Generated 2026-05-15 · Status: in_progress
Diagnostic stack is complete. Closeout means promoting selected diagnostics to either (a) reviewer-actionable state or (b) decommissioning, plus one cycle of manual review. No production scoring formulas were changed in this batch.
Purpose: Show how the top of the board would shift under a transparent activity overlay (liquidity / rel-vol / Pine accumulation / overextended). Now ships a top-25 entrants/drops section so the reviewer can spot promotion candidates without reading every row.
Promotion criteria: If the entrants list is consistently higher-quality than the current top-25 in manual review across at least 3 sessions, propose folding a small (≤±5%) version of the multiplier into production. Otherwise keep diagnostic-only.
Open report · CSV export · starter template
Purpose: Surface tickers where internal scoring disagrees with external benchmark sources; carry Pine and cool-off context; suggest keep / watchlist_only / ignore / needs_more_data per row. Now exports a CSV for offline review and a starter state template.
Promotion criteria: After one full review pass (state file no longer all-blank), measure: do reviewer 'ignore' decisions land on names that later confirm the internal view? If yes, keep diagnostic; if not, tune the gap thresholds in external_benchmark_review.py.
Open Pine report · Open cohort report
Purpose: Daily-OHLCV proxy of the Pine v6 gate stack; A/B cohort tracking of overextended_bb / clean_go forward returns.
Promotion criteria: Already production-quality as a gating overlay. Promotion is gated on the cool-off cohort showing a statistically meaningful spread over enough sessions (target: 20+ trading days).
Purpose: Per-ticker accumulation-style score built from Pine OHLCV metrics (rel-vol, MFI, RSI zone, bar strength, near 20d high, close location). Diagnostic only; surfaces top/weak accumulation names and overlap with Pine clean-go and activity-adjusted top-25.
Promotion criteria: Track agreement between top-25 accumulation list and the eventual reviewer-confirmed names from the disagreement queue. If 60%+ overlap on confirmed-keep decisions over a month, consider adding as a small weighted input to ai_score (would require explicit user signoff).
data/reports/disagreement_review_state_template.csv offline. For each severe row, decide keep / watchlist_only / ignore / needs_more_data.data/reports/disagreement_review_state.json (the canonical state) to record reviewed=true, decision, and notes for each reviewed entry. The next run will preserve those edits.ai_score for the next iteration, and which to leave purely diagnostic. No production scoring changes have been made in the closeout batch.update-rankings.yml. They will populate on the next scheduled run, or via a manual workflow_dispatch (user has explicitly chosen NOT to auto-trigger from this batch).git log --oneline -5.python 02_Code/Python/Reports/activity_adjusted_review.py && python 02_Code/Python/Reports/disagreement_queue_review.py && python 02_Code/Python/Reports/accumulation_signal_meter.py.tasks.json.