ResultPilot iteration 3: K=256-scenario corpus, fresh held-out origins, full training

With K=256 aligned scenarios the label-stability floor passed decisively (decisive-root split-half Spearman 0.818, unconditioned 0.638, both >= 0.5), so for the first time in this line the ranking target is stable enough to certify a verdict. The verdict is a valid negative for the direct-play configuration: the distributional afterstate ranker trailed exact fair D4 on every preregistered comparison in both fresh held-out half-folds (pooled top-1 0.424 vs 0.499; pairwise 0.685 vs 0.737; regret 0.241 vs 0.178). On the 411 decisive roots (spread > 20k) the gap narrowed but persisted (top-1 0.526 vs 0.584; regret 0.082 vs 0.064). The model clearly beat its D1 continuation teacher (top-1 0.424 vs 0.319) and its quantile head is calibrated (0.864 coverage). Conclusion: a compact action-free afterstate network trained on successor-closed H40 D1-continuation labels is a viable, calibrated long-horizon evaluator, but it is NOT a viable direct replacement for 4-ply expectimax; any future use must be as a companion signal inside search, and the same ranking gate applies. No gameplay tier was opened.