{"id":"W2770895268","doi":"10.1145/3110025.3110067","title":"Community Detection in Evolving Networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University; Compute Canada","keywords":"Modularity (biology); Community structure; Computer science; Enhanced Data Rates for GSM Evolution; Clique percolation method; Complex network; Social network analysis; Data mining; Order (exchange); Social network (sociolinguistics); Evolving networks; Artificial intelligence; Data science; Theoretical computer science; Machine learning; Distributed computing; World Wide Web; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003887171,0.0007086563,0.001217211,0.005393733,0.001406158,0.002099595,0.002323445,0.002323197,0.001136496],"category_scores_gemma":[0.03169648,0.0006142881,0.0008949175,0.003564597,0.001791232,0.004298131,0.00258471,0.001692294,0.0004503565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001423053,"about_ca_system_score_gemma":0.0006400418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003279856,"about_ca_topic_score_gemma":0.001605974,"domain_scores_codex":[0.995515,0.001439533,0.0001867881,0.00131258,0.001268875,0.000277187],"domain_scores_gemma":[0.9852424,0.009006458,0.002000529,0.001283064,0.001968077,0.0004994353],"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":[0.0003662388,0.0001670347,0.02072138,0.0005365438,0.0003696513,0.0009214937,0.001407547,0.3419232,0.01723216,0.1943718,0.008974181,0.4130087],"study_design_scores_gemma":[0.00001689893,0.00003584819,0.001608822,0.00003401679,0.00002508878,0.00030719,0.0001199562,0.9061152,0.00312437,0.08379079,0.004796783,0.00002490759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03329528,0.0009638992,0.962487,0.0003644402,0.0000729407,0.00009111478,0.0001570441,0.0004522701,0.002115941],"genre_scores_gemma":[0.5283065,0.00110744,0.4654827,0.0003531303,0.0001942308,0.0002622762,0.0007115387,0.0001920984,0.003390176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005393733,"threshold_uncertainty_score":0.02055758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02039706189152401,"score_gpt":0.289563551717916,"score_spread":0.269166489826392,"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."}}