{"id":"W4256576576","doi":"10.1002/9781118445112.stat07543.pub2","title":"<scp>LASSO</scp>, the","year":2015,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Lasso (programming language); Elastic net regularization; Coordinate descent; Linear regression; Shrinkage; Mathematics; Selection (genetic algorithm); Set (abstract data type); Algorithm; Regression; Ridge; Computer science; Statistics; Applied mathematics; Artificial intelligence; Biology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003951374,0.0006965398,0.0006161125,0.0001229855,0.0001940815,0.0001342766,0.001036567,0.0003678418,0.005171428],"category_scores_gemma":[0.0009924057,0.0005143405,0.00005355757,0.0004372468,0.0006902402,0.0000601939,0.00065662,0.0008389074,0.003934034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002530012,"about_ca_system_score_gemma":0.0002053196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002791964,"about_ca_topic_score_gemma":0.009071828,"domain_scores_codex":[0.9962341,0.0001721394,0.0005799218,0.000859291,0.001255609,0.0008989303],"domain_scores_gemma":[0.9972679,0.0005486155,0.0006201323,0.001053045,0.00008194934,0.0004283754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000003038468,0.0001259251,0.0002295075,0.00004042567,0.0000634824,0.00005713745,0.000166273,0.00005900783,0.00001104303,0.004960888,0.9816539,0.01262935],"study_design_scores_gemma":[0.0003714265,0.0001237743,0.0005471411,0.0001480277,0.0001092596,0.00001153588,0.0002084925,0.001202633,0.000001534624,0.01365452,0.9833341,0.0002875195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00005962985,0.001236692,0.03265376,0.0001927381,0.001177368,0.0009033429,0.06812841,0.0003972323,0.8952508],"genre_scores_gemma":[0.0001900264,0.002551303,0.07531403,0.0006461681,0.0004733812,0.00005724749,0.009353522,0.0006566643,0.9107577],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05877489,"threshold_uncertainty_score":0.9997308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03453330034355774,"score_gpt":0.2803074980264197,"score_spread":0.245774197682862,"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."}}