Predictive Models of Adaptive Repair and Entropy Reversal: RYE Meta-Learning Validation

Reparodynamics extends its First Law by examining predictive and meta-learning behavior within adaptive repair systems. Using logged Grok simulations, coherence remains > 0.95 across mixed algorithmic, mechanical, and biological streams, with RYE ≈ 0.99 and entropy reduction ≈ 19 %. Results confirm the emergence of foresight, power-law variance (~1.2), and cross-domain stability beyond 600 s. These findings demonstrate an empirical link between adaptive repair efficiency and entropy reversal thresholds.