{"id":"W4327936212","doi":"10.5539/ijsp.v12n2p28","title":"Olsavs: A New Algorithm For Model Selection","year":2023,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lasso (programming language); Ordinary least squares; Shrinkage; Mathematics; Mean squared error; Variance (accounting); Feature selection; Selection (genetic algorithm); Variable (mathematics); Algorithm; Regression; Statistics; Least-squares function approximation; Linear regression; Computer science; Artificial intelligence; Estimator","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008681901,0.00008051888,0.000176703,0.00007873886,0.00003994191,0.00005517505,0.0001310301,0.00004092739,0.00003808599],"category_scores_gemma":[0.003295522,0.00006615528,0.00004494508,0.00007342971,0.0000438321,0.00006432318,0.00003275522,0.0001106993,0.000001457636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000484836,"about_ca_system_score_gemma":0.0001578204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000100849,"about_ca_topic_score_gemma":0.000006013885,"domain_scores_codex":[0.9990088,0.00003794652,0.000435753,0.0001109292,0.0002923359,0.0001142046],"domain_scores_gemma":[0.9972637,0.001522201,0.0002266634,0.00004953994,0.0008380162,0.00009985758],"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":[0.00006531013,0.00005130982,0.0001636755,0.00003472509,0.0000663561,0.000003861248,0.0001453996,0.000107252,0.00007056706,0.5110835,0.01093359,0.4772744],"study_design_scores_gemma":[0.0003245781,0.000133596,0.0004506981,0.00002089838,0.00002031963,0.00001689121,0.00001014212,0.3016886,0.00005308753,0.6967368,0.0004953123,0.00004915277],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004238845,0.00001172961,0.9942923,0.0004520189,0.0003185499,0.0001309366,0.0004541386,0.00001479084,0.00008668805],"genre_scores_gemma":[0.007464525,0.00004743924,0.9919825,0.00005002805,0.0002133884,0.000005456897,0.000006524956,0.000009056143,0.0002211435],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4772252,"threshold_uncertainty_score":0.3945285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1152622829620855,"score_gpt":0.4131536130438684,"score_spread":0.2978913300817829,"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."}}