{"id":"W4415293251","doi":"10.1109/tcss.2025.3597202","title":"Overlapping Community Detection to Generate a Maximum Proximity-Driven Feedback Method for Group Consensus Under Social Network","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Computational Social Systems","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Social network analysis; Social network (sociolinguistics); Group (periodic table); Order (exchange); Focus (optics); Network analysis; Information exchange; Network topology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001405879,0.0006787573,0.001174056,0.0004031544,0.007471294,0.0005665932,0.0004419972,0.0003956396,0.00003071496],"category_scores_gemma":[0.000004706775,0.0008628762,0.001042938,0.001836457,0.0001687017,0.0001412201,0.00001900559,0.001163169,0.00002254627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001091195,"about_ca_system_score_gemma":0.0003771977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002449372,"about_ca_topic_score_gemma":0.0007667902,"domain_scores_codex":[0.9940025,0.002461929,0.001352256,0.0007719575,0.0005624207,0.0008489647],"domain_scores_gemma":[0.9964787,0.001621632,0.0005981187,0.0003027974,0.0008268711,0.0001718968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004310963,0.0007036071,0.00001589813,0.0001832694,0.002192315,4.485103e-7,0.001035465,0.9242387,0.000579655,0.02065866,0.002907382,0.0470535],"study_design_scores_gemma":[0.002266485,0.0003600214,0.0008196274,0.0003434281,0.001155338,0.000003001753,0.002399798,0.9247313,0.0002412223,0.06182799,0.004787739,0.001064101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01389489,0.000045861,0.9780234,0.001302406,0.002381587,0.00325129,0.0005178362,0.00024866,0.0003341273],"genre_scores_gemma":[0.9735123,0.000001872935,0.02193638,0.0004009478,0.002355363,0.001203407,0.0001355917,0.00008374061,0.0003703813],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9596174,"threshold_uncertainty_score":0.9993822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03456560911971143,"score_gpt":0.3227608627265405,"score_spread":0.2881952536068291,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}