fix: calibrate dynamic model symbols

tests/test_calibrate_thresholds.py

@@ -8,6 +8,7 @@ from tools.calibrate_torch_thresholds import (
     _average_selected_predictions,
     _apply_platt_calibration,
     _build_torch_model,
+    _calibration_symbols,
     _choose_recommendation,
     _full_backtest,
     _fit_platt_calibration,
@@ -62,6 +63,21 @@ def _record(index: int, probability: float, future: float) -> ForecastRecord:
     )
 
 
+def test_calibration_symbols_follow_explicit_configured_artifact_precedence() -> None:
+    artifact = {"symbols": {"btcusdt": {}, "ethusdt": {}}}
+
+    assert _calibration_symbols("solusdt, xrpusdt", ("ADAUSDT",), artifact) == [
+        "SOLUSDT",
+        "XRPUSDT",
+    ]
+    assert _calibration_symbols("", ("ADAUSDT",), artifact) == ["ADAUSDT"]
+    assert _calibration_symbols("", (), artifact) == ["BTCUSDT", "ETHUSDT"]
+
+
+def test_calibration_symbols_reject_malformed_artifact_symbols() -> None:
+    assert _calibration_symbols("", (), {"symbols": []}) == []
+
+
 def test_calibration_does_not_fallback_to_too_few_trades() -> None:
     selected = _choose_recommendation(
         [_result(trades=1, average=2.0, total=2.0, profit_factor=999.0)],