diff --git a/models/scheme_b_last_model.joblib b/models/scheme_b_last_model.joblib
index 5791929..a92beb2 100644
Binary files a/models/scheme_b_last_model.joblib and b/models/scheme_b_last_model.joblib differ
diff --git a/models/scheme_b_scaler.joblib b/models/scheme_b_scaler.joblib
index 8313b4f..465dcce 100644
Binary files a/models/scheme_b_scaler.joblib and b/models/scheme_b_scaler.joblib differ
diff --git a/strategy/ai_strategy.py b/strategy/ai_strategy.py
index 78bd6c8..be4f0df 100644
--- a/strategy/ai_strategy.py
+++ b/strategy/ai_strategy.py
@@ -211,5 +211,11 @@ def get_live_signal(period: int = None, model_type: str = 'lightgbm',
         return 0
     X_scaled = scaler.transform(X_last)
     X_scaled_df = pd.DataFrame(X_scaled, columns=feature_cols, index=X_last.index)
-    pred = model.predict(X_scaled_df)
-    return int(pred[0])
+    proba = model.predict_proba(X_scaled_df)[0]  # (p0, p1, p2)
+    pred = model.predict(X_scaled_df)[0]
+    confidence_threshold = MC.get('confidence_threshold', 0.45)
+    logger.info(f"方案B 预测概率: 观望={proba[0]:.2f} 做多={proba[1]:.2f} 做空={proba[2]:.2f} -> {int(pred)}")
+    if proba.max() < confidence_threshold:
+        logger.info(f"置信度 {proba.max():.2f} < {confidence_threshold}，视为观望")
+        return 0
+    return int(pred)
diff --git a/四分之一，五分钟，反手条件充足.py b/四分之一，五分钟，反手条件充足.py
index 6675e5e..4d84f6d 100644
--- a/四分之一，五分钟，反手条件充足.py
+++ b/四分之一，五分钟，反手条件充足.py
@@ -705,6 +705,7 @@ class BitmartFuturesTransaction:
                     self.last_kline_time = current_15m_id
                     logger.info(f"进入新 15m K 线: {current_15m_id}")
                     raw = get_live_signal(period=15)
+                    logger.info(f"方案B 信号: {raw} (0=观望 1=做多 2=做空), 当前持仓: {self.start}")
                     if raw == 1:
                         if self.start == 0:
                             signal = ('long', current_price)