Learning loop — bounded recursive evidence improvement.

A discovery system that improves itself — but never its own authority.

The returned lab result, failed proof, reviewer correction, or eval regression becomes a typed improvement proposal. DiscoveryLab can improve ranking, retrieval, mechanism templates, assay selection, and evals — but promotion remains eval-gated and human-reviewed.