{"id":"W2749746534","doi":"10.1111/cjag.12145","title":"Canadian Agricultural Business Risk Management Programs: Implications for Farm Wealth and Environmental Stewardship","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Livestock and Meat Agency; University of Alberta","funders":"Alberta Agriculture and Forestry","keywords":"Incentive; Net present value; Business; Agriculture; Cropping; Environmental economics; Subsidy; Agricultural science; Agricultural economics; Economics; Production (economics); Environmental science; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003836224,0.0004736489,0.0006087067,0.00009516479,0.002746821,0.0008380248,0.001280298,0.0002348398,0.00005809632],"category_scores_gemma":[0.00007956234,0.0002136213,0.0003085141,0.000116261,0.0002800368,0.0007480106,0.00007066614,0.0002554794,0.00001384437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001836859,"about_ca_system_score_gemma":0.0002528766,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4491791,"about_ca_topic_score_gemma":0.9941943,"domain_scores_codex":[0.9972143,0.00004569508,0.0008088642,0.0006131791,0.00002811971,0.001289829],"domain_scores_gemma":[0.9952741,0.00009958099,0.001193082,0.0002284043,0.0002122865,0.00299258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009681033,0.000101566,0.5986891,0.000119494,0.00067087,0.00006400089,0.001206937,0.0008259515,0.001100524,0.01894125,0.003805747,0.3743778],"study_design_scores_gemma":[0.0004450111,0.0003114188,0.9587587,0.00006590356,0.0001212067,0.0004098754,0.00380374,0.00001059347,0.00002105626,0.001082261,0.03440737,0.0005628954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852825,0.0005235947,0.000001045429,0.009952378,0.0008074589,0.000946518,0.001521019,0.00001290861,0.0009526052],"genre_scores_gemma":[0.9960867,0.001091761,0.0002538594,0.0001633177,0.00099034,0.00006743101,0.0004020892,0.000005994318,0.0009385165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5450151,"threshold_uncertainty_score":0.9985515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01957429617333907,"score_gpt":0.1774631674125384,"score_spread":0.1578888712391994,"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."}}