Fix Level 2 thresholds: remove word_count restrictions for better human text detection

app.py

@@ -544,31 +544,31 @@ def predict(text: str) -> Dict[str, Any]:
     ai_prob = probs[0][1].item()
     label = LABELS[pred_class]
     
-    # ===== CASUAL HUMAN TEXT CORRECTION =====
-    # If RoBERTa says AI, check if Level 2 strongly indicates casual human text
+    # ===== HUMAN TEXT CORRECTION =====
+    # If RoBERTa says AI, check if Level 2 indicates human text
     # Level 2 returns AI score (0.0 = definitely human, 1.0 = definitely AI)
-    # AI text typically has Level 2 scores > 0.90, human text < 0.70
+    # AI text typically has Level 2 scores > 0.85, human text < 0.60
     if pred_class == 1:  # RoBERTa says AI
         level2 = Level2_StatisticalFingerprinting()
         level2_score = level2.detect(text)
         word_count = len(text.split())
         
         # Override when Level 2 indicates human (score < 0.70)
-        # AI text has scores > 0.90, so this won't trigger for AI
-        if level2_score < 0.40:
-            # Very strong casual human indicators - definitely human
+        # AI text has scores > 0.85, so this won't trigger for AI
+        if level2_score < 0.35:
+            # Very strong human indicators - definitely human
             label = "Human-Written"
             human_prob = max(human_prob, 1 - level2_score)
             ai_prob = min(ai_prob, level2_score)
             confidence = human_prob
-        elif level2_score < 0.60 and word_count < 35:
-            # Strong casual indicators in short/medium text
+        elif level2_score < 0.55:
+            # Strong human indicators - likely human
             label = "Human-Written"
-            human_prob = max(human_prob, 0.70)
-            ai_prob = min(ai_prob, 0.30)
+            human_prob = max(human_prob, 0.75)
+            ai_prob = min(ai_prob, 0.25)
             confidence = human_prob
-        elif level2_score < 0.70 and word_count < 20:
-            # Moderate casual indicators in short text
+        elif level2_score < 0.70:
+            # Moderate human indicators - probably human
             label = "Human-Written"
             human_prob = max(human_prob, 0.65)
             ai_prob = min(ai_prob, 0.35)