{"id":"W1999985320","doi":"10.1198/jasa.2011.tm09650","title":"Fast Robust Model Selection in Large Datasets","year":2011,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Estimator; Outlier; Covariate; Robust regression; Robustness (evolution); Selection (genetic algorithm); Computer science; Model selection; Robust statistics; Context (archaeology); Linear regression; Ordinary least squares; Feature selection; Regression; Statistic; Mathematics; Statistics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.03737104,0.003004547,0.004166489,0.003215219,0.001614406,0.002467799,0.004096329,0.002507249,0.003453766],"category_scores_gemma":[0.1004517,0.001853831,0.003816961,0.004135635,0.00144684,0.003215761,0.004100282,0.004847261,0.001860312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173509,"about_ca_system_score_gemma":0.003764729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005978181,"about_ca_topic_score_gemma":0.009091998,"domain_scores_codex":[0.9798647,0.01583823,0.0007970646,0.001608636,0.001560359,0.0003310059],"domain_scores_gemma":[0.9233103,0.06478028,0.002547439,0.006419877,0.002468737,0.0004733955],"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":[0.0004950341,0.0001676798,0.004779074,0.0008514888,0.00123771,0.0007815826,0.0002464356,0.7057642,0.002395163,0.0504166,0.01133023,0.2215347],"study_design_scores_gemma":[0.0001281859,0.0000716935,0.0007518289,0.0000487636,0.00008693308,0.0001288345,0.00004557855,0.9190647,0.001036335,0.07591706,0.002677902,0.00004212031],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002581135,0.0003540204,0.9955059,0.0002660379,0.00003082469,0.00008868358,0.0002222985,0.0008006879,0.0001503659],"genre_scores_gemma":[0.06749653,0.000560582,0.9273865,0.0003373317,0.0001816077,0.001055878,0.001782832,0.0004885657,0.0007101955],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03737104,"threshold_uncertainty_score":0.1976393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09881432076865368,"score_gpt":0.3959868610863974,"score_spread":0.2971725403177436,"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."}}