Add honest Torch validation gate

tests/test_time_series.py

@@ -282,6 +282,28 @@ def test_time_series_forecaster_reads_torch_gru_artifact(make_settings, tmp_path
     assert forecast.probability_up > 0.5
 
 
+def test_time_series_forecaster_attaches_quality_gate(make_settings, tmp_path) -> None:
+    artifact_path = tmp_path / "lstm_forecaster.json"
+    _write_torch_gru_artifact(artifact_path, head_bias=0.2)
+    (tmp_path / "torch_threshold_calibration.json").write_text(
+        json.dumps({"validation": {"status": "fail", "passed": False, "checks": []}}),
+        encoding="utf-8",
+    )
+    settings = make_settings(
+        tmp_path,
+        time_series_min_candles=80,
+        time_series_lstm_enabled=True,
+        time_series_lstm_model_path=artifact_path,
+    )
+    returns = [0.00015 if index % 4 else -0.00005 for index in range(140)]
+
+    forecast = TimeSeriesForecaster(settings).forecast(_candles_from_returns(returns), symbol="BTCUSDT")
+
+    assert forecast.usable is True
+    assert forecast.quality_gate_passed is False
+    assert forecast.quality_gate["status"] == "fail"
+
+
 def test_time_series_forecaster_reads_multifeature_direct_horizon_artifact(make_settings, tmp_path) -> None:
     artifact_path = tmp_path / "lstm_forecaster.json"
     _write_multifeature_torch_gru_artifact(artifact_path, head_bias=0.2)