{"id":"W2039943102","doi":"10.1198/016214507000000950","title":"Robust Linear Model Selection Based on Least Angle Regression","year":2007,"lang":"en","type":"article","venue":"Journal of the American Statistical Association","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":182,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Outlier; Scalability; Computer science; Robust regression; Multivariate statistics; Model selection; Data set; Set (abstract data type); Linear regression; Regression; Sequence (biology); Selection (genetic algorithm); Data mining; Algorithm; Artificial intelligence; Mathematics; Machine learning; Statistics","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":[0.005495818,0.001840602,0.002420039,0.001587471,0.0005498354,0.0014661,0.00188025,0.001010747,0.00231458],"category_scores_gemma":[0.02272347,0.0009634799,0.001733047,0.001676986,0.0008049157,0.001642333,0.001586109,0.00278012,0.001788742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005007538,"about_ca_system_score_gemma":0.001590855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003432387,"about_ca_topic_score_gemma":0.00294158,"domain_scores_codex":[0.9960879,0.002439282,0.0001718477,0.0005180351,0.0006086939,0.0001742695],"domain_scores_gemma":[0.9893602,0.007581705,0.0008442458,0.0008901804,0.001173569,0.0001501519],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000182283,0.00007290941,0.001791129,0.0001128401,0.0003289693,0.0001735536,0.00004693704,0.8781565,0.002312583,0.01659136,0.002301743,0.09792909],"study_design_scores_gemma":[0.0000124033,0.00002444558,0.0001103124,0.000005128442,0.00001294667,0.00001283129,0.000004539918,0.9937543,0.0005467861,0.005143993,0.000362063,0.00001032236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003342554,0.000112668,0.9956542,0.00008904309,0.00001828275,0.00002372218,0.00005615417,0.0005142174,0.0001890688],"genre_scores_gemma":[0.283258,0.0005377516,0.7112054,0.0002151596,0.0002171228,0.0003985975,0.001338495,0.0005527377,0.002276842],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005495818,"threshold_uncertainty_score":0.02906501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0874089107963037,"score_gpt":0.4124026416889772,"score_spread":0.3249937308926735,"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."}}