7814566696146591,35.53,63.18500000000003,2.5137710721643542,377.4924663857149,263.12,3.323800000000002
+5283,5291,94-13-3,O=C(OCCC)c1ccc(O)cc1,Training,0,0,70,0.723052379328443,46.53,48.68030000000003,2.611171250638134,276.7262618127396,180.203,1.9589999999999999
+5284,5292,94-20-2,O=C(NCCC)NS(=O)(=O)c1ccc(cc1)Cl,Training,0,0,94,0.8794576573550539,75.27000000000001,65.46320000000003,2.7503464362871206,484.77740369929194,276.745,1.7379
+5285,5293,94223-87-7,n1c5ccc(cc5(cc2c1c4cccc3cccc2c34))C,Training,0,0,98,0.3686386362298839,12.89,88.41600000000004,1.984192391503657,1038.997515910278,267.331,5.343820000000004
+5286,5294,94223-88-8,O=[N+]([O-])c1ccc2nc3c(cc2(c1))c5cccc4cccc3c45,Training,1,1,108,0.325018591658869,56.03,90.33340000000001,1.8986702245577498,1143.595156619394,298.30100000000004,4.943600000000003
+5287,5295,94-25-7,O=C(OCCCC)c1ccc(N)cc1,Training,0,0,76,0.4529213480251256,52.32,56.04490000000003,2.481072534225339,292.660770563408,193.246,2.2257
+5288,5296,94339-55-6,OC1c2cc3ccc4cccc5ccc(c2(C=CC1))c3c45,Training,1,1,100,0.44401584905497754,20.23,88.75680000000004,2.103502362262145,1010.476941776831,270.331,5.034300000000002
+5289,5297,94339-56-7,OC2C=Cc1c3ccc5cccc4ccc(cc1C2)c3c45,Training,1,1,100,0.46590689185555956,20.23,88.89080000000006,2.0630673264249606,1010.4769417768312,270.331,4.514200000000002
+5290,5298,94-36-0,O=C(OOC(=O)c1ccccc1)c2ccccc2,Training,0,0,90,0.5996635086620677,52.6,63.71500000000003,1.9296630435110773,482.7351541205121,242.23000000000002,2.615400000000001
+5291,5299,943-93-1,O1C2CCC=CCCC=CCCC12,Training,0,0,72,0.40963642648396265,12.53,54.643000000000036,1.798429676831087,183.17001630580293,178.27499999999998,3.2204000000000015
+5292,5300,94-41-7,O=C(C=Cc1ccccc1)c2ccccc2,Training,0,0,78,0.5562298197848601,17.07,66.24850000000004,2.1172786918812947,483.3581054615089,208.26000000000002,3.5827000000000018
+5293,5301,944-22-9,O(CC)P(CC)(=S)Sc1ccccc1,Training,0,1,78,0.7224251548088033,9.23,68.75100000000003,2.7054883512104966,313.15785391237847,246.33700000000002,4.144600000000003
+5294,5302,94-45-1,n2c1ccc(OCC)cc1sc2N,Training,1,1,68,0.7974077275753165,48.14,55.201400000000014,2.481966974516596,424.4719650273174,194.259,2.2772
+5295,5303,94495-71-3,O=C4Oc1c(c(OC)c(O)c2OC3OC=CC3(c12))C5=C4C(=O)CC5,Training,1,1,122,0.7997233619771871,95.20000000000002,80.73430000000002,1.9853057259103593,1014.2417321475793,328.2760000000002,1.9820999999999998
+5296,5304,94500-43-3,OCc1cc4c5ccccc5(cc3ccc2cccc1c2c34),Training,0,1,104,0.32954103958388603,20.23,93.57480000000004,2.208446266740905,1154.3480587215813,282.34200000000004,5.229500000000003
+5297,5305,94500-44-4,c1ccc5c(c1)cc3ccc2cccc4c2c3c5(cc4CCl),Training,1,0,104,0.1888098175126323,0.0,97.20900000000003,2.208446266740905,1154.3480587215813,300.788,6.4760000000000035
+5298,5306,94500-46-6,c1ccc2c(c1)cc3cc(c5cccc4ccc2c3c45)CCl,Training,1,0,104,0.1888098175126323,0.0,97.20900000000005,2.1908535309928214,1154.3480587215813,300.788,6.4760000000000035
+5299,5307,94500-53-5,OCc2cc5cccc4ccc3cc1ccccc1c2c3c45,Training,0,1,104,0.32954103958388603,20.23,93.57480000000005,2.2293537367839202,1154.348058721581,282.34200000000004,5.229500000000003
+5300,5308,94500-54-6,c1ccc2c(c1)cc3ccc4cccc5cc(c2c3c45)CCl,Training,1,0,104,0.1888098175126323,0.0,97.20900000000003,2.2293537367839193,1154.3480587215813,300.788,6.4760000000000035
+5301,5309,94574-56-8,O=C(OCc1c(O)cc2C(=O)c3ccccc3(C(=O)c2(c1(O))))C,Training,1,1,116,0.7012678658758772,100.9,78.54860000000002,2.193468676738971,865.6275809285623,312.27700000000004,1.9362999999999997
+5302,5310,94-58-6,O1c2ccc(cc2(OC1))CCC,Training,0,0,64,0.6676723734723985,18.46,46.56000000000003,2.2618069364467726,281.1671103240186,164.20399999999998,2.367800000000001
+5303,5311,94-59-7,O1c2ccc(cc2(OC1))CC=C,Training,0,0,62,0.6201277561173599,18.46,46.46600000000002,2.3167377858533187,304.7069310172286,162.188,2.1437999999999997
+5304,5312,94-62-2,O=C(C=CC=Cc1ccc2OCOc2(c1))N3CCCCC3,Training,0,0,110,0.6327883020732139,38.77,81.17000000000004,1.5596547149797815,571.3979945235308,285.343,2.997200000000001
+5305,5313,94-70-2,O(c1ccccc1(N))CC,Training,0,1,54,0.6290814951669368,35.25,42.02340000000001,2.8111809171884006,210.16749419417292,137.18200000000002,1.6675000000000002
+5306,5314,94740-40-6,O=NN(C(=O)C1N(C(=O)C)CCC1)CC(=O)O,Training,1,1,94,0.5331936225800383,107.35000000000001,55.55280000000002,2.7602147145797846,356.5404885166978,243.21899999999994,-0.40810000000000085
+5307,5315,94-74-6,O=C(O)COc1ccc(cc1C)Cl,Training,0,0,70,0.8131158175997405,46.53,49.31980000000002,2.7194415184626908,322.63589476880867,200.62099999999998,2.11182
+5308,5316,94-75-7,O=C(O)COc1ccc(cc1Cl)Cl,Training,0,0,70,0.85199274417323,46.53,49.59280000000002,2.7194415184626908,325.16521978178946,221.039,2.4568000000000003
+5309,5317,94764-55-3,O=[N+]([O-])c2ccc3c1ccccc1sc3(c2),Training,1,1,78,0.467863471386403,43.14,65.98540000000003,2.409407788086353,702.3776755816397,229.26,3.9627000000000008
+5310,5318,947-72-8,c1ccc2c(c1)cc(c3ccccc23)Cl,Training,1,1,72,0.476239910717608,0.0,66.46400000000003,2.638447883812873,640.957112138695,212.67899999999997,4.6464000000000025
+5311,5319,947-73-9,Nc2cc1ccccc1c3ccccc23,Training,1,1,72,0.42835853156085796,26.02,65.86640000000003,2.6384478838128724,640.957112138695,193.249,3.5752000000000015
+5312,5320,94-80-4,O=C(OCCCC)COc1ccc(cc1Cl)Cl,Training,0,0,94,0.5869538552286919,35.53,67.82400000000004,2.366463998272113,380.013532483327,277.14700000000005,3.7155000000000022
+5313,5321,94-81-5,O=C(O)CCCOc1ccc(cc1C)Cl,Training,0,0,82,0.7886629905263893,46.53,58.55380000000003,2.404692996477168,349.6863125286536,228.675,2.8920200000000014
+5314,5322,94-82-6,O=C(O)CCCOc1ccc(cc1Cl)Cl,Training,0,0,82,0.8145307694678334,46.53,58.82680000000003,2.404692996477168,352.5207793847902,249.09300000000002,3.237000000000002
+5315,5323,94840-66-1,O=C(O)C(N)CSC(F)(F)C(F)F,Training,0,0,78,0.6793535046948719,63.31999999999999,39.02020000000001,3.9450552231202876,189.37319965689187,221.17499999999998,0.9894000000000005
+5316,5324,94887-71-5,O=S(=O)(O)Oc1cc(cc(c1(N))Cl)Cc2cc(O)c(N)c(c2)Cl,Training,0,1,124,0.36418628308231876,135.87,88.3762,2.409523563973951,847.9039799217104,379.221,2.6357999999999997
+5317,5325,95050-14-9,O=[N+]([O-])c6cccc5c1cc4cccc3ccc2ccc(c1c2c34)c56,Training,1,1,116,0.20728775802973945,43.14,101.23040000000003,1.945486551051897,1367.6092909079675,321.3350000000001,6.139600000000002
+5318,5326,95-06-7,C=C(CSC(N(CC)CC)=S)Cl,Training,1,1,70,0.6748250408157072,3.24,62.970000000000034,3.766284484667463,166.44079551951015,223.79399999999998,3.0988000000000016
+5319,5327,95-14-7,n1nc2ccccc2([nH]1),Training,1,0,44,0.5607362152362961,41.57,33.88869999999999,2.9546597902851044,282.28075871425636,119.12699999999998,0.9578999999999998
+5320,5328,95152-79-7,O=[N+]([O-])c1ccc(cc1)c3nc2n(cc(C)s2)c3[N+](=O)[O-],Training,1,1,106,0.5456424237569132,103.58,76.55080000000002,2.1897907394773006,865.3951258502625,304.28700000000003,3.1876200000000017
+5321,5329,95-16-9,n1csc2ccccc12,Training,0,0,44,0.5397735725540235,12.89,39.62000000000002,2.954659790285104,282.89393676634353,135.19099999999997,2.2963000000000005
+5322,5330,951-78-0,O=C1C=CN(C(=O)N1)C2OC(CO)C(O)C2,Training,0,0,88,0.552382719533219,104.55000000000001,52.942300000000024,2.2658980772377593,479.2779559208222,228.20399999999998,-1.8226999999999998
+5323,5331,951-80-4,n2c1ccccc1c(N)c3ccc(N)cc23,Training,1,1,78,0.4414472626928828,64.92999999999999,68.07380000000002,2.55225726979096,689.1378427386807,209.252,2.5523999999999996
+5324,5332,95186-19-9,OCCc1c(nc(N)n2ncnc12)c3ccccc3,Training,0,0,96,0.725692877587237,89.33,71.42020000000002,2.308616927471942,707.6303631413393,255.28100000000003,0.9082999999999996
+5325,5333,95-19-2,OCCN1C(=NCC1)CCCCCCCCCCCCCCCCC,Training,0,0,148,0.3091599810177378,35.83,110.5068000000001,1.7614305431204995,317.1490803783339,352.60700000000014,5.954300000000006
+5326,5334,952-23-8,n1c3cc(N)ccc3(cc2ccc(N)cc12),Training,1,1,78,0.4414472626928828,64.92999999999999,68.07380000000002,2.4397721399992816,632.1378427386805,209.25199999999998,2.5523999999999996
+5327,5335,952-97-6,O=[N+]([O-])c1ccc(cc1)Sc2ccccc2,Training,1,1,80,0.5965279185654896,43.14,63.661400000000036,2.143385024320089,482.13176398410815,231.27599999999998,3.746000000000002
+5328,5336,95307-47-4,O=C(O)C4(C)(CCCC2(C)(C4(CCC13(CC(O)(C(=C)C1(O))CCC23)))),Training,0,1,134,0.6439167659731055,77.76,90.29540000000004,1.7895849342493897,614.7601063032595,334.4560000000001,3.1258000000000017
+5329,5337,95-33-0,n2c1ccccc1sc2SNC3CCCCC3,Training,0,0,90,0.8399410248536084,24.92,75.48570000000004,1.6372019750951294,455.88004875061125,264.419,4.2257000000000025
+5330,5338,95331-48-9,O=C(N(O)c4ccc1ccc2cccc3ccc4(c1c23))C,Training,1,1,102,0.31899429732889895,40.540000000000006,85.09250000000004,2.2290504938639772,974.6408607246677,275.307,4.326100000000002
+5331,5339,95389-75-6,[N-]=[N+]=Nc3nc2ccc1ccccc1c2n3C,Training,1,1,82,0.3523088494686262,66.58000000000001,67.02600000000002,2.5288424135468413,765.0076245514706,223.239,3.668300000000002
+5332,5340,954-46-1,O=[N+]([O-])c3cc1ccccc1c2ccccc23,Training,1,1,82,0.35644235437100646,43.14,68.10840000000003,2.590696146592083,734.4562652641641,223.231,3.901200000000002
+5333,5341,95-46-5,c1ccc(c(c1)C)Br,Training,0,0,42,0.5624635581750883,0.0,38.87900000000001,3.1348615113454477,160.49662946459569,171.03699999999998,2.7575200000000013
+5334,5342,95-47-6,c1ccc(c(c1)C)C,Training,0,0,42,0.47575768534032103,0.0,35.916,3.1348615113454477,156.14811391899892,106.16799999999998,2.30344
+5335,5343,95-48-7,Oc1ccccc1C,Training,0,0,42,0.5359354364287862,20.23,32.84379999999999,3.134861511345448,160.49662946459569,108.13999999999999,1.70062
+5336,5344,95-49-8,c1ccc(c(c1)C)Cl,Training,0,0,42,0.5015016660067645,0.0,36.189,3.1348615113454477,160.49662946459569,126.58599999999998,2.6484200000000007
+5337,5345,95-50-1,c1ccc(c(c1)Cl)Cl,Training,0,0,42,0.5285863388321962,0.0,36.46200000000001,3.1348615113454477,162.63833891467198,147.004,2.9934000000000003
+5338,5346,95-51-2,Nc1ccccc1Cl,Training,0,1,42,0.5297860823199099,26.02,35.86440000000001,3.134861511345448,164.63833891467198,127.574,1.9222
+5339,5347,95-54-5,Nc1ccccc1(N),Training,1,1,42,0.4839273658917496,52.04,35.2668,3.134861511345448,162.63833891467198,108.144,0.851
+5340,5348,95-55-6,Oc1ccccc1(N),Training,1,1,42,0.3849667558355937,46.25,32.51919999999999,3.134861511345448,164.63833891467198,109.128,0.9743999999999999
+5341,5349,95-57-8,Oc1ccccc1Cl,Training,0,0,42,0.5671077548351335,20.23,33.1168,3.134861511345448,164.63833891467198,128.558,2.0456000000000003
+5342,5350,95-63-6,c1cc(c(cc1C)C)C,Training,0,0,48,0.4933927122974484,0.0,40.65300000000001,3.1716780304409156,211.2783370413565,120.19499999999998,2.611860000000001
+5343,5351,95-64-7,Nc1ccc(c(c1)C)C,Training,1,1,48,0.5209726320693896,26.02,40.328400000000016,3.1716780304409156,215.80766205433727,121.18299999999999,1.88564
+5344,5352,95-65-8,Oc1ccc(c(c1)C)C,Training,0,0,48,0.5577043959706656,20.23,37.5808,3.1716780304409156,215.80766205433727,122.16699999999999,2.0090399999999997
+5345,5353,95-68-1,Nc1ccc(cc1C)C,Training,1,1,48,0.5209726320693896,26.02,40.328400000000016,3.1716780304409156,215.80766205433727,121.18299999999999,1.88564
+5346,5354,95741-56-3,c1ccc5c(c1)c(c4c3cccc2cccc(c23)c4c5C)C,Training,1,1,104,0.3139786131501948,0.0,95.35800000000005,2.1042376424908253,1000.8302363943983,280.37,6.257240000000006
+5347,5355,95741-57-4,c1ccc2cc3c(cc2(c1))c5cccc4cc(cc3c45)C,Training,1,1,98,0.3247432736502296,0.0,90.62100000000004,2.0152644968277538,1038.4474119296713,266.34299999999996,5.948820000000004
+5348,5356,957-52-8,c1ccc4c(c1)c2cccc3c2c4(ccc3CCl),Training,1,1,86,0.40612091588278265,0.0,77.93500000000003,2.2345018001350607,742.4121453127873,250.72799999999995,5.226000000000003
+5349,5357,95-77-2,Oc1ccc(c(c1)Cl)Cl,Training,0,0,48,0.6227397221533862,20.23,38.12680000000001,3.1716780304409156,222.29788705001033,163.003,2.699
+5350,5358,95-78-3,Nc1cc(ccc1C)C,Training,1,1,48,0.5209726320693896,26.02,40.328400000000016,3.1716780304409156,215.80766205433727,121.18299999999998,1.88564
+5351,5359,95791-46-1,c1ccc3c(c1)ccc4c2ccccc2c(cc34)Cl,Training,1,1,90,0.35140579262754695,0.0,83.97000000000004,2.337122735750299,922.3919838784873,262.739,5.799600000000003
+5352,5360,95-79-4,Nc1cc(ccc1C)Cl,Training,0,1,48,0.551296349469733,26.02,40.60140000000001,3.1716780304409156,220.15617759993404,141.601,2.23062
+5353,5361,958-09-8,OCC3OC(n2cnc1c(ncnc12)N)CC3(O),Training,0,1,96,0.6289933028308912,119.31,61.35500000000002,1.985350028460512,571.6385353073613,251.246,-0.9508000000000005
+5354,5362,95-82-9,Nc1cc(ccc1Cl)Cl,Training,0,0,48,0.5825188519698148,26.02,40.87440000000001,3.1716780304409156,222.29788705001033,162.019,2.5756000000000006
+5355,5363,95-83-0,Nc1ccc(cc1(N))Cl,Training,1,1,48,0.5397866981817153,52.04,40.2768,3.1716780304409156,222.29788705001033,142.589,1.5044
+5356,5364,95840-05-4,OC1C=CC2OC2(C1(O)),Training,1,0,50,0.3263083304746979,52.989999999999995,29.81459999999999,2.161883576095793,154.38196255841365,128.12699999999998,-0.9546000000000001
+5357,5365,95-84-1,Oc1ccc(cc1(N))C,Training,1,1,48,0.40297528147681455,46.25,37.2562,3.1716780304409156,220.15617759993404,123.155,1.28282
+5358,5366,95-85-2,Oc1ccc(cc1(N))Cl,Training,1,0,48,0.42842497449662975,46.25,37.52920000000001,3.1716780304409156,224.29788705001033,143.573,1.6278
+5359,5367,95860-07-4,O=[N+]([O-])c1ccc(c(c1)NO)C,Training,0,0,64,0.520189276712738,75.4,43.24260000000001,3.134300249949543,311.5198400095355,168.152,1.7043199999999998
+5360,5368,95-87-4,Oc1cc(ccc1C)C,Training,0,0,48,0.5577043959706656,20.23,37.5808,3.1716780304409156,215.80766205433727,122.16699999999997,2.0090399999999997
+5361,5369,958-93-0,n1ccccc1N(Cc2ccsc2)CCN(C)C,Training,0,0,96,0.7967911857797698,19.370000000000005,78.16000000000004,2.073203426922918,439.32736809121815,261.394,2.7113000000000005
+5362,5370,95896-78-9,n1cc(nc3c1cc(c2c3(nc(N)n2C))C)C,Training,1,1,86,0.6344439144723893,69.62,67.69640000000001,2.6186762168767466,741.5606544292406,227.27099999999996,1.7155399999999998
+5363,5371,959-23-9,O=C(C=Cc1ccccc1)c2ccc(OC)cc2,Training,0,0,90,0.6006950368606063,26.3,72.80050000000004,2.0946899037137086,539.0694605822265,238.286,3.591300000000002
+5364,5372,95-93-2,c1c(c(cc(c1C)C)C)C,Training,0,0,54,0.5114796780810564,0.0,45.39000000000002,3.2824629074535223,196.2103774276832,134.22199999999998,2.9202800000000018
+5365,5373,959-33-1,O=C(C=Cc1ccc(OC)cc1)c2ccccc2,Training,0,0,90,0.6006950368606063,26.3,72.80050000000004,2.0835216937528966,539.0694605822265,238.28600000000003,3.591300000000002
+5366,5374,95-94-3,c1c(c(cc(c1Cl)Cl)Cl)Cl,Training,0,0,54,0.5666155547825669,0.0,46.482000000000006,3.2824629074535223,205.9198833722299,215.894,4.3002
+5367,5375,95969-40-7,[O-][N+]2(C)(CC=C(c1ccccc1)CC2),Training,0,0,74,0.4912030573577602,23.06,58.32140000000004,2.1905769197158445,340.5991788315501,189.25799999999995,2.418100000000001
+5368,5376,96014-36-7,O=[N+]([O-])c3c(N)ccc2[nH]c1ccccc1c23,Training,1,1,84,0.3805104475471705,84.94999999999999,66.87150000000003,2.601448049939636,745.925182405841,227.223,2.8115000000000006
+5369,5377,96018-75-6,O=CN(O)c1cccc(c1)Cl,Training,0,0,58,0.4180456110702536,40.540000000000006,41.781500000000015,2.9480500083514247,264.37241578261717,171.583,1.692
+5370,5378,961-11-5,O=P(OC(=CCl)c1cc(c(cc1Cl)Cl)Cl)(OC)OC,Training,0,0,106,0.3866254509297224,44.760000000000005,78.01150000000003,3.195069219267893,538.5763442423939,365.96400000000006,5.601500000000003
+5371,5379,96-11-7,C(C(CBr)Br)Br,Training,1,1,38,0.6821704282168467,0.0,40.30300000000001,2.754184786037662,25.219280948873624,280.78499999999997,2.5397000000000007
+5372,5380,96-17-3,O=CC(C)CC,Training,0,0,36,0.4618018883133206,17.07,25.518999999999988,2.964900494759057,41.20310343869659,86.134,1.2314
+5373,5381,96-18-4,C(C(CCl)Cl)Cl,Training,1,1,38,0.5247282741569694,0.0,31.080999999999992,2.754184786037662,25.219280948873624,147.43200000000002,2.0713999999999997
+5374,5382,96-23-1,OC(CCl)CCl,Training,1,1,38,0.5470204373327194,20.23,27.446799999999993,2.7541847860376616,27.974168451037094,128.986,0.8249
+5375,5383,962-32-3,O2C3c5ccccc5(c1cc4ccccc4(cc1C23)),Training,1,1,90,0.525011143629999,12.53,75.95100000000004,1.9008931106640357,818.7881607391033,244.293,4.632800000000002
+5376,5384,962-58-3,O=P(Oc1nc(nc(c1)C)C(C)C)(OCC)OCC,Training,1,0,108,0.715372633783905,70.54,72.34450000000004,2.990376564858854,455.0426471169343,288.28400000000005,3.468320000000002
+5377,5385,96-26-4,O=C(CO)CO,Training,1,0,36,0.4353852085134311,57.53,19.1786,2.98816088213427,44.0,90.078,-1.4599000000000002
+5378,5386,96287-03-5,n1cc(N)c(c2nc3c(cccn3(c12))C)C,Training,1,1,80,0.6203478922077159,56.209999999999994,64.37940000000002,2.6026753617169036,696.8679005773128,212.256,2.0815399999999995
+5379,5387,96-29-7,ON=C(C)CC,Training,1,0,36,0.2911398403892525,32.59,25.186499999999988,3.2188150560434132,58.568425030288566,87.122,1.2465
+5380,5388,96301-34-7,O=C1C=C(C)C4(C(=C1)CCC2C4(CCC3(C(=O)CCC23)(C)))(C),Training,0,0,118,0.6695977993795551,34.14,86.24000000000005,1.7527566409787332,625.618502199986,298.426,4.253500000000003
+5381,5389,96-31-1,O=C(NC)NC,Training,0,0,36,0.4132723717850116,41.13,23.515399999999993,2.98816088213427,46.75488750216347,88.11,-0.4548000000000001
+5382,5390,96-33-3,O=C(OC)C=C,Training,0,0,34,0.33962825058753815,26.3,22.21299999999999,3.234390866915873,65.94833690207419,86.08999999999999,0.34540000000000004
+5383,5391,96-34-4,O=C(OC)CCl,Training,0,0,36,0.3590618766690068,26.3,22.735999999999994,2.98816088213427,46.75488750216347,108.524,0.3982
+5384,5392,96346-61-1,O=C5C=C4C(=C3C(c1ccc(cc1)N(C)C)CC2(C)(C(CCC2(O)(CCCO))C3CC4))CC5,Training,0,0,178,0.6521797320674584,60.77000000000001,132.3016,1.6246478942477516,990.6242837106137,449.6350000000004,5.155700000000007
+5385,5393,96-37-7,CC1CCCC1,Training,0,0,36,0.42179147361668384,0.0,27.631999999999984,2.184105569636068,33.30296890880646,84.162,2.1965000000000003
+5386,5394,96383-86-7,Oc3ccc4ccc2c(ccc1c2(C=CC(O)C1(O)))c4(c3),Training,1,1,104,0.553649419328305,60.69,83.11940000000001,2.115851559219658,895.7385189061036,278.307,3.1197000000000017
+5387,5395,963-89-3,n3c1ccc(cc1c(c4ccc2ccccc2c34)C)C,Training,1,1,96,0.3130929426158614,12.89,86.22900000000004,2.2801691529261157,967.2867569201643,257.33599999999996,5.158040000000003
+5388,5396,96-45-7,N1C(NCC1)=S,Training,1,0,34,0.40178338478966236,24.06,28.603399999999997,2.3673518510178746,63.19344939991072,102.162,-0.5358999999999998
+5389,5397,96-47-9,O1CCCC1C,Training,0,0,36,0.4299172783206054,9.23,24.64799999999999,2.184105569636068,37.20310343869659,86.13399999999999,1.1853
+5390,5398,96-48-0,O=C1OCCC1,Training,0,0,34,0.3967776605314054,26.3,20.192999999999994,2.3673518510178746,59.94833690207419,86.09,0.3234
+5391,5399,96-50-4,n1ccsc1N,Training,1,1,32,0.5215253330648401,38.91,26.526400000000002,3.049648321313926,112.35361803232175,100.146,0.7253000000000001
+5392,5400,96-54-8,c1ccn(c1)C,Training,0,0,32,0.4392057746620909,4.93,25.41299999999999,3.049648321313926,107.4988650600484,81.11799999999998,1.0251
+5393,5401,965-52-6,O=C(NN=Cc1oc(cc1)[N+](=O)[O-])c2ccc(O)cc2,Training,1,1,102,0.499387662026941,117.97000000000001,68.52940000000001,1.9654215364791057,659.9872474445725,275.21999999999997,1.6573
+5394,5402,96563-01-8,O=C(O)C(N)CSC(F)(F)C(F)Cl,Training,0,0,78,0.7069316938168012,63.31999999999999,43.76520000000001,3.9450552231202876,192.61831215472841,237.63,1.2587000000000006
+5395,5403,96563-06-3,c1ccc3c(c1)c2cc(c(cc2C3C)C)C,Training,1,0,80,0.6002679336659499,0.0,68.86900000000003,2.338137994127126,564.2461480497744,208.30399999999997,4.435640000000003
+5396,5404,96563-07-4,c1ccc3c(c1)c2cc(ccc2C3C)C,Training,1,1,74,0.591273939129921,0.0,64.13200000000003,2.339996625038721,523.3115615848764,194.27699999999996,4.127220000000002
+5397,5405,96563-08-5,c1ccc3c(c1)c2c(cccc2C3C)C,Training,1,1,74,0.591273939129921,0.0,64.13200000000003,2.3923898468714375,523.3115615848764,194.27699999999996,4.127220000000002
+5398,5406,96563-09-6,c1cc(cc3c1c2ccc(cc2C3C)C)C,Training,0,1,80,0.6002679336659499,0.0,68.86900000000003,2.2982599765522242,512.7461480497744,208.30399999999997,4.435640000000003
+5399,5407,96563-10-9,Fc2ccc3c1ccc(F)cc1C(c3(c2))C,Training,1,1,80,0.6216220029568547,0.0,59.31100000000003,2.2982599765522242,521.443179140968,216.23,4.097000000000002
+5400,5408,96563-11-0,Fc2ccc3c1ccccc1C(c3(c2))C,Training,1,1,74,0.6007323342869243,0.0,59.35300000000003,2.324785122332467,528.6119516101977,198.23999999999998,3.957900000000002
+5401,5409,96614-59-4,O=C(O)CNC(=O)C(NC(=O)CCC(N)C(=O)O)CSC(=CCl)Cl,Training,1,1,136,0.31974562739290724,158.82,89.66840000000002,4.66344510050901,517.021666171834,402.256,-0.12619999999999904
+5402,5410,96-64-0,O=P(F)(OC(C)C(C)(C)C)C,Training,0,0,68,0.6125948991951918,26.3,44.64050000000002,4.097767717974698,167.7696121417746,182.17499999999998,3.2300000000000013
+5403,5411,96-67-3,O=[N+]([O-])c1cc(N)c(O)c(c1)S(=O)(=O)O,Training,0,0,82,0.21662424289431065,143.76,48.988200000000006,3.5947539886334807,522.6688113613133,234.189,0.12929999999999997
+5404,5412,96687-77-3,O=C(O)C4N(C(=O)CCSSCCC(=O)N2C(C(=O)O)CSC2(c1ccccc1(O)))C(c3ccccc3(O))SC4,Training,0,0,214,0.2108034685104874,155.68,157.30119999999968,1.2877175546693462,1169.2147409778124,624.7840000000002,4.014000000000003
+5405,5413,96-69-5,Oc1cc(c(cc1C(C)(C)C)Sc2cc(c(O)cc2C)C(C)(C)C)C,Training,0,0,136,0.6468828904092667,40.46,107.21060000000006,2.537011223267222,725.6403481817905,358.54700000000014,6.460840000000006
+5406,5414,96839-34-8,O=[N+]([O-])c1cccc(c1CO)[N+](=O)[O-],Training,0,1,74,0.5752578719806516,106.51000000000002,45.67360000000001,3.3940405061093935,357.4165861464257,198.13399999999996,0.9952999999999996
+5407,5415,968-81-0,O=C(NC1CCCCC1)NS(=O)(=O)c2ccc(cc2)C(=O)C,Training,0,0,120,0.8305743326907693,92.34,82.17270000000003,1.9983584904180298,646.6249497468594,324.4020000000001,2.2098000000000004
+5408,5416,96910-70-2,O=CC23(C(=CC1CC(C)(C)CC1C3(C)(C2))CO),Training,1,1,94,0.5887222439477218,37.3,66.38480000000004,2.040707317567271,409.1448824383832,234.33899999999994,2.566400000000001
+5409,5417,96910-71-3,O=CC2=CC1(O)(CC(C)(C)CC1C3(C)(CC23(C=O))),Training,1,1,98,0.7591744233038519,54.37,66.82280000000004,2.1518975662271314,478.1303860297527,248.32199999999995,1.8879
+5410,5418,96910-73-5,O=CC1=CC(C)C2CC(C)(C)CC2(O)(C=C1(C=O)),Training,1,0,98,0.7609171218127954,54.37,68.91280000000003,2.510958208544723,444.65506710308614,248.32199999999997,2.054
+5411,5419,96-91-3,O=[N+]([O-])c1cc(N)c(O)c(c1)[N+](=O)[O-],Training,1,0,74,0.31277551741940296,132.53,45.827999999999996,3.4275044779343165,416.1731577182378,199.12199999999999,0.7907999999999997
+5412,5420,96918-15-9,o1ccc2cc3ccc4cccc5ccc(c12)c3c45,Training,1,1,88,0.3343847860361443,13.14,79.91800000000005,2.2685269523334863,1036.9638030765223,242.277,5.330200000000002
+5413,5421,96918-17-1,O=[N+]([O-])c1oc2c(c1)cc3ccc4cccc5ccc2c3c45,Training,1,1,104,0.24054458372746504,56.28,86.57240000000004,2.106438683678538,1187.1978290185534,287.27400000000006,5.238400000000002
+5414,5422,96918-24-0,o1ccc2c1cc3ccc4cccc5ccc2c3c45,Training,1,1,88,0.3343847860361443,13.14,79.91800000000005,2.268526952333487,1036.9638030765223,242.277,5.330200000000003
+5415,5423,96918-27-3,O=[N+]([O-])c1oc2cc3ccc4cccc5ccc(c2(c1))c3c45,Training,1,1,104,0.24054458372746504,56.28,86.57240000000004,2.1064386836785376,1187.1978290185534,287.27400000000006,5.238400000000002
+5416,5424,96-98-0,O=C(O)c1ccc(c(c1)[N+](=O)[O-])C,Training,1,1,68,0.5545811672294876,80.44,44.79270000000001,3.267052212361692,372.4068180287228,181.14699999999996,1.6014199999999998
+5417,5425,96-99-1,O=C(O)c1ccc(c(c1)[N+](=O)[O-])Cl,Training,1,1,68,0.585764651799086,80.44,45.06570000000001,3.267052212361692,376.7553335743196,201.56499999999997,1.9464
+5418,5426,97-00-7,O=[N+]([O-])c1ccc(c(c1)[N+](=O)[O-])Cl,Training,1,1,68,0.5431080805091585,86.28,44.76080000000001,3.267052212361692,378.8970430243959,202.55299999999997,2.1564000000000005
+5419,5427,97-02-9,O=[N+]([O-])c1ccc(N)c(c1)[N+](=O)[O-],Training,1,1,68,0.4184019522317551,112.30000000000001,44.163199999999996,3.267052212361692,376.14215552223243,183.123,1.0852
+5420,5428,97055-37-3,O=C(O)C(=C(C(Cl)Cl)C(Cl)Cl)Cl,Training,1,1,70,0.6326594241949826,37.3,51.50280000000001,4.940456913984027,199.88411903840284,272.342,3.1713000000000005
+5421,5429,97055-38-4,O=C1OC(OC)C(=C1Cl)C(Cl)Cl,Training,1,1,68,0.5370313172713299,35.53,45.262000000000015,2.947388104180231,236.1928094887362,231.462,1.8123
+5422,5430,97136-66-8,Nc1ccc(cc1)C=Cc2ccc(cc2)C,Training,1,1,80,0.5913385117285661,26.02,70.96140000000003,2.1451719267172638,430.3483304571821,209.292,3.747620000000002
+5423,5431,97166-13-7,CC(C(CBr)Br)Cl,Training,1,1,44,0.6611246347104237,0.0,41.82400000000001,3.144208207369825,46.954453363209694,250.361,2.772100000000001
+5424,5432,97-18-7,Oc1c(cc(cc1Sc2cc(cc(c2(O))Cl)Cl)Cl)Cl,Training,0,0,100,0.7079213197705984,40.46,80.3766,2.4729202264566297,590.6118891901951,356.0569999999999,5.862600000000001
+5425,5433,97-23-4,Oc1ccc(cc1Cc2cc(ccc2(O))Cl)Cl,Training,1,0,88,0.8647127178367139,40.46,69.03960000000002,2.370227579270102,503.61088041818437,269.127,3.9954000000000005
+5426,5434,97-24-5,Oc1ccc(cc1Sc2cc(ccc2(O))Cl)Cl,Training,0,0,88,0.8505061179855621,40.46,70.35660000000001,2.370227579270102,508.6970467453647,287.16700000000003,4.555800000000002
+5427,5435,97-32-5,O=C(Nc1ccccc1)c2ccc(OC)c(c2)[N+](=O)[O-],Training,1,1,102,0.6849934340112487,81.47,74.04360000000003,2.2656881588816358,640.8770925467024,272.26,2.8557000000000015
+5428,5436,97389-17-8,n2cc(nc3cc(c1c(nc(N)n1C)c23)C)C,Training,1,1,86,0.6344439144723893,69.62,67.69640000000001,2.597300529533811,741.5606544292406,227.27099999999996,1.7155399999999998
+5429,5437,97-41-6,O=C(OCC)C1C(C=C(C)C)C1(C)(C),Training,0,0,80,0.5122374841803435,26.3,56.82500000000004,2.6588530245812474,259.49529453537843,196.28999999999996,2.7879000000000014
+5430,5438,97-42-7,O=C(OC1C(=CCC(C(=C)C)C1)C)C,Training,0,0,78,0.49882618094456793,26.3,56.84900000000004,2.662549845627343,276.0463166175518,194.27399999999994,2.850500000000001
+5431,5439,97461-39-7,O=C(OC(C)(C)C)C=Cc1oc(cc1)[N+](=O)[O-],Training,1,1,92,0.3500645942498761,82.58,60.24140000000002,2.6413283639729905,452.6720016392287,239.22699999999998,2.542700000000001
+5432,5440,97461-41-1,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NCC(C)(C)C,Training,1,1,98,0.5060558740473725,85.38,66.86110000000004,2.526396418249071,468.66711499475736,252.26999999999995,2.3632999999999997
+5433,5441,97461-42-2,O=C(C=Cc1oc(cc1)[N+](=O)[O-])NCCCCC,Training,1,1,98,0.3494311584890384,85.38,66.93110000000003,2.3777737567290287,437.04073944762627,252.26999999999992,2.5074000000000005
+5434,5442,97461-43-3,O=C(OC)C(=Cc1oc(cc1)[N+](=O)[O-])C,Training,1,1,80,0.3289961228763351,82.58,51.02940000000001,2.8884053313465152,417.8921238288699,211.17299999999997,1.7641
+5435,5443,97467-07-7,c1ccc(cc1)C2=CC=[N+](C)CC2,Training,1,0,66,0.5711629937320435,3.01,56.15140000000003,2.286487452870546,346.64704302439577,172.25099999999992,2.1868
+5436,5444,97483-08-4,O=P(Oc1c(cc(cc1Cl)C)Cl)(OC)OC,Training,0,1,90,0.7816940690580461,44.760000000000005,63.45150000000003,3.108550682382983,404.5123164021044,285.063,4.081520000000002
+5437,5445,97509-27-8,O=[N+]([O-])c2c3ccccc3(cc1c2(C=CC(O)C1(O))),Training,1,1,96,0.6054017591155579,83.60000000000001,70.60300000000001,2.4325215261634354,707.9033363128012,257.245,2.1691000000000007
+5438,5446,97509-29-0,O=[N+]([O-])c2c3ccccc3(cc1C=CC(O)C(O)c12),Training,0,1,96,0.6054017591155579,83.60000000000001,70.60300000000001,2.4466103601293154,707.9033363128012,257.245,2.1691
+5439,5447,97-52-9,O=[N+]([O-])c1ccc(N)c(OC)c1,Training,1,1,64,0.4083069985344587,78.39,44.06080000000001,3.134300249949543,311.5198400095355,168.152,1.1856
+5440,5448,97-53-0,Oc1ccc(cc1(OC))CC=C,Training,0,0,64,0.6932796632293877,29.46,48.559800000000024,2.9595595472247798,279.16711032401867,164.20399999999998,2.1292999999999997
+5441,5449,97534-21-9,O=C(Nc1ccccc1)C2C(=O)NC(NC2(=O))=S,Training,0,0,92,0.5079843621993272,87.30000000000001,67.44510000000001,2.113806079139532,509.5947921589542,263.27799999999996,-0.2278000000000001
+5442,5450,97-54-1,Oc1ccc(C=CC)cc1(OC),Training,0,0,64,0.7269926580745424,29.46,49.36680000000003,3.0458289647057484,289.8900954855593,164.20399999999998,2.4339000000000004
+5443,5451,97546-74-2,O=C(NC(CO)C(O)CO)C1CC([N+](=O)C1(C)(C))(C)C,Training,0,0,116,0.49399896139743965,109.87,72.00150000000005,2.8521238382474685,394.2227541440186,289.35200000000003,-0.8272999999999988
+5444,5452,97-56-3,N(=Nc1ccccc1C)c2ccc(N)c(c2)C,Training,1,1,86,0.6008050688597392,50.739999999999995,70.94640000000003,2.262725897212121,559.1438223871523,225.295,4.301040000000002
+5445,5453,97576-08-4,O=[N+]([O-])c1ccc2ccc4c5C=CC(O)C(O)c5(cc3ccc1c2c34),Training,1,1,122,0.3145439536000152,83.60000000000001,96.80100000000002,2.016178266621387,1211.0899966672882,331.3270000000001,3.913300000000002
+5446,5454,97606-15-0,c2c3c1cscc1C4NC4(c3(cs2)),Training,1,1,64,0.6554849418584517,21.94,56.24970000000002,2.1302838621203626,438.3360162491804,205.307,3.175600000000001
+5447,5455,97629-28-2,O=[N+]([O-])c1cc(N)c(c(c1(N))C)C,Training,1,1,70,0.3883089581491963,95.17999999999999,51.3952,3.4973813605379926,374.1421555222324,181.195,1.37604
+5448,5456,97629-64-6,O=[N+]([O-])c1c(N)cc(c(N)c1C)C,Training,0,1,70,0.38830895814919625,95.17999999999999,51.39520000000001,3.528354265248704,374.1421555222324,181.19499999999996,1.37604
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+5542,5550,99240-67-2,O=C(Oc2c(ccc3c1ccccc1Cc23)NC(=O)C)c4ccccc4,Training,0,0,128,0.44199880959573634,55.4,100.3882,1.7868850313763827,1009.1508757234241,343.38200000000006,4.435400000000003
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+5556,5564,99520-59-9,Oc1ccc2c(c1)c3ccc4ccc5cccc6cc2c3c4c56,Training,1,1,106,0.34357180365460827,20.23,96.24080000000004,1.9825532540080792,1263.8604219801678,292.3370000000001,5.937000000000003
+5557,5565,99520-64-6,O6C7c5cccc4cc3c1ccccc1c2ccc(c(c23)c45)C67,Training,1,1,106,0.26072668485775147,12.53,92.45100000000004,1.8441344357241003,1201.7014559940797,292.33700000000005,5.7664000000000035
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+5559,5567,99520-67-9,Oc2c6cccc5ccc4ccc3c1ccccc1c2c3c4c56,Training,0,1,106,0.34357180365460827,20.23,96.24080000000004,2.0597376645906675,1263.860421980168,292.33700000000005,5.937000000000003
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+5573,5581,99601-30-6,n2cc(nc3ccc1c(nc(N)n1CC)c23)C,Training,1,1,86,0.6888271777253475,69.62,67.65240000000001,2.4812676961011944,713.5562795950137,227.27099999999993,1.8900199999999998
+5574,5582,99601-31-7,n1cc(nc3c1ccc2c3(nc(N)n2CC))C,Training,1,1,86,0.6888271777253475,69.62,67.65240000000001,2.508575397774682,713.5562795950137,227.27099999999993,1.8900199999999998
+5575,5583,99601-32-8,n1cccc3c1cc(c2c3(nc(N)n2CC))C,Training,1,1,86,0.6931858117517485,56.73,69.85740000000001,2.5834411376932347,712.0797537422704,226.28299999999996,2.4950200000000002
+5576,5584,99601-33-9,n1cccc3c1ccc2c3(nc(N)n2CC),Training,1,1,80,0.6722701894379244,56.73,65.1204,2.523402695771685,669.141155629221,212.25599999999994,2.1866000000000003
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+5578,5586,99-65-0,O=[N+]([O-])c1cccc(c1)[N+](=O)[O-],Training,1,1,62,0.49411926294389913,86.28,39.75080000000001,3.121805775248301,306.8248996548373,168.10799999999995,1.503
+5579,5587,99675-03-3,O=C(OC(C)C)c1ccccc1(OP(OC)(NC(C)C)=S),Training,0,0,118,0.609509478481626,56.790000000000006,87.18720000000006,3.0275006654767482,533.4602218965406,331.374,3.499500000000002
+5580,5588,99-73-0,O=C(c1ccc(cc1)Br)CBr,Training,0,0,58,0.5999490968087596,17.07,52.266500000000015,2.8953480359887576,253.2994975838911,277.943,3.026700000000001
+5581,5589,99-75-2,O=C(OC)c1ccc(cc1)C,Training,0,0,58,0.5702367575745928,26.3,42.518500000000024,2.8953480359887567,248.77017257091026,150.17699999999996,1.78162
+5582,5590,99-76-3,O=C(OC)c1ccc(O)cc1,Training,0,0,58,0.6143884490200855,46.53,39.446300000000015,2.8953480359887567,250.5446100817276,152.14899999999997,1.1788
+5583,5591,99766-47-9,O=Nc1c(cccc1CC)CC,Training,1,1,64,0.6289199533960564,29.43,50.653000000000034,3.213974574884701,258.91711032401867,163.21999999999994,3.2093000000000016
+5584,5592,99803-60-8,O=Nc1ccc(OP(OC)(OC)=S)cc1C,Training,1,1,88,0.600940077318444,57.120000000000005,65.56500000000003,2.946378960928082,429.51720390426783,261.239,3.2890200000000016
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+5588,5596,99-96-7,O=C(O)c1ccc(O)cc1,Training,0,0,52,0.6102585058580265,57.53,35.066100000000006,3.003400684579818,237.53306142431703,138.12199999999999,1.0903999999999998
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+5591,5599,99-99-0,O=[N+]([O-])c1ccc(cc1)C,Training,0,0,52,0.43791186569144913,43.14,37.83340000000001,3.003400684579817,240.28794892648057,137.13799999999998,1.90322
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+5611,5619,17620-38-1,O=C1N(C(=O)C2CC=CCC12)CC3OC3,Training,1,0,80,0.37242745498841484,49.910000000000004,51.81400000000003,1.8000324496193028,319.7421968319772,207.22899999999993,0.33640000000000003
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+5613,5621,25187-08-0,O=C(c1ccc(cc1Cl)Cl)c2ccc(cc2Cl)Cl,Training,1,0,92,0.6648893161587273,17.07,76.35650000000001,2.4778713637686196,568.8834635498207,320.00199999999995,5.531200000000002
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+5618,5626,89110-96-3,O=C1C(CCCC1(Cl)Cl)(C(C(C)C)Cl)Cl,Training,1,0,88,0.6985425250181329,17.07,66.35800000000003,2.9714955187067895,264.1480031020815,292.033,4.154300000000003
+5619,5627,102405-96-9,O=[N+]([O-])c2cc3oc(nc3(cc2(Oc1ccc(cc1)C(C)(C)CC(C)(C)C)))C(C)(C)C,Training,1,1,166,0.31212004078001254,78.4,122.97740000000007,1.932228578262592,1097.4829106134055,424.5410000000003,7.539600000000006
+5620,5628,110882-70-7,O=C(Nc1nc(c(cc1)[N+](=O)[O-])Cl)C,Training,1,1,74,0.4613124778277186,85.13,50.20510000000001,3.000632319118686,393.7664516165355,215.59599999999998,1.6016
+5621,5629,2106-49-2,O=[N+]([O-])c1cccc(c1(F))Cl,Training,1,1,58,0.4859048548225686,43.14,38.06440000000001,3.273580821537543,302.6337992264623,175.54599999999996,2.3873000000000006
+5622,5630,84870-65-5,N#Cc2cc(cc(C#N)c2(N=Nc1ccc(cc1C)N(CC)CC))[N+](=O)[O-],Training,1,1,136,0.4107392812662271,118.68,101.44240000000005,2.454800498040971,945.6651133591263,362.39300000000014,4.908180000000004
+5623,5631,102405-54-9,O=[N+]([O-])c1cc2oc(nc2(cc1Cl))C(C)(C)C,Training,1,1,90,0.5748219530930371,69.17,64.37340000000002,2.666150348052462,598.5177300470274,254.67299999999997,3.6869000000000014
+5624,5632,86603-13-6,O=S(=O)(O)OC(c1ccc(cc1)Cl)C(N)C,Training,1,0,90,0.8063850804546919,89.62,60.47600000000003,2.986982471382455,443.08171912192716,265.718,1.5477
+5625,5633,134964-55-9,Oc2ccccc2(C=Cc1cccc(OC)c1),Training,1,1,86,0.8105590581506829,29.46,70.02880000000003,2.2287011445166005,529.9499584541678,226.27499999999998,3.571200000000003
+5626,5634,2011-66-7,O=C(c1cc(ccc1(N))[N+](=O)[O-])c2ccccc2Cl,Training,1,1,96,0.4038738252493739,86.23,72.39330000000001,2.5279515389275438,670.6879473056839,276.679,3.061400000000001
+5627,5635,14345-84-7,Nc1c(cc(cc1Br)Br)C(N)=S,Training,1,1,64,0.6186268987636125,52.04,62.141799999999996,3.3738590108748685,338.423415200434,310.014,2.4280000000000004
+5628,5636,14346-17-9,n2c1c(cc(cc1Br)Br)c(N)s2,Training,1,1,62,0.8099020490192034,38.91,59.4324,2.9242062797931907,438.14415089128414,307.99800000000005,3.4035
+5629,5637,1586-88-5,C(=C(CCl)[Si](Cl)(Cl)Cl)CCl,Training,1,1,60,0.4122021423604868,0.0,52.83600000000001,4.211614145716065,126.09986547010988,258.43499999999995,3.584900000000001
+5630,5638,400-70-4,O=[N+]([O-])c1cc(c(cc1Cl)Cl)C(F)(F)F,Training,1,0,82,0.566832509048916,43.14,48.1184,3.431869725433556,419.4317037635926,259.99799999999993,3.9204
+5631,5639,14663-23-1,O=C3N=C([O-])N(N=Cc1oc(cc1)c2ccc(cc2)[N+](=O)[O-])C3,Training,1,1,116,0.46564954018463545,124.37,77.54040000000002,1.7411385575264515,821.9481015760782,313.2490000000001,0.7472000000000001
+5632,5640,84080-70-6,O=C(O)C(=NOCC(=O)OC)C(=O)CCl,Training,1,1,84,0.2180803053760533,102.26000000000002,48.76580000000001,4.37671620372187,299.8555352119088,237.59499999999997,-0.5754999999999999
+5633,5641,7783-54-2,FN(F)F,Training,1,Non Predicted,26,0.38398021731644777,3.24,5.163,2.3237900077244498,8.0,71.001,0.9419000000000001
+5634,5642,7195-44-0,O=C(OCC1OC1)c2ccc(cc2)C(=O)OCC3OC3,Training,1,1,106,0.5654839300991585,77.66,66.48700000000004,1.5163890246855238,453.9003429116071,278.26000000000005,0.7977999999999998
+5635,5643,93641-38-4,O=C(C=Cc1oc2ccccc2(c1))NNC(=O)C(Cl)(Cl)Cl,Training,1,1,110,0.49828953223236655,71.34,81.8234,1.942789041041518,670.9945515444826,347.58500000000004,2.9636000000000005
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+5637,5645,68938-65-8,O=C(OCCN(c3ccc(N=Nc2nc1ccc(cc1s2)[N+](=O)[O-])cc3)CC)c4ccccc4,Training,1,1,172,0.12149132113112077,110.29000000000002,131.5039,1.3552233279627877,1322.4681368402303,475.5300000000002,6.303200000000005
+5638,5646,87269-99-6,O=C(O)C(NC(C(=O)OCC)CC(=O)c1ccccc1)C,Training,1,0,114,0.5533852504800594,92.70000000000002,76.04400000000004,2.789144942902765,500.04525782102604,293.31899999999996,1.253799999999999
+5639,5647,64265-57-2,O=C(OCC(COC(=O)CCN1CC1C)(COC(=O)CCN2CC2C)CC)CCN3CC3C,Training,1,1,188,0.18928079794584857,87.93,122.55700000000009,1.4557086171905858,613.3441763087233,467.60700000000037,1.295000000000002
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+5641,5649,15121-89-8,O=C(OCC)C=CC(=O)c1ccccc1,Training,1,1,78,0.4276749817332226,43.370000000000005,56.54550000000003,2.6025601383454826,365.7134385940965,204.225,1.9886
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+5646,5654,56970-78-6,O=C(O)C(C)CBr,Training,1,1,42,0.6248967711303387,37.3,30.59379999999999,3.3434170589539596,72.09004635215048,167.002,1.102
+5647,5655,350-30-1,O=[N+]([O-])c1ccc(F)c(c1)Cl,Training,1,1,58,0.4859048548225686,43.14,38.06440000000001,3.1515496683060507,302.6337992264623,175.546,2.3873000000000006
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+5649,5657,52583-53-6,O=C(Nc2cc(ccc2(N=Nc1c(cc(cc1Br)[N+](=O)[O-])Br))N(CC)CC)C,Training,1,1,148,0.26541512130223205,100.2,116.97910000000006,2.444828358708617,906.427356645806,513.1900000000002,6.339800000000004
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+5652,5660,53814-79-2,O=C(OC1CCCCC1)c2cc(c3C(=O)c4ccccc4(C(=O)c3(c2(N))))[N+](=O)[O-],Training,1,1,148,0.31157015467512333,129.60000000000002,103.10430000000005,1.8491480192042413,1069.0812692141756,394.3830000000002,3.4419000000000013
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+5655,5663,676-83-5,CP(Cl)Cl,Training,1,Non Predicted,26,0.4269904798686815,0.0,24.549999999999994,2.3237900077244498,10.75488750216347,116.915,2.4057000000000004
+5656,5664,105076-77-5,O=C(Nc3cc(ccc3(N=Nc1c2cc(ccc2(ns1))[N+](=O)[O-]))N(CCOC)CCOC)C,Training,1,1,174,0.24342722714180817,131.55,127.16110000000006,1.9398621169587031,1157.2527897011366,472.5270000000003,4.677500000000005
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+5662,5670,3776-30-5,O=C1C(CCCC1(Cl)Cl)(Cl)Cl,Training,1,0,64,0.5902515308002967,17.07,47.73200000000002,2.8530194697565747,169.02130455739126,235.925,3.087200000000001
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+5664,5672,96662-24-7,N#CCCN(c2ccc(N=Nc1ccc(cc1)[N+](=O)[O-])cc2)Cc3ccccc3,Training,1,1,144,0.2726305304583207,94.89,111.4364,1.7054377862521248,1009.8232027194379,385.4270000000001,5.930480000000005
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+5666,5674,50893-53-3,O=C(OC(C)Cl)Cl,Training,1,0,42,0.41371480874344635,26.3,27.648999999999994,3.126006652390634,71.33515884998701,142.969,1.9466
+5667,5675,86813-46-9,O=Cc1cc(cc(c1)[N+](=O)[O-])N2CCNCC2,Training,1,1,90,0.47655420464283055,75.47999999999999,63.56660000000003,2.3413634221020545,441.5878382609177,235.24299999999994,0.8168999999999997
+5668,5676,37111-25-4,O=C(OCC1OC1)CC,Training,1,1,52,0.40814823712775716,38.83,30.989999999999984,1.9593576370486971,106.87060032410332,130.14299999999997,0.33840000000000015
+5669,5677,68400-36-2,O=[N+]([O-])c6ccc(N=Nc4c(N)c5c(O)c(N=Nc1ccc(cc1C)c3ccc(N=Nc2ccc(O)cc2)c(c3)C)c(cc5(cc4S(=O)(=O)[O-]))S(=O)(=O)[O-])cc6,Training,1,1,284,0.03858150374060466,298.18,201.03479999999973,1.3738656659316908,2882.2630822491756,794.7840000000003,9.079640000000003
+5670,5678,55506-46-2,O(c1ccccc1Cc2cccs2)CC3OC3,Training,1,1,88,0.7560536110678048,21.759999999999998,68.80200000000004,1.72242985423651,474.7272489831517,246.331,3.116500000000001
+5671,5679,27610-48-6,O(c2ccc3c(OCC1OC1)cccc3(c2))CC4OC4,Training,1,1,104,0.757333610765287,43.52,74.41800000000003,1.5369391089183118,616.9030237837436,272.30000000000007,2.3950000000000005
+5672,5680,96783-79-8,OOC(c1ccc2cc(ccc2(c1))C(OO)(C)C)(C)C,Training,1,0,108,0.6457503509463508,58.92,77.42760000000004,2.5025892243099315,561.6530237837436,276.332,4.289200000000003
+5673,5681,593-53-3,FC,Training,1,1,14,0.3673293108901918,0.0,7.032,1.0,2.0,34.033,0.5857
+5674,5682,19276-03-0,n1ccn(c1CCl)Cc2ccccc2,Training,1,1,72,0.7065049432459168,17.82,57.32800000000003,2.18799233987344,394.6796004438821,206.67600000000002,2.6702000000000004
+5675,5683,91520-02-4,O=C(Oc1c(OC)cccc1CC2OC2)C,Training,1,1,86,0.44044128060198573,48.06,57.747000000000035,2.280354227833688,396.00527574751527,222.23999999999995,1.5617999999999999
+5676,5684,1205-74-9,O=C(Nc1ccccc1)CC(=O)CBr,Training,1,0,74,0.6609277543392975,46.17,58.48970000000002,2.4580810994943985,324.15370011260666,256.09899999999993,1.9792
+5677,5685,102672-57-1,O=C(OC(C)I)OC1CCCCC1,Training,1,0,76,0.4458007564409409,35.53,57.921000000000035,2.1815090048769585,164.24274933154618,298.1200000000001,3.253300000000002
+5678,5686,115922-43-5,O=C(C(=NOC)C(=O)Cl)CBr,Training,1,1,62,0.23990977427793084,55.73,44.10500000000001,4.476280870669247,203.90421104845106,242.45599999999996,0.7181999999999998
+5679,5687,105757-36-6,Nc1ccc(cc1)C=Cc2cc[n+](cc2)C,Training,1,1,80,0.599058534823174,29.9,67.40040000000002,2.1451719267172638,433.6487204825034,211.288,2.2637
+5680,5688,77458-54-9,O=C(C=NNc1ccc(cc1)Cl)CCl,Training,1,0,74,0.4910921203033943,41.46,59.29370000000002,2.4942424352663575,335.1701202996886,231.082,2.5456000000000003
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+5684,5692,28418-86-2,O=C(c1ccc(c2ccccc12)C)C,Training,1,0,70,0.6209895171434741,17.07,58.689500000000024,2.883174852525854,497.56176431647657,184.23799999999997,3.3508200000000015
+5685,5693,354-64-3,FC(F)(F)C(F)(F)I,Training,1,0,50,0.3497577369924604,0.0,25.022,4.020391543176799,65.40990953421706,245.916,2.5765
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