gbanyan ba2f97ac55 feat(04-02): implement QC checks for scoring results ...

- Add scipy>=1.14 dependency for MAD-based outlier detection
- Create quality_control.py with 4 QC functions
- compute_missing_data_rates: NULL rate detection with warn/error thresholds
- compute_distribution_stats: mean/median/std per layer with anomaly detection
- detect_outliers: MAD-based robust outlier detection (>3 MAD)
- run_qc_checks: orchestrator with composite score percentiles

2026-02-11 20:46:57 +08:00

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