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Reviewer flagged 4 killer flaws: behaviour-policy logp mismatch on teacher rows (ratio pegs to clip from step 0), frac_clipped not ratio_mean is the saturation diagnostic, mixed-policy can produce gradient AWAY from hacking when teacher-half has zero adv variance, and probe_distill NLL normalizer is incomparable to train.py Dr.GRPO. User instruction reinforces: no mixed policy. Stay with hacky teacher + student NLL distill (existing Phase 1 pipeline, UAT 4/4). Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>