{"id":"W2334483474","doi":"10.1093/ajae/aav065","title":"Bayesian Estimation of Possibly Similar Yield Densities: Implications for Rating Crop Insurance Contracts","year":2015,"lang":"en","type":"article","venue":"American Journal of Agricultural Economics","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Ministry of Agriculture, Food and Rural Affairs","funders":"","keywords":"Crop insurance; Actuarial science; Sample (material); Insurance policy; Government (linguistics); Agriculture; Yield (engineering); Econometrics; Economics; Nonparametric statistics; Business; 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":[0.01793226,0.0006940988,0.001869087,0.001053361,0.000857982,0.002074823,0.002368493,0.001867049,0.002053316],"category_scores_gemma":[0.09887901,0.0007613349,0.001232604,0.001154648,0.00144569,0.003360757,0.001867954,0.002878173,0.0002394393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001900444,"about_ca_system_score_gemma":0.001329269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01454685,"about_ca_topic_score_gemma":0.01059592,"domain_scores_codex":[0.9919486,0.005412747,0.0002732231,0.001056013,0.001076176,0.0002330918],"domain_scores_gemma":[0.9447233,0.0466142,0.002665713,0.003409808,0.002046178,0.0005408217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000369253,0.0003264618,0.02715549,0.0001199182,0.0002943131,0.0002011022,0.0006065282,0.7834091,0.001221509,0.08173943,0.001759748,0.102797],"study_design_scores_gemma":[0.00003521024,0.00006753692,0.003173897,0.0000181804,0.00001994616,0.00005793103,0.00006466347,0.9683266,0.000335098,0.02740718,0.0004701925,0.00002357685],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.24942,0.0005718067,0.744324,0.001156616,0.00004291332,0.0003102616,0.0002234353,0.0002477684,0.003703154],"genre_scores_gemma":[0.8153699,0.0002293978,0.1823149,0.0002273577,0.0000523944,0.0001491274,0.0004039078,0.00003425651,0.001218687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01793226,"threshold_uncertainty_score":0.094836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045869158979734,"score_gpt":0.2354578095480556,"score_spread":0.2149991179582583,"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."}}