{"id":"W3015605702","doi":"10.1016/j.insmatheco.2020.03.009","title":"Calibrating Gompertz in reverse: What is your longevity-risk-adjusted global age?","year":2020,"lang":"en","type":"article","venue":"Insurance Mathematics and Economics","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Schulich School of Business, York University","keywords":"Longevity risk; Longevity; Salience (neuroscience); Gompertz function; Metric (unit); Pension; Hazard; Demography; Actuarial science; Salient; Hazard ratio; Gerontology; Economics; Psychology; Medicine; Computer science; Biology; Sociology; Statistics; Finance; Operations management; Mathematics; Cognitive psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003912537,0.0004713916,0.000614277,0.001290219,0.0003974565,0.00178344,0.001176679,0.001051239,0.002743525],"category_scores_gemma":[0.02347018,0.0002759939,0.0007528899,0.0009726569,0.001182939,0.003224363,0.001820206,0.001660871,0.0004814003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008342484,"about_ca_system_score_gemma":0.0007502038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006268669,"about_ca_topic_score_gemma":0.004579291,"domain_scores_codex":[0.9993833,0.0002721929,0.00002367377,0.0002061519,0.00006454324,0.00005003303],"domain_scores_gemma":[0.9969059,0.001972854,0.0004000081,0.000375571,0.0002262675,0.0001194384],"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":[0.0001179189,0.00006265932,0.08406861,0.0001221991,0.0001657973,0.0001956455,0.0008946277,0.4620342,0.0005056917,0.339826,0.005884648,0.106122],"study_design_scores_gemma":[0.0000267294,0.00008206769,0.01609517,0.0001407206,0.00005226793,0.000240982,0.0005553865,0.4734715,0.0007566197,0.494536,0.01396187,0.00008070586],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.194616,0.001222484,0.7881417,0.004264749,0.0003621366,0.00006109022,0.001076296,0.0003951708,0.009860286],"genre_scores_gemma":[0.8694533,0.0008306034,0.1257498,0.0005225821,0.0001687093,0.00007570571,0.0008550826,0.0001480008,0.002196275],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006268669,"threshold_uncertainty_score":0.02069175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605444179761106,"score_gpt":0.2824059208799021,"score_spread":0.236351479082291,"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."}}