{"id":"W199296758","doi":"10.1137/1.9781611972795.84","title":"Detecting Communities in Social Networks using Max-Min Modularity","year":2009,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Modularity (biology); Cluster analysis; Chen; Community structure; Robustness (evolution); Complex network; Measure (data warehouse); Clustering coefficient; Theoretical computer science; Data mining; Artificial intelligence; Mathematics; World Wide Web; Combinatorics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002524004,0.0001188896,0.0002114271,0.00008530643,0.0002556915,0.00006459249,0.0001666701,0.00003969602,0.0002632944],"category_scores_gemma":[9.520236e-7,0.0001255318,0.000101267,0.0002853691,0.00002802695,0.00009723472,0.00007070132,0.0002852103,0.000001072386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004180469,"about_ca_system_score_gemma":0.00001068032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002913885,"about_ca_topic_score_gemma":0.0003533913,"domain_scores_codex":[0.9992212,0.0001016037,0.0002236147,0.0001063599,0.00007964206,0.0002675827],"domain_scores_gemma":[0.9996608,0.00004204876,0.00006711575,0.0001772338,0.00002842089,0.00002430567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003053063,0.0004597912,0.2861647,0.000005674966,0.0001235214,0.000004371398,0.001906708,0.04193128,0.001032258,0.113356,0.0008386089,0.5541465],"study_design_scores_gemma":[0.0002336096,0.00002158243,0.01473875,0.0000239764,0.00002724512,5.208935e-7,0.001353291,0.932847,0.0004017013,0.04975073,0.0003064349,0.0002951279],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7065156,0.00002345746,0.280183,0.0000496964,0.00001502029,0.00008186916,8.056238e-7,0.00008714227,0.01304335],"genre_scores_gemma":[0.9937888,6.569382e-7,0.005713735,0.00007887928,0.0003465282,0.000003098701,0.00001288301,0.000008185852,0.00004723786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8909158,"threshold_uncertainty_score":0.5119038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03596780132429976,"score_gpt":0.3038009831175571,"score_spread":0.2678331817932573,"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."}}