hot fix, excluding a disicpline

app.py

@@ -72,6 +72,8 @@ DISCIPLINE_MODEL_PATH = MODELS_DIR / "discipline_classifier_gemma_20260130_14084
 CONCEPT_MODEL_PATH = MODELS_DIR / "concept_conditioned_gemma_20260130_140842.pt"
 EMBEDDING_MODEL_NAME = "google/embeddinggemma-300m"
 
+EXCLUDED_DISCIPLINES = {"Quantum Physics"}
+
 # ---------------------------------------------------------------------------
 # Globals (loaded once at startup)
 # ---------------------------------------------------------------------------
@@ -164,12 +166,18 @@ def predict(title: str, abstract: str, threshold: float, top_k: int):
         conc_logits = concept_model(emb_tensor, disc_probs_tensor)
         conc_probs = torch.sigmoid(conc_logits).cpu().numpy()[0]
 
-    # Format discipline results
+    # Format discipline results (skip excluded labels)
     disc_order = np.argsort(disc_probs)[::-1]
     disc_lines = []
-    for rank, idx in enumerate(disc_order[:top_k], 1):
-        prob = disc_probs[idx]
+    rank = 0
+    for idx in disc_order:
         label = discipline_labels[idx].get("label", f"Discipline_{idx}")
+        if label in EXCLUDED_DISCIPLINES:
+            continue
+        rank += 1
+        if rank > top_k:
+            break
+        prob = disc_probs[idx]
         marker = "**" if prob >= threshold else ""
         disc_lines.append(f"{rank}. {marker}{label}{marker}  —  {prob:.1%}")