{"id":"W1972766374","doi":"10.1080/02664763.2011.595399","title":"Applying a marginalized frailty model to competing risks","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Statistics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Public Health Agency of Canada; Western University","funders":"","keywords":"Multivariate statistics; Econometrics; Martingale (probability theory); Multivariate analysis; Statistics; Proportional hazards model; Computer science; Breast cancer; Cluster analysis; Actuarial science; Mathematics; Medicine; Economics; Cancer","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":[0.01350106,0.001207905,0.001635968,0.00184958,0.0004949426,0.00183244,0.004153204,0.001694456,0.003978476],"category_scores_gemma":[0.03404225,0.0008016747,0.003153137,0.001560984,0.00164817,0.001959231,0.003018571,0.003531506,0.0006279045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001443356,"about_ca_system_score_gemma":0.002497928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009052039,"about_ca_topic_score_gemma":0.004958623,"domain_scores_codex":[0.9950046,0.003340631,0.0001733441,0.0005369661,0.0006959395,0.0002486141],"domain_scores_gemma":[0.9870163,0.0101077,0.0006067666,0.001130929,0.0008379225,0.0003004586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001586078,0.00009986226,0.008265359,0.0002677315,0.0005381609,0.000681794,0.0006886144,0.4760119,0.0009774368,0.4506916,0.002553919,0.05906499],"study_design_scores_gemma":[0.00003494623,0.0001121081,0.000982985,0.00004720038,0.00007599408,0.0002117956,0.00005584913,0.8161114,0.0001998886,0.1799037,0.002221181,0.00004287524],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006004988,0.0001762771,0.9927036,0.0002493876,0.00005245697,0.00006507669,0.0001019541,0.0001004501,0.0005457253],"genre_scores_gemma":[0.4332442,0.001340595,0.556149,0.0004915618,0.0003814297,0.0009429813,0.0006364775,0.0001757477,0.006638028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01350106,"threshold_uncertainty_score":0.0714013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1619227687976239,"score_gpt":0.366346027452832,"score_spread":0.2044232586552081,"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."}}