{"id":"W3202523284","doi":"10.1002/cjs.11661","title":"Robust estimation and variable selection for function‐on‐scalar regression","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Mathematics; Estimator; Least absolute deviations; Scalar (mathematics); Robustness (evolution); Applied mathematics; Regression analysis; Regression; Feature selection; Statistics; Mathematical optimization; Algorithm; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004108125,0.00008977239,0.0001946498,0.00009534628,0.0001775155,0.00007281053,0.00004284767,0.00006593909,0.000246338],"category_scores_gemma":[0.007820345,0.00007793569,0.00002166902,0.0001280688,0.00004180752,0.0000583764,0.000003913672,0.0001581288,0.000001567543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008482518,"about_ca_system_score_gemma":0.0007252042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008880832,"about_ca_topic_score_gemma":0.0006643006,"domain_scores_codex":[0.9992136,0.00007633146,0.0003168047,0.0001012061,0.0001222777,0.0001697555],"domain_scores_gemma":[0.9973297,0.001415906,0.0001914617,0.00007224235,0.0006790404,0.0003116746],"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":[0.00002822785,0.00001655916,0.0002434954,0.000105598,0.00003159485,0.00002061611,0.00006829866,0.0003272707,0.0001002282,0.9233388,0.03364969,0.0420696],"study_design_scores_gemma":[0.0004111942,0.0003678967,0.0009890881,0.0002003564,0.0001235781,0.0001294678,0.00007858212,0.04663754,0.0002329623,0.9461963,0.004524341,0.0001087403],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001288394,0.00007165617,0.9972901,0.0001810396,0.0004047566,0.00007088304,0.0002681002,0.000003973029,0.0004210775],"genre_scores_gemma":[0.01648772,0.000009916005,0.98291,0.0001471689,0.0001116988,0.000002662339,0.00001066475,0.00001498415,0.0003051662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04631027,"threshold_uncertainty_score":0.9362249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1040892775418899,"score_gpt":0.3171644884129491,"score_spread":0.2130752108710593,"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."}}