diff --git a/cami_src/cami_suite.py b/cami_src/cami_suite.py
index 502ee9f7ca0fe1579da7fb1085dc946dffc3c011..d41005f8bb9f5cb51ba870e624704c6832592c8d 100644
--- a/cami_src/cami_suite.py
+++ b/cami_src/cami_suite.py
@@ -245,7 +245,7 @@ class cami():
                     val_res_dct = set_validation_results['input_values']['values'][rel_score_name]
                     for val in val_res_dct:
                         f.write(f'{val}\t{val_res_dct[val]}\n')
-                
+
             # sub_validation_results = biodigest.single_validation.single_validation(
             #     tar=set(self.result_module_sets[result_set]),
             #     tar_id='entrez',
@@ -365,23 +365,23 @@ class cami():
                                  'first_neighbours': cami_v1.make_first_neighbor_result_set}
                     }
         
-        params_tr = {'hub_penalty': [0, 0.25, 0.5, 0.75, 1.0], 
-                     'damping_factor': [0.1, 0.25, 0.5, 0.75], 
+        params_tr = {'hub_penalty': [0.5], 
+                     'damping_factor': [0.1, 0.25, 0.5, 0.75, 0.85], 
                      'confidence_level': [0.2, 0.35, 0.5, 0.75],
                      'ranking': ['trustrank'],
                      'function': {'cami_v2': cami_v2.run_cami, 
                                   'cami_v3':cami_v3.run_cami}}
         
-        params_b_m = {'hub_penalty': [0, 0.25, 0.5, 0.75, 1.0], 
-                     'confidence_level': [0.2, 0.35, 0.5, 0.75],
-                     'ranking': ['betweenness', 'harmonic'],
-                     'function': {'cami_v2': cami_v2.run_cami,
-                                  'cami_v3':cami_v3.run_cami}}
+        # params_b_m = {'hub_penalty': [0, 0.25, 0.5, 0.75, 1.0], 
+        #              'confidence_level': [0.2, 0.35, 0.5, 0.75],
+        #              'ranking': ['betweenness', 'harmonic'],
+        #              'function': {'cami_v2': cami_v2.run_cami,
+        #                           'cami_v3':cami_v3.run_cami}}
         
         cami_setting_list = generate_param_combinations(params_0)+\
                             generate_param_combinations(params_1)+\
-                            generate_param_combinations(params_tr)+\
-                            generate_param_combinations(params_b_m)
+                            generate_param_combinations(params_tr)#+\
+                           #generate_param_combinations(params_b_m)
 
 
         camis = {}
diff --git a/cami_src/evaluation_scripts/seed_variation_script.py b/cami_src/evaluation_scripts/seed_variation_script.py
index 5fdca37fb0d6ca4e70d19de9928dac8ccb58b8ad..be29a1db41dd4ffe019aabad057683f8a52d2a4b 100644
--- a/cami_src/evaluation_scripts/seed_variation_script.py
+++ b/cami_src/evaluation_scripts/seed_variation_script.py
@@ -55,7 +55,7 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Fal
             with open(os.path.join(cami.tmp_dir, f'{used_tools[0]}_{cami.uid}_relevance_scores.tsv'), 'r') as f:
                 for line in f:
                     val_name = line.split('\t')[0]
-                    redisc_table.write(f'\t{val_name}')
+                    res_table.write(f'\t{val_name}')
             res_table.write('\n')
             
             #result dictionaries of the form {tool:list(value for each iteration)}
@@ -87,11 +87,7 @@ def make_seedvariation(cami, n_iterations, removal_frac=0.2, vis=False, plot=Fal
                 # reinitialize tools
                 cami.initialize_all_tools()
                 
-                # repeat consensus
-                if ident%20==0:     
-                    predict_and_make_consensus(cami)
-                else:
-                    predict_and_make_consensus(cami)
+                predict_and_make_consensus(cami)
                 
                 used_seeds = [cami.ppi_vertex2gene[seed] for seed in cami.seed_lst]