{"id":"W2804292829","doi":"10.5539/ijsp.v7n2p91","title":"Assessing Impacts on Mortality of Lifestyle Factors: Allowing for Model Uncertainty","year":2018,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cohort; Demography; Medicine; Attributable risk; Population; Regression analysis; Cohort study; Proportional hazards model; Environmental health; Statistics; Mathematics; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002423924,0.0001009034,0.0002140328,0.00009889639,0.0001763554,0.0001548482,0.0002758935,0.00005161114,0.00002088652],"category_scores_gemma":[0.001351892,0.00008534492,0.0001012179,0.00007061669,0.0004414188,0.0003315809,0.00003815553,0.0001083213,2.635188e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001344015,"about_ca_system_score_gemma":0.0002392357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007151754,"about_ca_topic_score_gemma":0.0008515707,"domain_scores_codex":[0.9982583,0.0001284325,0.0005478965,0.0001486203,0.0007445875,0.0001721831],"domain_scores_gemma":[0.9972534,0.0004472628,0.0005328573,0.0001033565,0.001558264,0.000104853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002974396,0.0006398956,0.6169596,0.0001594679,0.0006461854,0.000008779238,0.00814761,0.003238245,0.0001863116,0.3517133,0.000937485,0.0170656],"study_design_scores_gemma":[0.0007997379,0.0004002125,0.5581669,0.0001836632,0.0001087135,0.000001201605,0.001142973,0.01251496,0.0002032817,0.4246649,0.001599751,0.0002136853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9200105,0.00001948566,0.07732481,0.0002458854,0.0006722377,0.0002079962,0.0002901749,0.000006328728,0.001222606],"genre_scores_gemma":[0.9803437,0.00006198925,0.01920467,0.00007961971,0.0002827055,0.000002245272,0.00000804034,0.000006098217,0.00001091606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07295161,"threshold_uncertainty_score":0.3480265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06492897661188213,"score_gpt":0.3988533326250858,"score_spread":0.3339243560132036,"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."}}