{"id":"W2896398456","doi":"10.1080/01621459.2018.1543124","title":"Adaptive Huber Regression","year":2018,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":305,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Regression; Statistics; Mathematics; Econometrics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008272365,0.001522915,0.002354197,0.002049671,0.0007485143,0.001447239,0.003137468,0.002036054,0.003295633],"category_scores_gemma":[0.02974009,0.0008110777,0.001669954,0.002660811,0.001988841,0.002950013,0.002039516,0.003495502,0.001503808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223005,"about_ca_system_score_gemma":0.001479786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003354794,"about_ca_topic_score_gemma":0.003222411,"domain_scores_codex":[0.9956797,0.001995477,0.0001667834,0.001132557,0.0007531691,0.0002722951],"domain_scores_gemma":[0.9865972,0.00762757,0.001326978,0.00289004,0.001306072,0.0002520354],"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":[0.0002125748,0.00008380375,0.006866552,0.0004719965,0.000551339,0.0002973606,0.0002006118,0.5473922,0.00433487,0.271176,0.01016977,0.1582429],"study_design_scores_gemma":[0.00001693521,0.00003382711,0.001028618,0.00003302606,0.00003748075,0.00005569611,0.00001495685,0.9090032,0.00120818,0.08543884,0.00309084,0.0000384314],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003791696,0.0005273967,0.9940686,0.00025423,0.00005913501,0.00003603334,0.000180467,0.0003902736,0.0006921857],"genre_scores_gemma":[0.4311694,0.003062483,0.5485365,0.0008869138,0.000894199,0.0004859611,0.00185638,0.0007258253,0.01238236],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008272365,"threshold_uncertainty_score":0.04374897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0743662802260562,"score_gpt":0.4399700873989351,"score_spread":0.3656038071728789,"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."}}