{"id":"W4400196528","doi":"10.1080/00949655.2024.2368887","title":"A Bayesian destructive generalized Waring regression cure model with a variance decomposition and application in colorectal cancer data","year":2024,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Statistics; Colorectal cancer; Bayesian probability; Regression; Variance (accounting); Regression analysis; Decomposition; Bayesian linear regression; Logistic regression; Mathematics; Econometrics; Cancer; Bayesian inference; Medicine; Internal medicine; Biology","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":[0.009395359,0.0008265903,0.001522781,0.001372137,0.0005580675,0.001103643,0.002432757,0.0017441,0.001686079],"category_scores_gemma":[0.01690126,0.0006520607,0.001639458,0.001468056,0.001183615,0.001566468,0.001510427,0.002640924,0.000426479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009152126,"about_ca_system_score_gemma":0.001208367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006267428,"about_ca_topic_score_gemma":0.004759686,"domain_scores_codex":[0.9973856,0.001702162,0.00008159885,0.000365413,0.0003080431,0.0001572745],"domain_scores_gemma":[0.9930374,0.005366704,0.0005323531,0.0004535744,0.0004348189,0.0001751893],"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":[0.0001727291,0.00009712058,0.004954496,0.0001513246,0.000150649,0.0003739566,0.0003082109,0.7762012,0.001981061,0.1598697,0.001425677,0.05431376],"study_design_scores_gemma":[0.0000139763,0.00003629754,0.0004402785,0.000008014153,0.00001732963,0.00006710603,0.00001482572,0.9808632,0.0001531196,0.01775694,0.0006099001,0.00001908126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02682357,0.0002781265,0.9714615,0.0004002693,0.00002306173,0.00007510338,0.0001676703,0.0001831027,0.0005875464],"genre_scores_gemma":[0.5553679,0.001073461,0.4344077,0.0003684683,0.0001395263,0.0007051373,0.0009507524,0.0001766959,0.006810372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009395359,"threshold_uncertainty_score":0.04968804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06959746962436913,"score_gpt":0.4440528854628272,"score_spread":0.374455415838458,"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."}}