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@@ -36,6 +36,11 @@ held-out accuracy by at least 2 percentage points over norm-matched raw feedback
traffic level, without harming the no-traffic setting by more than 0.5 points. The predictor must
remove measurable soma-predictable traffic while retaining causal teaching alignment.
+The validation-only timescale screen froze `eta_P=0.05` and 200 neutral warmup steps by the highest
+mean last-epoch accuracy across top-down traffic scales 0.2 and 0.5 (and the best worst-scale
+endpoint). C1 must use this choice without further test-set tuning. Traffic projection seeds remain
+separate from model/data seeds and must be recorded explicitly.
+
### C2. SDIL scales when depth is useful
Flattened CIFAR is retained as a preservation result, not as evidence that added depth is used.