{"id":"W2148559137","doi":"10.1111/cjag.12003","title":"Transfer Efficiency Analysis of Margin‐Based Programs","year":2013,"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":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of Alberta","funders":"","keywords":"Production (economics); Incentive; Transfer payment; Payment; Moral hazard; Margin (machine learning); Business; Government (linguistics); Differential (mechanical device); Gross margin; Agriculture; Economics; Agricultural economics; Public economics; Finance; Microeconomics; Market economy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003838496,0.0002700463,0.0005540242,0.001594015,0.0003835742,0.001042678,0.0008217456,0.0004452492,0.01227569],"category_scores_gemma":[0.01696058,0.0001479724,0.0005570546,0.001370316,0.0008573826,0.00127075,0.001055976,0.0006579214,0.0004358804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003490549,"about_ca_system_score_gemma":0.001674575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0110238,"about_ca_topic_score_gemma":0.007075323,"domain_scores_codex":[0.9979393,0.0008411849,0.00006385629,0.0001484712,0.0004856742,0.0005213834],"domain_scores_gemma":[0.9859462,0.009778845,0.001550944,0.0009300162,0.001435391,0.0003584961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001099121,0.0009850217,0.04624877,0.0003286902,0.0002420968,0.0002159271,0.0004780282,0.6634757,0.004700426,0.1527809,0.003943711,0.1255016],"study_design_scores_gemma":[0.0002094256,0.001262427,0.1101852,0.0001130506,0.0002634995,0.0001772747,0.0009956275,0.8169314,0.00655474,0.05495014,0.008315674,0.00004156622],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9175752,0.0003625485,0.03359773,0.0004227974,0.0000110292,0.000283191,0.0004600667,0.00009098337,0.04719636],"genre_scores_gemma":[0.9936884,0.00007146805,0.001925656,0.00002993057,0.000006653139,0.0000535373,0.0001250019,0.00001729006,0.004082108],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01227569,"threshold_uncertainty_score":0.04106629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01653898323193284,"score_gpt":0.1504122694819926,"score_spread":0.1338732862500598,"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."}}