{"id":"W2769850043","doi":"","title":"Chapter 8. Risk and Insurance in Transition:: Perspectives from Zouping County, China","year":2001,"lang":"en","type":"article","venue":"","topic":"China's Socioeconomic Reforms and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"China; Transition (genetics); Actuarial science; Business; Political science; Law","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":[0.0004403877,0.0002059312,0.0001801631,0.0009903815,0.004726144,0.003360997,0.0005281274,0.0009381147,0.003234349],"category_scores_gemma":[0.0004103174,0.00009259368,0.0002467668,0.002385491,0.001771186,0.001156611,0.001314136,0.0009978543,0.0000746196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009382475,"about_ca_system_score_gemma":0.009884936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2947958,"about_ca_topic_score_gemma":0.5030594,"domain_scores_codex":[0.999755,0.00006280522,0.00000557419,0.00001874505,0.00003195332,0.0001259671],"domain_scores_gemma":[0.9997512,0.00007536246,0.00002688951,0.000007680396,0.00005014686,0.0000887098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009654399,0.0002050343,0.1636237,0.0005036065,0.00005908278,0.00266072,0.2013545,0.002157998,0.001017569,0.5311726,0.04590775,0.05124088],"study_design_scores_gemma":[0.00003543559,0.0001251327,0.3287066,0.0006253027,0.00007957291,0.0003546851,0.3499658,0.002484916,0.0006657414,0.03805389,0.2788367,0.00006626582],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8305659,0.01574999,0.0004688436,0.05523176,0.0002500225,0.0000576199,0.000538076,0.00001003527,0.09712767],"genre_scores_gemma":[0.9811576,0.005966108,0.0001976599,0.002130698,0.0001155525,0.0000233517,0.0001173172,0.000003306155,0.01028847],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2947958,"threshold_uncertainty_score":0.5861599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007473851566443246,"score_gpt":0.2425015114411235,"score_spread":0.2350276598746803,"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."}}