{"id":"W2129583728","doi":"10.1080/00949650412331321115","title":"Unified scheme for testing for outliers in linear models","year":2006,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; McMaster University","keywords":"Outlier; Mathematics; Missing data; Statistics; Linear regression; Linear model; Design matrix; Factorial; Data mining; Computer science; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006333121,0.00009139985,0.0002639387,0.0001027777,0.00006561985,0.00002389863,0.00002959769,0.00005319777,0.000001365239],"category_scores_gemma":[0.00288709,0.00008104013,0.00003336168,0.00008382301,0.00003232279,0.0001541099,0.000006799515,0.0000908283,7.854585e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003810543,"about_ca_system_score_gemma":0.0000332626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003216214,"about_ca_topic_score_gemma":0.000002557158,"domain_scores_codex":[0.9988936,0.00005369761,0.0006541652,0.0001141661,0.000146569,0.000137779],"domain_scores_gemma":[0.9898616,0.009292326,0.0002802865,0.00003089463,0.0004771897,0.00005769478],"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":[0.000160659,0.000053489,0.0000483613,0.00008728067,0.00000515884,0.000001521035,0.00005182045,0.6580345,0.00008562572,0.3240295,0.00004669031,0.01739538],"study_design_scores_gemma":[0.0008707281,0.0001405377,0.0001934994,0.00002310977,0.00001400248,0.000001452532,0.0000214315,0.5064148,0.000004725662,0.4922505,0.00001881782,0.00004636199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01342664,0.00001553865,0.9859625,0.00006131413,0.00007253659,0.0003337489,0.00005579894,0.000009863182,0.00006211657],"genre_scores_gemma":[0.4248551,3.892802e-7,0.5750378,0.00001733851,0.000056142,0.00000348937,0.000008936004,0.000008930434,0.00001178525],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4114285,"threshold_uncertainty_score":0.3456325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2025829189007008,"score_gpt":0.4640862695997438,"score_spread":0.261503350699043,"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."}}