{"id":"W3126100301","doi":"","title":"Greener Pastures: Resetting the Age of Eligibility for Social Security Based on Actuarial Science","year":2017,"lang":"en","type":"article","venue":"C.D. Howe Institute Commentary","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social security; Life expectancy; Pension; Old Age Security; Baby boom; Dependency ratio; Context (archaeology); Retirement age; Notice; Legislation; Demographic economics; Social Security Act; Economics; Demography; Fertility; Political science; Population; Geography; Birth rate; Sociology; Finance; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.005177293,0.0002065174,0.0002905264,0.0001368239,0.009185366,0.0004133109,0.002329126,0.00009871056,0.00002090421],"category_scores_gemma":[0.0008044694,0.000165921,0.0002601938,0.0002747906,0.006025521,0.0007123319,0.0003817483,0.0002801261,0.000002408709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002514178,"about_ca_system_score_gemma":0.0002886868,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008980896,"about_ca_topic_score_gemma":0.01427707,"domain_scores_codex":[0.997158,0.0002349135,0.000377673,0.0005114674,0.001093053,0.0006249227],"domain_scores_gemma":[0.9979454,0.0002432778,0.0004096437,0.001089677,0.0002166307,0.00009532051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001984421,0.002876354,0.3500347,0.0005400144,0.0004550576,0.0000943358,0.05187735,0.0003421327,0.001046044,0.2488123,0.2626263,0.07931101],"study_design_scores_gemma":[0.002858318,0.0002212337,0.3471356,0.000136157,0.0001446755,2.349085e-7,0.003694973,0.0004724073,0.0008622516,0.02159101,0.6222686,0.0006145241],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9034104,0.00003567015,0.0005998899,0.05646516,0.004679099,0.00231158,0.0002381207,0.00009291103,0.03216716],"genre_scores_gemma":[0.9929877,0.00002195183,0.0004414279,0.005205052,0.001192318,0.00008591524,0.00003376107,0.00001156937,0.00002034192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3596423,"threshold_uncertainty_score":0.9976184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06148105730243573,"score_gpt":0.3993573106878309,"score_spread":0.3378762533853952,"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."}}