Self-Evolving Hierarchical Trust Calibration for RBP-RNA Affinity Ranking

Ranking RNA-binding protein (RBP)–RNA pairs by binding affinity is a foundational step toward characterizing post-transcriptional regulatory specificity, yet it remains difficult because the available computational evidence is heterogeneous, noisy, and context-dependent. Sequence-based predictors, physics-based energy functions, and structure-confidence metrics each supply useful but incomplete signals whose raw scores are not comparable across pairs. Conventional pipelines compound this by optimizing a single global objective without revisiting the ranking errors they produce, so recurrent failure patterns are discarded rather than used to refine subsequent calibration. The central challenge is therefore not to collect more scores, but to decide how much to trust each one, and when. We introduce BindGauge, a self-evolving agent that represents its knowledge as a compact hierarchy of interpretable importance weights over tools and over metrics within each tool, and that aggregates calibrated evidence through multi-round residual deliberation with cross-tool interaction terms. To make calibration adaptive, BindGauge maintains a Ranking Experience Memory that records past ranking outcomes, diagnoses recurrent failure signatures, and distills per-metric reliability profiles. This closed loop, separated from standard parameter training, enables BindGauge to evolve from a uniform aggregator into a task-specialized ranker while preserving full interpretability. With 145 interpretable scalars, BindGauge attains Spearman ρ = 0.832 on PRAB and 0.317 on KD on two homology-controlled benchmarks, against 0.500 (Random Forest) and 0.216 (SVM) for the strongest learned baselines on each, and it exposes per-round tool weights and failure-signature clusters that render each ranking decision auditable. Both test splits are small, so we report bootstrap intervals alongside point estimates. Our code is available at https://anonymous.4open.science/r/BindGauge-4F71/.