{"id":"W2051644092","doi":"10.1002/cjs.10082","title":"Model‐based linear clustering","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Humanities; Cluster analysis; Maximum likelihood; Mathematics; Statistics; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.005181591,0.001246754,0.002048424,0.003082881,0.001436492,0.003290232,0.004217752,0.002092437,0.005218358],"category_scores_gemma":[0.02002966,0.001017503,0.002270379,0.003815614,0.001714738,0.00268258,0.003655361,0.002789532,0.002705106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003034537,"about_ca_system_score_gemma":0.002807023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01077414,"about_ca_topic_score_gemma":0.01019583,"domain_scores_codex":[0.9939234,0.003152231,0.0002303328,0.001133192,0.001303597,0.0002572309],"domain_scores_gemma":[0.9926922,0.003694866,0.0005810063,0.001234289,0.001623484,0.0001741528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001611144,0.00009209074,0.002642771,0.0003536156,0.0004086981,0.0001084871,0.0003952329,0.6384418,0.001391563,0.1535705,0.01011189,0.1923222],"study_design_scores_gemma":[0.00001404503,0.00002038693,0.0004351707,0.00003224831,0.00002728625,0.00004523642,0.00003367763,0.9212949,0.0004498336,0.0746066,0.003014248,0.00002645198],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00233721,0.0003067301,0.9952991,0.0002038302,0.00003043061,0.00004695786,0.0001110239,0.0002442745,0.001420382],"genre_scores_gemma":[0.2245403,0.00097331,0.7629558,0.00041886,0.0001813725,0.0005183756,0.001685355,0.0004187163,0.008307902],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01077414,"threshold_uncertainty_score":0.02740324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02886596827548563,"score_gpt":0.2641297409475343,"score_spread":0.2352637726720487,"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."}}