{"id":"W2964385099","doi":"10.1007/s10985-019-09480-2","title":"Parametric and semiparametric estimation methods for survival data under a flexible class of models","year":2019,"lang":"en","type":"article","venue":"Lifetime Data Analysis","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Covariate; Accelerated failure time model; Parametric statistics; Inference; Econometrics; Nonlinear system; Semiparametric model; Semiparametric regression; Computer science; Function (biology); Mathematics; Nonparametric statistics; Parametric model; Statistics; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004435485,0.0001936808,0.000917555,0.000816598,0.0000491446,0.0000795027,0.001127286,0.0001261492,0.000194489],"category_scores_gemma":[0.0102264,0.0001653774,0.00008720388,0.003697354,0.00007543288,0.0004416353,0.0008657101,0.0001273942,0.000008968109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001898574,"about_ca_system_score_gemma":0.00005727728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001723586,"about_ca_topic_score_gemma":0.00000848028,"domain_scores_codex":[0.9975008,0.0004479567,0.0006694577,0.0007904437,0.0003327037,0.0002586057],"domain_scores_gemma":[0.9817998,0.01431189,0.0003634528,0.003244817,0.0001656037,0.0001144683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001796461,0.0005749219,0.00416803,0.001137927,0.00612516,7.662342e-7,0.0001097873,0.01568815,0.000333463,0.6799217,0.003592175,0.2881682],"study_design_scores_gemma":[0.0002457989,0.00004535254,0.0005040246,0.00001270936,0.002470897,5.050869e-7,0.00004113673,0.7504914,0.00007105117,0.2458032,0.0001661658,0.0001477098],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003334371,0.0002412043,0.9916862,0.00007141423,0.00005901835,0.000361431,0.003783052,0.00003533618,0.0004279285],"genre_scores_gemma":[0.04330894,0.00005851749,0.9540063,0.00003576978,0.00001846486,0.0000109505,0.002349439,0.00002058786,0.0001911094],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7348033,"threshold_uncertainty_score":0.9981109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2814666528890903,"score_gpt":0.4935555543037599,"score_spread":0.2120889014146695,"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."}}