{"id":"W2187581550","doi":"10.2139/ssrn.2617350","title":"Lifetime Ruin Under Uncertain Hazard Rate","year":2015,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Economics; Actuarial science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01074526,0.0002067322,0.0002489444,0.0002155293,0.0007154478,0.0002474554,0.000665393,0.0001247798,0.00009392809],"category_scores_gemma":[0.0001909119,0.0001928058,0.0001990294,0.0006028067,0.0002849482,0.0004050884,0.00006280792,0.001390652,0.0002992891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001831024,"about_ca_system_score_gemma":0.004438581,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002043797,"about_ca_topic_score_gemma":0.02531192,"domain_scores_codex":[0.9945076,0.0008171554,0.0003748473,0.0002906655,0.0009020171,0.00310779],"domain_scores_gemma":[0.9988599,0.00006181925,0.0002333618,0.0002524833,0.0002562623,0.0003361959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008065159,0.0001359641,0.02114605,0.000004532357,0.0003446379,0.00002330423,0.002628292,0.0006638074,0.00001867423,0.9572191,0.006855104,0.01087986],"study_design_scores_gemma":[0.001164458,0.0002448724,0.006406754,0.00001961689,0.00008394796,0.00003057948,0.02595398,0.00007909053,0.00001069083,0.8486545,0.1169224,0.0004291053],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7963847,0.009085117,0.01407695,0.02396623,0.003316666,0.0009713118,0.000007388614,0.0003931186,0.1517985],"genre_scores_gemma":[0.9835594,0.004067479,0.000125111,0.0006689678,0.001047317,0.00001079787,0.000003075176,0.00003010737,0.01048771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1871747,"threshold_uncertainty_score":0.9924736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706839816283165,"score_gpt":0.3094915146190526,"score_spread":0.2824231164562209,"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."}}