usher-exploring

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gbanyan f441e8c1ad feat(04-01): implement multi-evidence weighted scoring integration

- Create join_evidence_layers() with LEFT JOIN preserving NULLs from all 6 evidence tables
- Implement compute_composite_scores() with NULL-preserving weighted average (weighted_sum / available_weight)
- Add quality_flag classification based on evidence_count (sufficient/moderate/sparse/no_evidence)
- Include per-layer contribution columns for explainability
- Add persist_scored_genes() to save scored_genes table to DuckDB
- Log summary stats: coverage, mean/median scores, quality distribution, NULL rates

2026-02-11 20:41:44 +08:00

.planning

docs(04): create phase plan for scoring and integration

2026-02-11 20:31:55 +08:00

config

feat(01-01): create Python package scaffold with config system

2026-02-11 16:24:35 +08:00

src/usher_pipeline

feat(04-01): implement multi-evidence weighted scoring integration

2026-02-11 20:41:44 +08:00

tests

docs(03-04): complete subcellular localization evidence layer