Update src/leaderboard.py

src/leaderboard.py

@@ -352,6 +352,11 @@ def get_track_leaderboard(
     track_quality_col = f"{track}_{metric}"
     track_adequate_col = f"{track}_adequate"
     
+    # Ensure columns exist
+    if track_quality_col not in df.columns or track_adequate_col not in df.columns:
+        print(f"Warning: Missing columns for track {track}")
+        return pd.DataFrame()
+    
     # Filter by adequacy
     if min_adequacy > 0:
         adequacy_mask = df["scientific_adequacy_score"] >= min_adequacy
@@ -361,8 +366,12 @@ def get_track_leaderboard(
     if category_filter != "all":
         df = df[df["model_category"] == category_filter]
     
-    # Filter to models that have this track
-    valid_mask = (df[track_quality_col] > 0) & df[track_adequate_col]
+    # Filter to models that have this track - fix boolean operation
+    # Convert to proper boolean and handle NaN values
+    quality_mask = pd.to_numeric(df[track_quality_col], errors='coerce') > 0
+    adequate_mask = df[track_adequate_col].fillna(False).astype(bool)
+    
+    valid_mask = quality_mask & adequate_mask
     df = df[valid_mask]
     
     if df.empty: