feat: Phase G G7 — result-quality flag propagation into calibration engine

Makefile

@@ -1,4 +1,4 @@
-.PHONY: help demo test lint ci clean bench-leakage bench-multi-negatives bench-baseline bench-hidden-active bench-cluster-split bench-expert-ablation bench-expert-ablation-500 bench-selectivity bench-feature-decomp bench-gate bench-easy-baseline bench-charge-matched bench-order-dependent bench-precision-at-k bench-per-family bench-simulation-ablation bench-simulation-ablation-within-amp simulation-gate bench-strategy-compare regenerate-all generate phase3 pilot validate-scoring validate-scoring-phase3 validate-scoring-strict external-pilot pilot-confident presynth-qc gold-standard diversity synthesis-order novelty-broad external-consensus questionnaire gate-check ip-report benchmark-card wave0-5-gate-check wave0-5-novelty-audit wave0-5-novelty-audit-v2 wave0-5-panel wave0-5-evidence wave0-5-fill-external wave0-5b-generate wave0-5b-filter recalibration-engine recalibration-engine-dry-run validate-policy-version generate-synthetic-lab-results bump-policy-version generate-review-packet failed-candidate-report safe-publication-filter classify-negative-informativeness validate-rejection-events negative-result-dashboard calibration-audit calibration-audit-example calibration-overfit-check
+.PHONY: help demo test lint ci clean bench-leakage bench-multi-negatives bench-baseline bench-hidden-active bench-cluster-split bench-expert-ablation bench-expert-ablation-500 bench-selectivity bench-feature-decomp bench-gate bench-easy-baseline bench-charge-matched bench-order-dependent bench-precision-at-k bench-per-family bench-simulation-ablation bench-simulation-ablation-within-amp simulation-gate bench-strategy-compare regenerate-all generate phase3 pilot validate-scoring validate-scoring-phase3 validate-scoring-strict external-pilot pilot-confident presynth-qc gold-standard diversity synthesis-order novelty-broad external-consensus questionnaire gate-check ip-report benchmark-card wave0-5-gate-check wave0-5-novelty-audit wave0-5-novelty-audit-v2 wave0-5-panel wave0-5-evidence wave0-5-fill-external wave0-5b-generate wave0-5b-filter recalibration-engine recalibration-engine-dry-run validate-policy-version generate-synthetic-lab-results bump-policy-version generate-review-packet failed-candidate-report safe-publication-filter classify-negative-informativeness validate-rejection-events negative-result-dashboard calibration-audit calibration-audit-example calibration-overfit-check result-quality-filter
 
 PYTHON := $(shell [ -f .venv/bin/python ] && echo .venv/bin/python || echo python3)
 PYTEST  := $(shell [ -f .venv/bin/pytest ] && echo .venv/bin/pytest || echo pytest)
@@ -678,3 +678,10 @@ calibration-overfit-check:
 		--cohort-sizes 8,25,50 --model-params 10 --n-features 5 \
 		--out-json /tmp/overfit_check.json --out-md /tmp/overfit_check.md
 	@echo "Overfit check complete. See /tmp/overfit_check.json"
+
+result-quality-filter:
+	echo '[{"candidate_id":"AMP001","flags":[]},{"candidate_id":"AMP002","flags":["contamination"]},{"candidate_id":"AMP003","flags":["replicate_disagreement","borderline_threshold"]}]' > /tmp/rq_input.json
+	.venv/bin/openamp-foundry result-quality-filter \
+		--results-json /tmp/rq_input.json \
+		--out-json /tmp/rq_output.json --out-md /tmp/rq_output.md
+	@echo "Result quality filter done. See /tmp/rq_output.json"

docs/evidence/METRICS_CURRENT.md

@@ -5,7 +5,8 @@ Machine-readable snapshot: `outputs/metrics_snapshot.json` regenerated with `mak
 > **Purpose:** One authoritative table of current pipeline metrics. If any doc disagrees
 > with this file, this file wins. Updated whenever benchmark/benchmark config changes.
 >
-> **Last updated:** 2026-07-09 (Phase G G6 — calibration-overfit warning — v0.5.84)
+> **Last updated:** 2026-07-09 (Phase G G7 — result-quality flag propagation — v0.5.85)
+> **New in v0.5.85:** Result-quality flag propagation (G7) — `assess_result_quality()` and `filter_results_for_calibration()` propagate result-quality flags into the calibration engine. Candidates with contamination or assay interference are excluded; candidates with 2+ quality flags are excluded; candidates with 1 flag are included with caution; clean candidates are fully included. `QUALITY_FLAGS` dictionary (8 flags). `ResultQualityReport` dataclass. CLI (`openamp-foundry result-quality-filter`) accepts `--results-json`, `--out-json`, `--out-md`. JSON + Markdown output. Schema (`schemas/result_quality_report.schema.json`). `make result-quality-filter` target. 27 tests. 3022 total.
 > **New in v0.5.84:** Calibration-overfit warning (G6) — `check_cohort_overfit_risk()` and `run_overfit_check()` flag when a calibration cohort is too small relative to model parameters. Warns at three severity levels (critical/warning/caution/none). CLI (`openamp-foundry calibration-overfit-check`) accepts comma-separated cohort sizes, model params, n features. JSON + Markdown output. Schema (`schemas/calibration_overfit_check.schema.json`). `make calibration-overfit-check` target. 21 tests. 2995 total.
 > **New in v0.5.83:** Batch-2 selection rationale report (G5) — CLI (`openamp-foundry batch-rationale`) that generates a synthetic candidate pool, runs the batch-2 selector with configurable weights, and produces a per-candidate rationale report classifying each selected candidate into exploit / explore / diversity / combined roles. Reports weight configuration, role breakdown summary, per-candidate contributions (ensemble×weight, uncertainty×weight, diversity×weight), safety gate impact, and caveats. Schema (`schemas/batch_rationale_report.schema.json`). `make batch-rationale` target. 19 tests. 2974 total.
 > **New in v0.5.82:** Active-learning strategy comparison report (G4) — CLI (`openamp-foundry bench strategy-compare`) that compares 5 selection strategies (exploitation, exploration, diversity, combined, random) on the same synthetic pool with identical hidden active candidates. Each strategy runs multi-round recovery of hidden actives; the report ranks strategies by recall, compares the production selector vs pure strategies and random baseline, and produces structured JSON + Markdown output with caveats. Prevents one-selector bias by making strategy performance transparent. Schema (`schemas/active_learning_strategy_comparison.schema.json`). `make bench-strategy-compare` target. 18 tests. 2955 total.
@@ -76,7 +77,7 @@ Machine-readable snapshot: `outputs/metrics_snapshot.json` regenerated with `mak
 > **New in v0.5.31:** Added dipeptide-order features for sequence-order awareness. `dipeptide_order_score` achieves AUROC 0.7861 on AMP-vs-scrambled discrimination — the strongest order-dependent feature in the pipeline. Only 7/31 features survive scrambling (amphipathicity/helix-wheel + dipeptide). All composition features are purely position-independent (exactly 0.5000 AUROC on scrambled test).
 > **New in v0.5.30:** Easy baseline benchmark added — charge density alone (AUROC 0.8166) outperforms the full pipeline ensemble (0.7792) on AMP-vs-Swiss-Prot-decoy discrimination. Honest finding documented: expected because pipeline optimizes for safety, not raw discrimination.
 > **New in v0.5.29:** Expanded benchmark to 500 AMPs + 500 composition-matched decoys (n=1000). AUROC 0.7792 (CI₉₅: 0.7505–0.8065) confirms signal generalizes. Cluster-aware CI: 0.746–0.8102. Representative AUROC: 0.778. Standard benchmark (n=191) retained for backward comparison.
-> **Pipeline version:** v0.5.84 (G6)
+> **Pipeline version:** v0.5.85 (G7)
 > **Branch:** main
 
 ---

docs/research/ROADMAP.md

@@ -1,5 +1,55 @@
 # Roadmap
 
+## v0.5.85 — Loop 85: Phase G G7 — Result-Quality Flag Propagation into Calibration Engine ✓ (2026-07-09)
+
+`assess_result_quality()` and `filter_results_for_calibration()` propagate
+result-quality flags into the calibration engine. Low-quality outcomes cannot
+drive updates — garbage results must not update the scoring model.
+
+Changes:
+- `src/openamp_foundry/calibration/result_quality.py` (G7) — Core module with
+  `QUALITY_FLAGS` dictionary (8 standard flags), `EXCLUDED_FLAGS` set
+  (contamination, assay_interference), `ResultQualityReport` dataclass (7 fields:
+  candidate_id, flags, quality_level, can_drive_update, propagation_action,
+  explanation, dry_lab_only), `assess_result_quality()` applying multi-tier rules
+  (excluded flags → excluded, 2+ minor flags → low/excluded, 1 flag → acceptable,
+  0 flags → high), `filter_results_for_calibration()` grouping results into
+  included/included_with_caution/excluded with summary counts,
+  `write_result_quality_json()` and `write_result_quality_markdown()` for output.
+- `schemas/result_quality_report.schema.json` (G7) — JSON Schema Draft 07 for
+  per-candidate or aggregate result quality reports. Validates all 7 required
+  fields including flag enum constraint and dry_lab_only const=true.
+- `src/openamp_foundry/calibration/__init__.py` — Exports all result-quality
+  symbols.
+- `src/openamp_foundry/cli/commands/reports.py` — Added `_run_result_quality_filter()`
+  CLI handler with `--results-json`, `--out-json`, `--out-md` flags.
+- `src/openamp_foundry/cli/main.py` — Registered `result-quality-filter` subcommand
+  with all argument flags and dispatch to handler.
+- `Makefile` — Added `result-quality-filter` target with default example data writing
+  to `/tmp/rq_output.json` and `/tmp/rq_output.md`. Added to `.PHONY`.
+- `tests/calibration/test_result_quality.py` — 27 tests covering: high quality (no
+  flags), contamination excluded, assay_interference excluded, 2 minor flags excluded
+  (low quality), 1 minor flag include_with_caution, can_drive_update True/False for
+  all quality levels, dry_lab_only always True, unknown flag raises ValueError,
+  explanation non-empty, to_dict output, contamination+other flags still excluded,
+  assay_interference+other flags still excluded, filter_results_for_calibration
+  empty/summary counts/per-action grouping/can_drive_update_count, missing flags
+  handling, EXCLUDED_FLAGS set, QUALITY_FLAGS descriptions and count.
+- `docs/evidence/METRICS_CURRENT.md` — v0.5.85 G7 changelog. Test count: 3022.
+- `tests/test_test_count_regression.py` — baseline updated to 3022.
+
+Honest boundaries:
+- Quality assessment is a computational filter on structural and metadata criteria.
+  A "high quality" result does not confirm biological activity.
+- Flag-based classification uses a pre-defined rule set. Edge cases (e.g.,
+  borderline_threshold with ambiguous_activity) are treated the same as any
+  other 2-flag combination — excluded for caution.
+- Excluded results may still contain useful scientific information and should
+  remain available for expert review.
+- The `dry_lab_only=True` constraint is an attestation, not a technical proof.
+- All calibration decisions require qualified human review regardless of
+  result quality assessment.
+
 ## v0.5.84 — Loop 84: Phase G G6 — Calibration-Overfit Warning for Small Cohorts ✓ (2026-07-09)
 
 `check_cohort_overfit_risk()` and `run_overfit_check()` flag when a calibration

schemas/result_quality_report.schema.json

@@ -0,0 +1,63 @@
+{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "$id": "https://openamp.ai/schemas/result_quality_report.schema.json",
+  "title": "Result Quality Report",
+  "description": "Schema for a result quality assessment report. Dry-lab only — does not measure biological activity.",
+  "type": "object",
+  "properties": {
+    "candidate_id": {
+      "type": "string",
+      "description": "Identifier for the candidate peptide."
+    },
+    "flags": {
+      "type": "array",
+      "items": {
+        "type": "string",
+        "enum": [
+          "low_sample_quality",
+          "assay_interference",
+          "ambiguous_activity",
+          "contamination",
+          "protocol_deviation",
+          "borderline_threshold",
+          "replicate_disagreement",
+          "missing_negative_control"
+        ]
+      },
+      "description": "Quality flags assigned to this result."
+    },
+    "quality_level": {
+      "type": "string",
+      "enum": ["high", "acceptable", "low", "excluded"],
+      "description": "Overall quality assessment level."
+    },
+    "can_drive_update": {
+      "type": "boolean",
+      "description": "Whether this result may drive a calibration update."
+    },
+    "propagation_action": {
+      "type": "string",
+      "enum": ["include", "include_with_caution", "exclude"],
+      "description": "Propagation action for the calibration engine."
+    },
+    "explanation": {
+      "type": "string",
+      "description": "Human-readable explanation of the quality assessment."
+    },
+    "dry_lab_only": {
+      "type": "boolean",
+      "description": "Always true. This is a computational assessment, not biological proof.",
+      "const": true
+    }
+  },
+  "required": [
+    "candidate_id",
+    "flags",
+    "quality_level",
+    "can_drive_update",
+    "propagation_action",
+    "explanation",
+    "dry_lab_only"
+  ],
+  "additionalProperties": false
+}

src/openamp_foundry/calibration/__init__.py

@@ -74,6 +74,15 @@
     auto_increment_version,
 )
 
+from openamp_foundry.calibration.result_quality import (
+    QUALITY_FLAGS,
+    ResultQualityReport,
+    assess_result_quality,
+    filter_results_for_calibration,
+    write_result_quality_json,
+    write_result_quality_markdown,
+)
+
 __all__ = [
     # Constants
     "MIN_COHORT_SIZE",
@@ -120,4 +129,11 @@
     "run_overfit_check",
     "write_overfit_check_json",
     "write_overfit_check_markdown",
+    # Result quality
+    "QUALITY_FLAGS",
+    "ResultQualityReport",
+    "assess_result_quality",
+    "filter_results_for_calibration",
+    "write_result_quality_json",
+    "write_result_quality_markdown",
 ]