{"id":"W3204558679","doi":"10.1002/cjs.11654","title":"Variable selection in nonparametric functional concurrent regression","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covariate; Lasso (programming language); Nonparametric statistics; Feature selection; Variable (mathematics); Selection (genetic algorithm); Regression analysis; Computer science; Statistics; Econometrics; Mathematics; Machine learning","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005053895,0.00009531886,0.0002516883,0.0002774337,0.00007156011,0.00005093245,0.00007306135,0.00006879058,0.001724796],"category_scores_gemma":[0.009851912,0.00008533663,0.00002798716,0.0006132921,0.00004885944,0.00005499708,0.000007199293,0.0003502644,0.000006743006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000251403,"about_ca_system_score_gemma":0.002348062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004397164,"about_ca_topic_score_gemma":0.00387291,"domain_scores_codex":[0.998799,0.0001592538,0.0004878435,0.0001044905,0.0002148713,0.000234496],"domain_scores_gemma":[0.9972094,0.001456381,0.0002174021,0.00006155026,0.0006924075,0.0003628005],"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":[0.000007774903,0.0000406348,0.004594618,0.00005324391,0.00001926257,0.0002934067,0.00007374403,0.00005956338,0.000144586,0.9415683,0.02892284,0.02422209],"study_design_scores_gemma":[0.0006460763,0.0001485641,0.02052657,0.0002744726,0.00005415944,0.0004050292,0.0001235989,0.003694583,0.0003086846,0.9657673,0.007879766,0.0001711503],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00403705,0.0002259958,0.9934106,0.00008404522,0.0007935276,0.00004155105,0.0001771396,0.000002665582,0.00122735],"genre_scores_gemma":[0.1028252,0.00001751579,0.896622,0.00008777968,0.0001283014,0.000001381293,0.000007085816,0.00001257321,0.0002981541],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09878817,"threshold_uncertainty_score":0.9991878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1021569378671671,"score_gpt":0.3336792177736905,"score_spread":0.2315222799065235,"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."}}