{"id":"W2742855836","doi":"10.1002/cjs.11327","title":"Minimax robust active learning for approximately specified regression models","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; McGill University; Jewish General Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Minimax; Statistics; Population; Context (archaeology); Regression; Sampling (signal processing); Regression analysis; Econometrics; Mathematics; Computer science; Benchmark (surveying); Sampling distribution; Mathematical optimization; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.01633004,0.001402036,0.003066399,0.001296543,0.000577822,0.002364549,0.004585002,0.002843936,0.002654236],"category_scores_gemma":[0.04250839,0.001230558,0.001261136,0.001168429,0.003057067,0.002857613,0.00304781,0.003747668,0.000659846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001869357,"about_ca_system_score_gemma":0.001620496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004475079,"about_ca_topic_score_gemma":0.003349118,"domain_scores_codex":[0.9956064,0.003024552,0.0001796528,0.0005848325,0.0004260759,0.0001784053],"domain_scores_gemma":[0.9539469,0.0405393,0.001749184,0.001523608,0.00187204,0.0003688729],"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":[0.0001117896,0.0000632274,0.001126419,0.00009676972,0.00008545902,0.00004983559,0.00009069233,0.9566496,0.0004030551,0.01965587,0.0007443572,0.02092277],"study_design_scores_gemma":[0.000006948963,0.00001200211,0.00004872661,0.000008721698,0.000002801061,0.000003441732,0.000003704891,0.9938012,0.000106363,0.005910553,0.00009246897,0.000003133703],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01204515,0.0003374276,0.9862422,0.0004165588,0.00002130667,0.00004305023,0.00006751865,0.0002276139,0.0005992403],"genre_scores_gemma":[0.7163666,0.0005544461,0.2731475,0.0007958861,0.0002466257,0.0007968449,0.0008636268,0.0003502508,0.006878201],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01633004,"threshold_uncertainty_score":0.0863626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05832086344198043,"score_gpt":0.2768825962325897,"score_spread":0.2185617327906092,"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."}}