{"id":"W2969926760","doi":"","title":"Проблемы пенсионной системы Китая: дилемма и решения","year":2016,"lang":"ru","type":"article","venue":"Administrative Consulting","topic":"Regional Socio-Economic Development Trends","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population ageing; Social security; Pension; China; Modernization theory; Old Age Security; Quarter (Canadian coin); Economic growth; Population; Retirement age; Political science; Development economics; Economics; Geography; Sociology; Demography; Birth rate; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001340781,0.0003519716,0.0002394751,0.001747041,0.001870012,0.003616144,0.0005454409,0.0009790754,0.02054314],"category_scores_gemma":[0.002459759,0.0003639679,0.0003414716,0.001652739,0.001737486,0.001417193,0.001174621,0.001263992,0.005294082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002199827,"about_ca_system_score_gemma":0.004169078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009987086,"about_ca_topic_score_gemma":0.01228024,"domain_scores_codex":[0.9986414,0.0002115977,0.00007879933,0.0001995482,0.0007038743,0.0001646486],"domain_scores_gemma":[0.9991735,0.0002289216,0.000118612,0.0001189152,0.0002622403,0.00009779514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007185224,0.00007548866,0.003074415,0.0003519542,0.00001768278,0.001094955,0.003762837,0.001038153,0.004487242,0.6157348,0.02410392,0.3461869],"study_design_scores_gemma":[0.00002066708,0.00006719113,0.007211578,0.0002863945,0.00002977528,0.001354089,0.001278819,0.001267632,0.004518491,0.07922417,0.9046801,0.00006113914],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08590581,0.03859867,0.08822511,0.01464545,0.003044272,0.0003775658,0.0007181978,0.0005602008,0.7679247],"genre_scores_gemma":[0.7000169,0.02797216,0.07979514,0.0008569308,0.001296306,0.0004959994,0.0003600312,0.0002541123,0.1889524],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02054314,"threshold_uncertainty_score":0.06872362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001256981978715,"score_gpt":0.3652415851081334,"score_spread":0.2651158869102619,"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."}}