tweak(confidence): blend modified prob with chunk majority; floor when unanimous

model_handler.py

@@ -569,7 +569,23 @@ class AIDetectionModelHandler:
             modified_prob = (overall_prob * 0.7) + (chunk_avg_prob * 0.3)
             
             final_prediction = 'Human' if modified_prob < 0.5 else 'AI'
-            confidence = abs(modified_prob - 0.5) * 2
+            # Base confidence from modified probability (0..1)
+            base_confidence = abs(modified_prob - 0.5) * 2
+
+            # For short texts/few chunks, incorporate chunk-majority evidence to avoid
+            # under-confident results when the label is clear but probability is near 0.5.
+            if total_chunks > 0:
+                majority_ratio = max(human_chunks, ai_chunks) / total_chunks  # e.g., 3/4 => 0.75
+                combined_confidence = max(
+                    base_confidence,
+                    0.6 * majority_ratio + 0.4 * base_confidence
+                )
+                # If every chunk agrees, ensure a reasonable floor
+                if majority_ratio == 1.0 and total_chunks >= 3:
+                    combined_confidence = max(combined_confidence, 0.85)
+                confidence = min(0.99, combined_confidence)
+            else:
+                confidence = base_confidence
             
             logger.info(f"  → Pure {final_prediction} text")
             logger.info(f"  → Original overall probability: {overall_prob:.3f}")