Align README, header and installation guidance with earlyon v0.3.0

docs/evidence/CUDA_EVIDENCE.md

@@ -1,5 +1,18 @@
 # Bounded CUDA evidence run — 2026-07-22
 
+> **Erratum (2026-07-22, [#6](https://github.com/sohams25/earlyon/issues/6)).**
+> The "estimated backbone FLOPs fraction" figures in this run come from the
+> *low-confidence uniform fallback*, not the fvcore attribution: the reuse
+> detector false-positives on torchvision ResNet's shared in-block (zero-FLOP)
+> ReLU modules, so `resnet18_ee` was assigned uniform per-exit fractions
+> (0.333/0.667) with `FlopsEstimate.reliable=False` and a RuntimeWarning.
+> Under fvcore leaf-walk attribution the per-exit fractions are 0.547/0.774
+> and the run's average estimated fraction is **0.918, not the 0.880 recorded
+> below** — i.e. the run saved roughly **8%** of estimated backbone compute,
+> not 12%. Accuracy, latency, throughput and exit-distribution numbers are
+> measurements and are unaffected. Raw JSON is preserved as recorded, with an
+> `erratum` field appended.
+
 Machine-readable source: [`cuda_evidence.json`](cuda_evidence.json).
 Reproduce: `python scripts/evidence_run.py` (seed 42; ~10 min compute on the
 hardware below after the CIFAR-10 download).

docs/evidence/cuda_evidence.json

@@ -259,5 +259,14 @@
     "gpu": "NVIDIA GeForce RTX 4050 Laptop GPU",
     "earlyon": "0.2.0",
     "os": "Linux-6.8.0-106-generic-x86_64-with-glibc2.35"
+  },
+  "erratum_2026_07_22": {
+    "issue": "https://github.com/sohams25/earlyon/issues/6",
+    "affected_fields": [
+      "test.early_exit_estimated_flops_fraction",
+      "benchmark_real_input.*.avg_estimated_flops_fraction",
+      "benchmark_noise_input.*.avg_estimated_flops_fraction"
+    ],
+    "note": "estimated FLOPs fractions in this run derive from the low-confidence uniform fallback (reuse detector false-positive on torchvision ResNet's zero-FLOP shared in-block ReLU; FlopsEstimate.reliable=False). Under fvcore leaf-walk attribution the per-exit fractions are layer2=0.5474, layer3=0.7736 and the test-set average estimated fraction is 0.918 instead of the recorded 0.880 (~8% estimated saving, not 12%). Measured accuracy/latency/throughput/exit-distribution values are unaffected. Original recorded fields left unmodified."
   }
 }

docs/marketing/earlyon-reddit.md

@@ -1,3 +1,7 @@
+> NOTE (v0.3.0): this is archived v0.2-era launch copy. The numbers below
+> predate the v0.3 fair benchmark runner and are superseded by
+> docs/evidence/CUDA_EVIDENCE.md; do not reuse them.
+
 # r/MachineLearning launch draft
 
 Flair: [P] (Project). Post as text, not a link post; r/ML buries bare links.
@@ -34,7 +38,7 @@ model = resnet50_ee(num_classes=10, pretrained=True).eval()
 result = model(x, mode="inference")
 
 result.exit_taken        # which head fired (-1 = full network)
-result.computation_used  # fraction of FLOPs actually run
+result.estimated_backbone_flops_fraction  # estimated fraction of backbone FLOPs (not measured latency)
 result.confidence        # how sure it was when it left
 ```