{"id":"W2006177467","doi":"10.1103/physreve.81.046102","title":"Loops and multiple edges in modularity maximization of networks","year":2010,"lang":"en","type":"article","venue":"Physical Review E","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; HEC Montréal","funders":"Agence Nationale de la Recherche","keywords":"Maximization; Null model; Null (SQL); Mathematics; Random graph; Modularity (biology); Clique; Combinatorics; Clique problem; Discrete mathematics; Computer science; Pathwidth; Mathematical optimization; Graph; Line graph","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":[0.0001328546,0.00008825256,0.0003184718,0.00002064708,0.00001824817,0.000007754788,0.00009024231,0.00001340856,0.00004802887],"category_scores_gemma":[0.00002061854,0.00007699103,0.00008337388,0.0002165064,0.0000446403,0.00005832413,0.00006416141,0.0001875008,0.000001632521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002903141,"about_ca_system_score_gemma":0.00000632017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001129844,"about_ca_topic_score_gemma":0.00002776007,"domain_scores_codex":[0.9994485,0.00003963109,0.0001849449,0.000150067,0.0000703458,0.0001065068],"domain_scores_gemma":[0.9995426,0.00008121051,0.00008988057,0.0002102329,0.00004010199,0.00003595862],"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":[0.000007389181,0.0006761384,0.3668603,0.00038102,0.00005688629,4.814582e-7,0.00005788263,0.0007033885,0.003830611,0.08881084,0.0007157037,0.5378994],"study_design_scores_gemma":[0.000611227,0.00005825041,0.1074883,0.001301138,0.0002385532,5.44202e-7,0.000009486824,0.7512218,0.00406724,0.127943,0.006504767,0.0005556691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9469817,0.003919211,0.04621809,0.000202173,0.00004522693,0.0005412192,0.000007172937,0.00004116196,0.002044021],"genre_scores_gemma":[0.9984953,0.000495861,0.0007708253,0.00003165044,0.0001568837,0.00001525705,0.00002042034,0.000007133943,0.00000660237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7505184,"threshold_uncertainty_score":0.3139603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01103124952420767,"score_gpt":0.2855459455967111,"score_spread":0.2745146960725035,"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."}}