{"id":"W3139051417","doi":"10.1111/exsy.12688","title":"Multivariate‐bounded Gaussian mixture model with minimum message length criterion for model selection","year":2021,"lang":"en","type":"article","venue":"Expert Systems","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; MNIST database; Cluster analysis; Model selection; Mixture model; Selection (genetic algorithm); Artificial intelligence; Representation (politics); Pattern recognition (psychology); Feature selection; Bounded function; Data mining; Gaussian; Machine learning; Artificial neural network; 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":[0.004706121,0.001351191,0.00197174,0.001565065,0.0008432905,0.001568365,0.002496179,0.001707539,0.002195555],"category_scores_gemma":[0.01337115,0.0007927068,0.001852752,0.00159045,0.001027953,0.001599706,0.001662006,0.002676588,0.0009949128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001396891,"about_ca_system_score_gemma":0.001673732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01021336,"about_ca_topic_score_gemma":0.006441648,"domain_scores_codex":[0.9964061,0.00189159,0.000192795,0.0006185012,0.0006634681,0.0002274907],"domain_scores_gemma":[0.9938778,0.004414482,0.0003811328,0.0003475999,0.0008611467,0.0001178349],"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":[0.000293523,0.0001114458,0.002155242,0.0001552173,0.0002004618,0.0001277069,0.000142342,0.8516304,0.002538479,0.02574321,0.002178858,0.1147231],"study_design_scores_gemma":[0.000005719663,0.0000185108,0.000147772,0.000005979135,0.000008386204,0.00001000672,0.000005013222,0.9952528,0.0003774579,0.003933132,0.000227118,0.000008136052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00682914,0.0001951638,0.9921164,0.0001929411,0.00002022199,0.00003960855,0.00007227125,0.0002509916,0.0002832877],"genre_scores_gemma":[0.4911932,0.0005248629,0.5016043,0.0003371821,0.0001357933,0.0006374597,0.001435788,0.0002457233,0.003885772],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01021336,"threshold_uncertainty_score":0.02488863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03003543556985333,"score_gpt":0.29848945313278,"score_spread":0.2684540175629267,"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."}}