{"id":"W4403914277","doi":"10.1016/j.csda.2024.108073","title":"Multi-model subset selection","year":2024,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Model selection; Selection (genetic algorithm); Mathematics; Computer science; Artificial intelligence; Statistics","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":[0.0001639004,0.0001222678,0.0001780796,0.0003123911,0.00007615265,0.0002039399,0.0001695096,0.00004300714,0.0001170932],"category_scores_gemma":[0.0000283508,0.0001279004,0.00005772725,0.0009687372,0.00001595693,0.0001804011,0.00003200501,0.0001184872,0.0001842354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007526315,"about_ca_system_score_gemma":0.00003741268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009827791,"about_ca_topic_score_gemma":0.0005264456,"domain_scores_codex":[0.9990343,0.0000259532,0.0002695271,0.0002887604,0.0002434519,0.0001379376],"domain_scores_gemma":[0.9995039,0.0001203049,0.00001941806,0.0002212344,0.00007005249,0.00006507704],"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":[0.000001578335,0.000009177137,0.0002013422,0.0000394038,0.001057809,0.000005094741,0.00003557324,0.9726362,0.00007492064,0.00168674,0.02034198,0.003910211],"study_design_scores_gemma":[0.00009743364,0.000004323388,0.00206227,0.000005894411,0.0006273979,0.000003858099,0.000004905868,0.9905781,0.000002631177,0.000789217,0.005683716,0.0001402595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.000804721,0.0003574702,0.9928026,0.00002393401,0.0002253835,0.00006037089,0.005222483,0.0004170286,0.00008601013],"genre_scores_gemma":[0.8380883,0.00003108013,0.1529316,0.00003333024,0.00008080241,0.00001128783,0.008515729,0.0000245193,0.0002833989],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.839871,"threshold_uncertainty_score":0.5215626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03066994363911109,"score_gpt":0.2980387150845116,"score_spread":0.2673687714454005,"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."}}