{"id":"W1568169880","doi":"10.1108/afr-01-2014-0001","title":"Hedging weather risk for corn production in Northeastern China","year":2014,"lang":"en","type":"article","venue":"Agricultural Finance Review","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Crop insurance; Hedge; Revenue; Production (economics); Basis risk; Risk management; Yield (engineering); Extreme weather; Agricultural economics; Actuarial science; Economics; Environmental science; Econometrics; Agriculture; Business; Agricultural science; Climate change; Finance; Geography","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":[0.001008733,0.0003661706,0.000248661,0.0009027696,0.000242515,0.000495158,0.0003784939,0.0002018656,0.0004471323],"category_scores_gemma":[0.001176102,0.0001028709,0.0004307196,0.0011278,0.0003091399,0.0004680681,0.0003451069,0.0001474765,0.00002862207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00217081,"about_ca_system_score_gemma":0.001078028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03785365,"about_ca_topic_score_gemma":0.03846565,"domain_scores_codex":[0.9997808,0.0000527583,0.00001543386,0.00003502899,0.00008152419,0.00003446902],"domain_scores_gemma":[0.9995499,0.0001203431,0.0001816362,0.00003251587,0.0000810577,0.00003460468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000297545,0.0001197231,0.6145411,0.00040286,0.0003755781,0.001047416,0.0005807395,0.2546256,0.009164191,0.006277959,0.001305811,0.1112615],"study_design_scores_gemma":[0.00001307168,0.0002194264,0.77942,0.00004157782,0.0002092401,0.0001251145,0.0004495289,0.2129187,0.002303313,0.002206826,0.002059696,0.00003352953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960796,0.001354481,0.001476569,0.000122184,0.000007081157,0.000009090418,0.00007564083,0.000008423529,0.0008669114],"genre_scores_gemma":[0.9987561,0.0007398389,0.0002220645,0.000005105874,0.000005079027,0.000001790565,0.00005184067,0.000001163145,0.0002168904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03785365,"threshold_uncertainty_score":0.07526666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009820536540986666,"score_gpt":0.2167594818575293,"score_spread":0.2069389453165426,"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."}}