signal_log: weight-research data points, scan_outcomes forward labels, watch provenance
New additive columns on every logged scan: bar_ts (primary closed-bar label, indexed with timeframe), engine_fingerprint (hash of the scoring config incl. the regime weight table in force - SignalAggregator.engine_config_fingerprint, twin of the gate fingerprint), code_version (short git SHA), penalty_tags_json / penalty_total / momentum_fading / exhaustion_count, and post-hoc watch_level / watch_kinds / watch_line written by violent_watch.attach_watch via signal_log.update_watch. Each indicators_json entry now also carries eff_weight (base weight x regime multiplier, the weight the composite actually used) and wscore. engine: IndicatorSignal.effective_weight / weighted_score are stamped inside _compute_composite (record-keeping only); regime_weight_table(config) is the single source of truth for the multiplier table (override honoured). Composite output byte-identical (120-report hash proof). New table scan_outcomes: model-free forward moves per scan (fwd_1h/4h/24h in $ and ATRs, mfe/mae over 24h, burst_1h, bars_used, complete) measured on the stored candle stream with the advisory model's continuity rule; labelled opportunistically at the end of log() (time-boxed, throttled, idempotent) - no daemon; scripts/label_scan_outcomes.py drives the backlog (--dry-run is read-only). analyze_signal_log --scan-outcomes: forward move + hit rate by TF x signal/grade with a NEUTRAL baseline and burst rate by watch level. Readers dedup by the first row per (timeframe, bar_ts). Module 31 (10 tests). Suite: 463 passed. Backtester untouched (test-locked). Claude-Session: https://claude.ai/code/session_01RWV2yLt3YXHHGVYHSQU2EE
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Harwinder Sekhon