{"id":"W3124287010","doi":"","title":"An Assessment of the Canadian Federal-Provincial Crop Production Insurance Program under Future Climate Change Scenarios in Ontario","year":2013,"lang":"en","type":"article","venue":"2013 Annual Meeting, August 4-6, 2013, Washington, D.C.","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Crop insurance; Yield (engineering); Climate change; Economics; Production (economics); Environmental science; Natural resource economics; Crop yield; Agricultural economics; Agriculture; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000785225,0.0002323363,0.000198476,0.0006245435,0.001418405,0.001167629,0.00085811,0.0003576684,0.001438797],"category_scores_gemma":[0.002347022,0.000187501,0.0005025913,0.001162156,0.0004279124,0.0004650337,0.0004696652,0.000303115,0.00007813301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05808879,"about_ca_system_score_gemma":0.0225999,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9932904,"about_ca_topic_score_gemma":0.9958402,"domain_scores_codex":[0.999506,0.00006220163,0.0000182545,0.00005118494,0.0001978429,0.0001645596],"domain_scores_gemma":[0.9990396,0.0001212428,0.0001416685,0.00003339368,0.0004797305,0.0001842941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004957624,0.00007656468,0.7765791,0.0000997953,0.0001751139,0.0006309447,0.00135019,0.1802184,0.002691115,0.007748797,0.006569665,0.0233645],"study_design_scores_gemma":[0.00003824367,0.00007607925,0.7509946,0.0000226176,0.00006696826,0.00007694595,0.002733984,0.2377801,0.0007418417,0.0008859879,0.006524211,0.00005833287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898062,0.0001211473,0.0005288678,0.0007666455,0.000007889265,0.00004577024,0.002782916,0.00003851125,0.005902111],"genre_scores_gemma":[0.9975591,0.00009817981,0.0003851807,0.0000214042,0.000001757777,0.000008216247,0.0008658334,0.000003854519,0.001056499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05808879,"threshold_uncertainty_score":0.4214657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137511519186874,"score_gpt":0.2562467463223163,"score_spread":0.2424955944036289,"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."}}