Update dupes calculation in predict_dupes function to multiply ownership product by 100, improving accuracy in duplicate predictions based on ownership metrics.

global_func/predict_dupes.py

@@ -328,7 +328,7 @@ def predict_dupes(portfolio, maps_dict, site_var, type_var, Contest_Size, streng
             portfolio['avg_own_rank'] = portfolio[dup_count_columns].mean(axis=1)
             
             # Calculate dupes formula
-            portfolio['dupes_calc'] = (portfolio['own_product'] * portfolio['avg_own_rank']) * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * Contest_Size + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((60000 - portfolio['salary']) / 100)
+            portfolio['dupes_calc'] = ((portfolio['own_product'] * 100) * portfolio['avg_own_rank']) * (portfolio['Own'] / (100 + (Contest_Size / 1000))) * Contest_Size + ((portfolio['salary'] - (60000 - portfolio['Own'])) / 100) - ((60000 - portfolio['salary']) / 100)
             portfolio['dupes_calc'] = portfolio['dupes_calc'] * dupes_multiplier
             
             # Round and handle negative values