{"id":"W2134165172","doi":"10.1109/icdmw.2010.40","title":"Meerkat: Community Mining with Dynamic Social Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Visualization; Data science; Graphical user interface; Social network analysis; Data mining; Social network (sociolinguistics); Exploratory analysis; Network analysis; Event (particle physics); Data visualization; Social media; World Wide Web; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002026207,0.0001241215,0.0001710551,0.00003507645,0.0004265183,0.00005823417,0.0002440523,0.00003681123,0.0009803664],"category_scores_gemma":[8.76788e-7,0.0001007876,0.00007741841,0.0001867024,0.00008093353,0.00006508038,0.00009923516,0.0005949745,0.000005841724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007487204,"about_ca_system_score_gemma":0.00001588859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005979501,"about_ca_topic_score_gemma":0.001724655,"domain_scores_codex":[0.9993947,0.00006395693,0.0001282135,0.0001094164,0.00009043774,0.0002132855],"domain_scores_gemma":[0.9994739,0.00007230552,0.00006744118,0.0002927547,0.00004944004,0.00004417815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007827365,0.0009085821,0.4634697,0.00001136122,0.001014864,0.000003542105,0.002549319,0.001977001,0.002564115,0.1766744,0.03214244,0.3186063],"study_design_scores_gemma":[0.002123129,0.0003438351,0.1799603,0.00005574793,0.0006061883,0.00000716247,0.005973755,0.7457173,0.001191464,0.03088116,0.03074883,0.00239105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7360559,0.000002622144,0.191993,0.0001053399,0.00003541825,0.00007837265,0.00000205812,0.0001657858,0.07156157],"genre_scores_gemma":[0.9917098,1.299622e-7,0.00744273,0.00005074948,0.0002318523,0.00001600048,0.00004620328,0.00001732638,0.0004851801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7437404,"threshold_uncertainty_score":0.9999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007234276236694074,"score_gpt":0.2559657912966591,"score_spread":0.248731515059965,"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."}}