{"id":"W2024776329","doi":"10.5430/rwe.v4n1p82","title":"The Trend Analysis on China's Agricultural Natural Risks and Improvement of the Ability of Disaster Mitigation","year":2013,"lang":"en","type":"article","venue":"Research in World Economy","topic":"Technology and Security Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural disaster; Agriculture; China; Macro; Environmental planning; Emergency management; Natural resource economics; Environmental resource management; Geography; Environmental science; Computer science; Economic growth; Economics; Meteorology","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":[0.0009712998,0.0002472357,0.0001664789,0.00269312,0.0002571179,0.0006241575,0.0002322125,0.0001648017,0.001434093],"category_scores_gemma":[0.00242368,0.00007926236,0.0003541462,0.003867904,0.0001915175,0.0009095563,0.0002926563,0.0002789491,0.0001222641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008767554,"about_ca_system_score_gemma":0.001255798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0238318,"about_ca_topic_score_gemma":0.01757735,"domain_scores_codex":[0.9997094,0.00004812878,0.00002948022,0.00006239688,0.0001036543,0.00004690783],"domain_scores_gemma":[0.9991758,0.000153295,0.0001572122,0.00006145232,0.0004087917,0.000043406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002077927,0.00006278833,0.7621535,0.000308362,0.0002037779,0.0006366217,0.002121385,0.02090098,0.003468276,0.02414438,0.006641467,0.1791507],"study_design_scores_gemma":[0.0000103108,0.0001374558,0.9297996,0.00007016459,0.0001176577,0.0002355033,0.0012681,0.05015685,0.001249412,0.005952223,0.01096621,0.00003648704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726785,0.0009747291,0.01163161,0.0007837945,0.00005992691,0.00004192343,0.001995862,0.0001107584,0.01172276],"genre_scores_gemma":[0.9951317,0.0006939566,0.001743945,0.00002107486,0.00003521021,0.00001318669,0.000942235,0.000008886232,0.001409675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0238318,"threshold_uncertainty_score":0.04738611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02432767067193305,"score_gpt":0.2998654122054372,"score_spread":0.2755377415335042,"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."}}