{"id":"W1648113946","doi":"10.48550/arxiv.1404.5874","title":"Using Triangles to Improve Community Detection in Directed Networks","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weighting; Computer science; Directed graph; Partition (number theory); Graph; Metric (unit); Theoretical computer science; Combinatorics; Mathematics; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004398137,0.001330567,0.001380874,0.007175319,0.001711613,0.002346717,0.00219572,0.002083404,0.00251381],"category_scores_gemma":[0.03924979,0.0007192608,0.001219988,0.004624862,0.001262273,0.005870345,0.004240902,0.002030329,0.001304347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001133368,"about_ca_system_score_gemma":0.0009208482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005502253,"about_ca_topic_score_gemma":0.007913485,"domain_scores_codex":[0.9951049,0.001583696,0.000293423,0.0009950207,0.001693897,0.000329075],"domain_scores_gemma":[0.9788833,0.01177784,0.002230119,0.002967712,0.003356445,0.0007846603],"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":[0.0007679498,0.0002943671,0.02659535,0.0007607112,0.0004432915,0.0005345215,0.00181771,0.212193,0.03405415,0.07785145,0.0127557,0.6319318],"study_design_scores_gemma":[0.00006888036,0.0001612362,0.003200505,0.00009035643,0.00009554195,0.0004456092,0.000406916,0.8766806,0.01380303,0.09239074,0.01259089,0.00006574216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05485473,0.0008181478,0.9388723,0.0003842658,0.0001548649,0.0001934401,0.000326753,0.001508745,0.002886797],"genre_scores_gemma":[0.3423428,0.0006489304,0.6507182,0.0003249404,0.0001898074,0.0002388573,0.001585655,0.0005656147,0.003385143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007175319,"threshold_uncertainty_score":0.02325988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07402897683819298,"score_gpt":0.2222899796998331,"score_spread":0.1482610028616401,"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."}}