{"id":"W4362671242","doi":"10.1016/j.chieco.2023.101972","title":"The optimal delayed retirement age in aging China: Determination and impact analysis","year":2023,"lang":"en","type":"article","venue":"China Economic Review","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Retirement age; Consumption (sociology); Economics; Context (archaeology); Productivity; Population; Overlapping generations model; Wage; Population ageing; China; Labour economics; Demographic economics; Macroeconomics; Pension; Demography; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002911186,0.0004554793,0.0008996243,0.003427193,0.000281313,0.001015039,0.0007166851,0.0004503699,0.002375898],"category_scores_gemma":[0.003880822,0.00024956,0.0009985642,0.002435735,0.0004832549,0.0007272332,0.0007961516,0.0006774621,0.0001117903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003033817,"about_ca_system_score_gemma":0.004590566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05523661,"about_ca_topic_score_gemma":0.05910384,"domain_scores_codex":[0.9994609,0.0001831269,0.00004202061,0.00006285103,0.0001394301,0.0001117348],"domain_scores_gemma":[0.9987525,0.0004689711,0.0001590298,0.00004908144,0.0005010191,0.00006943013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007275085,0.0003121464,0.218718,0.006632296,0.001703308,0.000569262,0.0007228858,0.1178149,0.0006387171,0.1882638,0.03426747,0.4296296],"study_design_scores_gemma":[0.0002138522,0.0005978167,0.6783102,0.003962149,0.00438535,0.0003620453,0.002369902,0.1565897,0.0007764754,0.06181211,0.09043684,0.0001836623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4444407,0.5045712,0.0115279,0.01078265,0.001063537,0.0001842561,0.003121329,0.00003948537,0.02426905],"genre_scores_gemma":[0.8636551,0.1302058,0.00125503,0.0002230249,0.0004995006,0.00005458538,0.0008957757,0.000008718214,0.003202475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05523661,"threshold_uncertainty_score":0.1098302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.118687457230017,"score_gpt":0.4387612886117105,"score_spread":0.3200738313816935,"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."}}