{"id":"W3213258851","doi":"10.1080/10618600.2021.1999825","title":"Mixtures of Matrix-Variate Contaminated Normal Distributions","year":2021,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Random variate; Cluster analysis; Computer science; Expectation–maximization algorithm; Data mining; Matrix (chemical analysis); Data Matrix; Algorithm; Artificial intelligence; Statistics; Mathematics; Maximum likelihood; Random variable","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":[],"consensus_categories":[],"category_scores_codex":[0.0003107089,0.00008497441,0.0002441337,0.0000822509,0.00007722945,0.00005839425,0.0001637487,0.00005370959,0.0000121145],"category_scores_gemma":[0.0001656473,0.00006911039,0.00007397868,0.0003123717,0.00009257728,0.0001350356,0.00006611187,0.000190583,3.347132e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007826875,"about_ca_system_score_gemma":0.000158102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003140288,"about_ca_topic_score_gemma":0.000001313858,"domain_scores_codex":[0.9988381,0.0001485965,0.0004775735,0.000106639,0.0003142048,0.0001148451],"domain_scores_gemma":[0.9980315,0.0005899434,0.000288883,0.00007297185,0.0008904549,0.000126272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001534971,0.00009643014,0.000309057,0.00002344657,0.00006015415,0.0001174657,0.00006959437,0.0003444777,0.000279963,0.9788769,0.0006885961,0.01911851],"study_design_scores_gemma":[0.0005633092,0.0001493947,0.03916145,0.00003076989,0.00003806601,0.0004760034,0.000004290132,0.03808928,0.0004227038,0.9205288,0.0004433398,0.00009256488],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007304056,0.0005105906,0.9908609,0.0009130321,0.0001723809,0.00002431493,0.0001597092,0.000005183512,0.00004987627],"genre_scores_gemma":[0.3833255,0.0000522267,0.6164835,0.00007761236,0.00002989797,2.414029e-7,0.00001335748,0.000002101242,0.00001557596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3760214,"threshold_uncertainty_score":0.281824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00868830389333632,"score_gpt":0.275012658105719,"score_spread":0.2663243542123827,"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."}}