訓練時期干預在匹配驗證損失下達到 63.4% 盲測配對人類偏好（1.2B 參數，320 項判斷，p = 1.98 × 10⁻⁵）[R]

TL;DR. I ran a blind A/B preference evaluation between two 1.2B-parameter LMs trained on identical data (same order, same seed, 30K steps / 3.9B tokens) - one with a Predictive-Coding-inspired precision-weighted gain function plus per-layer divergence-scaled gradients, one with standard cross-entropy. Smoothed val loss between the two is statistically indistinguishable (0.004-nat difference, well inside step-to-step noise). Ten judges (seven humans, three foundation models across Anthropic / Ope