Add Phase 10A.8: freeze-with-decay confirms stale aux is main freeze failure cause;

alpha sweep shows perlayer_vector at alpha=0.75 matches full network

10A.8A: freeze_decay_to_000 recovers to 28.5% (vs 14.6% fixed freeze) — stale
high-weight aux is the primary cause of freeze crashes. But 28.5% < DFA 31.2%
confirms continuous trainability adds ~2.7% independent value.

10A.8B: Both perlayer_vector and random_trainable optimal at alpha=0.75.
perlayer_vector +1.1% vs random_trainable +0.8% — per-layer vector is
the minimal sufficient scaffold, no network needed.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

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