{"id":"W2986248248","doi":"10.1002/sim.8852","title":"Model diagnostics for censored regression via randomized survival probabilities","year":2020,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Saskatchewan","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Residual; Quantile; Statistical hypothesis testing; Regression; Regression analysis; Nonlinear regression; Nonlinear system; Studentized residual; Accelerated failure time model","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":[0.02189423,0.001023355,0.001458626,0.002571376,0.0005128683,0.00134175,0.002418379,0.001648917,0.002411617],"category_scores_gemma":[0.1338942,0.0004976165,0.001545373,0.001548183,0.0037474,0.003203348,0.002034182,0.002735529,0.0003141195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00150029,"about_ca_system_score_gemma":0.002076377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003525845,"about_ca_topic_score_gemma":0.002093538,"domain_scores_codex":[0.9852181,0.01082758,0.0004629081,0.001986937,0.001181735,0.0003227384],"domain_scores_gemma":[0.8755313,0.107213,0.007511478,0.006812456,0.002332803,0.0005989209],"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":[0.0005261205,0.000151296,0.03210098,0.0003649242,0.0004152486,0.000461408,0.0003090486,0.5366053,0.00167533,0.3204003,0.002163153,0.1048269],"study_design_scores_gemma":[0.0000729986,0.0001385307,0.001780552,0.00003682992,0.00003581053,0.00008696372,0.00003921224,0.88802,0.0007948328,0.1082554,0.0007087721,0.00003004297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02747416,0.0002259469,0.9708185,0.0002900388,0.00003211991,0.00008367955,0.0001665272,0.0004551271,0.0004539108],"genre_scores_gemma":[0.7075624,0.0003413554,0.2892006,0.0003123479,0.0001076627,0.0005130236,0.0007663333,0.0001599818,0.001036274],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02189423,"threshold_uncertainty_score":0.1157892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1382759305060381,"score_gpt":0.4197208800041434,"score_spread":0.2814449494981054,"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."}}