sinhakrishnendu/babappaomega: BABAPPAΩ v1.3.0

BABAPPAΩ v1.3.0 Tree-Conditional Calibration & Gene-Level Identifiability This release introduces tree-conditional Monte Carlo calibration and the Gene-Level Episodic Identifiability Index (EII), strengthening BABAPPAΩ as a calibrated diagnostic framework for episodic branch–site structure. New Features • Tree-aware neutral simulation preserving topology, branch lengths, and alignment length • Gene-level dispersion statistics: - Observed variance - Neutral expected variance - Dispersion ratio (obs/neutral) - Standardized EII_z - Empirical Monte Carlo p-value • Enhanced interpretation report including calibrated gene-level summary • Strict exclusion of internal branches in reporting Conceptual Clarification • EII measures statistical resolvability, not adaptive substitution • Outputs are not dN/dS, not likelihood ratios, not hypothesis tests • Logit-scale inference preserved for quantitative benchmarking • Calibration prevents inflation under tree-aware neutrality Stability • Frozen reference model (no retraining) • Deterministic reproducibility • Backward compatible CLI • Calibration is optional (--tree-calibration) Upgrade pip install --upgrade babappaomega