{"id":"W2099121581","doi":"10.1080/10920277.2001.10595951","title":"Impacts on Economic Security Programs of Rapidly Shifting Demographics","year":2001,"lang":"en","type":"article","venue":"North American Actuarial Journal","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Baby boom; Life expectancy; Social security; Pension; Boom; Population; Old Age Security; Government (linguistics); Demographics; Business; Productivity; Population ageing; Economics; Labour economics; Health care; Economic growth; Birth rate; Fertility; Finance; Market economy; Medicine; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001809619,0.0002771257,0.0005248637,0.0004586333,0.0008288766,0.0002867555,0.0006878302,0.00007989315,0.0001337758],"category_scores_gemma":[0.0001917407,0.0002651069,0.0004388877,0.001095782,0.001221571,0.0003944875,0.00006032889,0.0006650348,0.00002661305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000231839,"about_ca_system_score_gemma":0.0004122106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007345585,"about_ca_topic_score_gemma":0.0378264,"domain_scores_codex":[0.9966127,0.000520792,0.0007458675,0.0003442916,0.0008660675,0.0009102834],"domain_scores_gemma":[0.9976608,0.0001604082,0.001193777,0.0003210628,0.0001664724,0.0004975286],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002048976,0.0002085638,0.8715017,0.000006852297,0.0001676868,0.00004115714,0.003406324,0.00009774195,0.000002727668,0.001365756,0.0003823804,0.1226142],"study_design_scores_gemma":[0.001167739,0.0009958333,0.9449852,0.00005682119,0.0001293301,0.00002480508,0.004989505,0.00006978312,0.000009738565,0.001289376,0.04572581,0.0005560846],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861793,0.00005374345,0.000122597,0.000660439,0.00124861,0.0004248419,0.00001239072,0.00008446766,0.01121365],"genre_scores_gemma":[0.995443,0.001842943,0.0004325108,0.0003460794,0.001877995,0.000008196044,0.0000070156,0.00002946908,0.00001272877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1220581,"threshold_uncertainty_score":0.9999801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01787667346214807,"score_gpt":0.2971700920675107,"score_spread":0.2792934186053626,"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."}}