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app.py

@@ -816,9 +816,24 @@ def _build_grid_summary_figure(field=None, min_size=None, metric="silhouette_cos
         index="short_model", columns="threshold",
         values=metric, aggfunc="mean",
     )
-    # Sort rows so the best model appears at the top
-    best_per_row = pivot.max(axis=1) if higher_better else pivot.min(axis=1)
-    row_order = best_per_row.sort_values(ascending=higher_better).index.tolist()
+
+    # Always sort rows by silhouette score so all three heatmaps share the same model order
+    sil_src = METRICS_DF.dropna(subset=["silhouette_cosine"])
+    if field and field != "__global__":
+        sil_src = sil_src[sil_src["field"] == field]
+    if min_size and min_size != "__all__":
+        try:
+            sil_src = sil_src[sil_src["min_community_size"] == int(min_size)]
+        except (ValueError, TypeError):
+            pass
+    sil_agg = sil_src.groupby("model")["silhouette_cosine"].mean()
+    sil_agg.index = sil_agg.index.map(_short)
+    # Models present in pivot but missing from silhouette get ranked last
+    row_order = (
+        sil_agg.reindex(pivot.index, fill_value=0)
+        .sort_values(ascending=True)   # ascending=True → worst at bottom, best at top in Plotly
+        .index.tolist()
+    )
     pivot = pivot.loc[row_order]
 
     # Identify best cell and embed star in cell text