{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009475364,0.001324209,0.001492381,0.001485021,0.000807355,0.001262243,0.002869406,0.001145312,0.0026319],"category_scores_gemma":[0.02630957,0.0005969097,0.001890185,0.001845951,0.002050746,0.001455114,0.003142693,0.002432412,0.0006142427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007409168,"about_ca_system_score_gemma":0.002472606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00514084,"about_ca_topic_score_gemma":0.0036785,"domain_scores_codex":[0.9934164,0.004145427,0.0001910083,0.0007915935,0.001232043,0.0002234213],"domain_scores_gemma":[0.9899637,0.006646808,0.000768461,0.0011605,0.001240395,0.0002200336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003388627,0.0001825045,0.008543956,0.0003706093,0.0003937117,0.000430628,0.0002666051,0.5360053,0.003911236,0.1551296,0.004138224,0.2902887],"study_design_scores_gemma":[0.00002869293,0.00006675578,0.0005815263,0.00001921038,0.0000188434,0.0000730527,0.00001315797,0.9689938,0.0006483559,0.02763364,0.001903668,0.00001931098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002298921,0.00006667912,0.9971012,0.00006501391,0.0000233924,0.00002934658,0.00003624389,0.0001034071,0.0002757499],"genre_scores_gemma":[0.2854507,0.0003548741,0.7088885,0.0003053554,0.0002779534,0.0008204469,0.0005976887,0.0002585844,0.00304597],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009475364,"threshold_uncertainty_score":0.05011111,"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."}}