{"id":"W3129654956","doi":"10.52933/jdssv.v2i6.47","title":"Robust Model-Based Clustering","year":2022,"lang":"en","type":"article","venue":"Journal of Data Science Statistics and Visualisation","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Defense; Universidad de Buenos Aires","keywords":"Cluster analysis; Estimator; Computer science; Mixture model; Robust statistics; Algorithm; Set (abstract data type); Monte Carlo method; Data mining; Class (philosophy); Multivariate statistics; Artificial intelligence; Machine learning; Mathematics; Statistics","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":[0.007565915,0.001917355,0.003248191,0.004825346,0.001327214,0.003814184,0.006867397,0.003443627,0.004443614],"category_scores_gemma":[0.02920518,0.001499252,0.004170662,0.004729518,0.002151989,0.004456826,0.004829055,0.003532335,0.004282586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001758795,"about_ca_system_score_gemma":0.002557286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004286262,"about_ca_topic_score_gemma":0.003591556,"domain_scores_codex":[0.9904461,0.00375031,0.0004654137,0.002060697,0.002881197,0.0003962565],"domain_scores_gemma":[0.9914355,0.002733594,0.0009576262,0.002889166,0.001802109,0.000181912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001202729,0.000093905,0.001527384,0.0004431896,0.000568855,0.0001208234,0.0002931305,0.5247713,0.0062768,0.2280369,0.01072473,0.2270228],"study_design_scores_gemma":[0.00001957192,0.00003700289,0.0004145303,0.00005331517,0.00005142249,0.0001130526,0.00003365157,0.8691872,0.002613017,0.1194938,0.007915151,0.00006832276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004678625,0.0001148821,0.9986427,0.00005289254,0.00001527537,0.00001953192,0.00006447236,0.0002495755,0.0003727447],"genre_scores_gemma":[0.05435654,0.0005201201,0.9408846,0.0001991915,0.0001089132,0.0002625872,0.001145135,0.0006773056,0.00184558],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007565915,"threshold_uncertainty_score":0.04001284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1328505588997095,"score_gpt":0.375986123003733,"score_spread":0.2431355641040234,"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."}}