Update predictors.py

predictors.py

@@ -357,10 +357,10 @@ def predict_1on1_scores(input, models):
         total = sum(mc_score.values())
         # Normalize each value by dividing it by the total
         mc_score = {key: value / total for key, value in mc_score.items()}
-
         sum_prob = 1 - bc_score["HUMAN"]
         for key, value in mc_score.items():
             mc_score[key] = value * sum_prob
+        print('MC Score:',mc_score)
         if sum_prob < 0.01:
             mc_score = {}