{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002281091,0.002627268,0.002489441,0.00199122,0.001150636,0.001677093,0.001716743,0.001546964,0.00979244],"category_scores_gemma":[0.006171269,0.0008314869,0.003659549,0.001303118,0.0003483669,0.001441703,0.00156083,0.001704099,0.004112778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003918266,"about_ca_system_score_gemma":0.001893615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002847773,"about_ca_topic_score_gemma":0.004725211,"domain_scores_codex":[0.9987494,0.0005574332,0.00007335659,0.0003024767,0.0001929587,0.000124357],"domain_scores_gemma":[0.9975612,0.001087215,0.00009052923,0.0007014546,0.0004621248,0.00009746421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001362686,0.0005550783,0.006678794,0.000393837,0.001390644,0.0007107011,0.0001923948,0.2941486,0.008503772,0.005480783,0.0467301,0.6338526],"study_design_scores_gemma":[0.00009338438,0.0002353723,0.001458636,0.00003003602,0.0003255639,0.0001690658,0.0000812806,0.9820315,0.00382271,0.007074005,0.00464748,0.00003091926],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04602223,0.000777216,0.9385971,0.000682172,0.0002973301,0.0004591508,0.002653591,0.005779124,0.004732132],"genre_scores_gemma":[0.6192328,0.0005536283,0.342057,0.0007354997,0.0003266588,0.0009297866,0.02020698,0.001493975,0.01446363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00979244,"threshold_uncertainty_score":0.03275901,"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."}}