add track-record reset; drop dead distance_penalty_factor knob

Track Record: new "Reset" action (POST /admin/track-record/reset) deletes all
trade setups so stats start fresh after material scoring/setup changes — live
setups regenerate on the next scan. Guarded by a confirm dialog.

Recommendation config: remove distance_penalty_factor, which was exposed in the
admin UI but consumed nowhere (the touch-probability model superseded it). A
knob that silently does nothing is worse than no knob. Remaining defaults are
left as-is — they're reasonable, and the honest way to tune them is backtesting
against accumulated outcomes, not invented "researched" numbers.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/services/admin_service.py

@@ -23,7 +23,6 @@ RECOMMENDATION_CONFIG_DEFAULTS: dict[str, float] = {
     "recommendation_confidence_diff_threshold": 20.0,
     "recommendation_signal_alignment_weight": 0.15,
     "recommendation_sr_strength_weight": 0.20,
-    "recommendation_distance_penalty_factor": 0.10,
     "recommendation_momentum_technical_divergence_threshold": 30.0,
     "recommendation_fundamental_technical_divergence_threshold": 40.0,
 }
@@ -236,7 +235,6 @@ async def get_recommendation_config(db: AsyncSession) -> dict[str, float]:
         "confidence_diff_threshold": config["recommendation_confidence_diff_threshold"],
         "signal_alignment_weight": config["recommendation_signal_alignment_weight"],
         "sr_strength_weight": config["recommendation_sr_strength_weight"],
-        "distance_penalty_factor": config["recommendation_distance_penalty_factor"],
         "momentum_technical_divergence_threshold": config["recommendation_momentum_technical_divergence_threshold"],
         "fundamental_technical_divergence_threshold": config["recommendation_fundamental_technical_divergence_threshold"],
     }
@@ -309,6 +307,19 @@ async def cleanup_data(db: AsyncSession, older_than_days: int) -> dict[str, int]
     return counts
 
 
+async def reset_trade_setups(db: AsyncSession) -> dict[str, int]:
+    """Delete all trade setups, wiping the track record for a fresh start.
+
+    Stats are derived from evaluated trade setups, so this resets the Track
+    Record to zero. Live setups regenerate on the next R:R scan. Used after
+    material changes to scoring / setup generation, when historical outcomes no
+    longer reflect current logic.
+    """
+    result = await db.execute(delete(TradeSetup))
+    await db.commit()
+    return {"trade_setups": result.rowcount}  # type: ignore[attr-defined]
+
+
 async def get_pipeline_readiness(db: AsyncSession) -> list[dict]:
     """Return per-ticker readiness snapshot for ingestion/scoring/scanner pipeline."""
     tickers_result = await db.execute(select(Ticker).order_by(Ticker.symbol.asc()))

app/services/recommendation_service.py

@@ -22,7 +22,6 @@ DEFAULT_RECOMMENDATION_CONFIG: dict[str, float] = {
     "recommendation_confidence_diff_threshold": 20.0,
     "recommendation_signal_alignment_weight": 0.15,
     "recommendation_sr_strength_weight": 0.20,
-    "recommendation_distance_penalty_factor": 0.10,
     "recommendation_momentum_technical_divergence_threshold": 30.0,
     "recommendation_fundamental_technical_divergence_threshold": 40.0,
 }