{"id":"W4206538304","doi":"10.1002/cjs.11675","title":"Economic variable selection","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Kwansei Gakuin University","keywords":"Feature selection; Variable (mathematics); Covariate; Selection (genetic algorithm); Computer science; Model selection; Bayes' theorem; Econometrics; Bayesian probability; Regression analysis; Regression; Perspective (graphical); Machine learning; Artificial intelligence; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009681763,0.0009655356,0.002113411,0.00197173,0.0007980411,0.002060483,0.001599629,0.001342268,0.01046765],"category_scores_gemma":[0.02847794,0.0004013505,0.001117326,0.003728336,0.001332608,0.00156987,0.001752504,0.001918929,0.001504619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771154,"about_ca_system_score_gemma":0.00263979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003414549,"about_ca_topic_score_gemma":0.0034817,"domain_scores_codex":[0.9912634,0.006365468,0.0001956174,0.0006677356,0.001261294,0.0002465359],"domain_scores_gemma":[0.9881155,0.009608032,0.0005187956,0.0008145821,0.0007800655,0.0001631054],"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":[0.0001720756,0.0001071316,0.004541583,0.0004656705,0.000410455,0.0002330719,0.00009202413,0.1376969,0.000332554,0.5723115,0.02267677,0.2609603],"study_design_scores_gemma":[0.0001541638,0.0001313989,0.002301086,0.0002131041,0.000120156,0.0002055995,0.00007654206,0.468487,0.0004726094,0.4812036,0.04659395,0.00004079122],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008497549,0.004327045,0.9667673,0.002567189,0.0004142311,0.0003050194,0.000621272,0.0001942069,0.01630613],"genre_scores_gemma":[0.5041556,0.01119511,0.4464953,0.001577036,0.001942739,0.001831123,0.002822201,0.000289744,0.02969117],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01046765,"threshold_uncertainty_score":0.05120265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06482457205450447,"score_gpt":0.3095555356521665,"score_spread":0.244730963597662,"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."}}