fix: honor explicit calibration horizon

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_horizon,
     _calibration_symbols,
     _choose_recommendation,
     _full_backtest,
@@ -78,6 +79,14 @@ def test_calibration_symbols_reject_malformed_artifact_symbols() -> None:
     assert _calibration_symbols("", (), {"symbols": []}) == []
 
 
+def test_explicit_calibration_horizon_selects_existing_multi_horizon_output() -> None:
+    entry = {"target_horizon": 12, "target_horizons": [3, 6, 12, 24]}
+
+    assert _calibration_horizon(entry, 24, explicit=True) == 24
+    assert _calibration_horizon(entry, 20, explicit=True) == 24
+    assert _calibration_horizon(entry, 24, explicit=False) == 12
+
+
 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)],