{"id":"W2093597895","doi":"10.5539/mas.v3n1p71","title":"Study on Public Agricultural Insurance in China——Based on Xinjiang Mode","year":2008,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Regional Development and Environment","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Xi'an Polytechnic University","keywords":"China; Agriculture; Business; Mode (computer interface); Work (physics); Public health insurance; Insurance policy; Agricultural economics; Key person insurance; Actuarial science; Economic growth; Economics; Health insurance; Geography; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0008620646,0.0003779846,0.0003898742,0.002037162,0.002054221,0.0008969961,0.0006062892,0.0004350726,0.005107423],"category_scores_gemma":[0.001033025,0.0004007948,0.0004667168,0.002344657,0.0006265512,0.0009018785,0.001080286,0.0005046129,0.0004933602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001776204,"about_ca_system_score_gemma":0.001700756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05101976,"about_ca_topic_score_gemma":0.07802699,"domain_scores_codex":[0.9990696,0.0001704285,0.00005431245,0.0001371141,0.0001730627,0.0003955068],"domain_scores_gemma":[0.9991308,0.0001284836,0.0001948433,0.00005678337,0.0001303223,0.0003588457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007670058,0.0003241495,0.9823132,0.00003089644,0.00002620704,0.000526164,0.01117628,0.00006048174,0.0005395372,0.0004107807,0.000352965,0.004162712],"study_design_scores_gemma":[0.000004632942,0.0001182554,0.9885776,0.00001069822,0.00001060185,0.0001361152,0.009937991,0.0001821327,0.0000762809,0.00004819269,0.0008907376,0.000006809965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999029,0.00003708582,0.00001953588,0.00004366948,0.000002104969,0.00001625466,0.00007234143,7.961079e-7,0.0007792511],"genre_scores_gemma":[0.9989281,0.00006802365,0.00002892208,0.00004395905,0.000004767387,0.00001906777,0.0001313454,9.999716e-7,0.0007747765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05101976,"threshold_uncertainty_score":0.1014456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04265045180046038,"score_gpt":0.2723544741476637,"score_spread":0.2297040223472034,"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."}}