{"id":"W4416967053","doi":"10.1080/10618600.2025.2596057","title":"Robust Multi-Model Subset Selection","year":2025,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Outlier; Selection (genetic algorithm); Robustness (evolution); Robust statistics; Cheminformatics; Estimator; Code (set theory); Source code","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":[0.004189887,0.001728722,0.002274754,0.001106869,0.0007119085,0.001304369,0.002056796,0.001217394,0.002151347],"category_scores_gemma":[0.01228438,0.0007073689,0.00198974,0.001009922,0.0008031712,0.001595033,0.001772855,0.002015577,0.001208342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005999177,"about_ca_system_score_gemma":0.001667489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002174434,"about_ca_topic_score_gemma":0.002541386,"domain_scores_codex":[0.9982015,0.0008955344,0.00007651811,0.0003612466,0.0003484678,0.0001167205],"domain_scores_gemma":[0.9953154,0.00270669,0.0003611038,0.0009267185,0.0005541661,0.0001359291],"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":[0.0001449839,0.00007860086,0.003242111,0.0001170339,0.0002719226,0.000174051,0.0001069347,0.8510834,0.002811322,0.0158796,0.005768234,0.1203218],"study_design_scores_gemma":[0.00000696911,0.00002313585,0.0001901506,0.000008141998,0.00001502881,0.00002762918,0.00001211203,0.9893856,0.000808763,0.009004875,0.0005096418,0.000007936788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0108217,0.0001980047,0.9873519,0.0001907064,0.00003203145,0.00004671986,0.0001841856,0.0006175493,0.0005572233],"genre_scores_gemma":[0.5047321,0.0004413266,0.4868633,0.0005434211,0.000220531,0.0004258858,0.003144994,0.000581796,0.003046619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004189887,"threshold_uncertainty_score":0.02215856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103888632090066,"score_gpt":0.4074373059381189,"score_spread":0.3035486738480529,"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."}}