{"id":"W2770794764","doi":"10.1111/cjag.12157","title":"The Effects of Pricing Canadian Livestock Emissions","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"U.S. Environmental Protection Agency","keywords":"Tonne; Subsidy; Greenhouse gas; Carbon tax; Economics; Welfare economics; Unit (ring theory); Economy; Agricultural economics; Mathematics; Engineering; Waste management; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.000746322,0.0002987748,0.0007252513,0.0003350333,0.001515105,0.0003782024,0.001334118,0.0001872232,0.0002290915],"category_scores_gemma":[0.0006691176,0.0002633587,0.0003661228,0.00005122719,0.000336645,0.0008659287,0.00004723261,0.0003331313,0.0001493561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002723341,"about_ca_system_score_gemma":0.0007204916,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4819378,"about_ca_topic_score_gemma":0.9593813,"domain_scores_codex":[0.9973096,0.00002315503,0.00141888,0.0003633203,0.000008597322,0.0008764899],"domain_scores_gemma":[0.9948046,0.0001959288,0.002405631,0.0006640293,0.00007615706,0.001853709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003191077,0.00003784144,0.5980496,0.0001559094,0.0008830382,0.00007606344,0.00391979,0.003157273,0.0001224907,0.3770437,0.01048467,0.006037701],"study_design_scores_gemma":[0.0007249902,0.0002620238,0.9489501,0.0001091823,0.00004151226,0.0001349651,0.0007526434,0.0001219609,0.0001458611,0.01146012,0.03684618,0.0004505264],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813561,0.001646792,0.000008298905,0.004134198,0.003062638,0.0003195746,0.0001710955,0.000003395503,0.009297921],"genre_scores_gemma":[0.9966059,0.0005152012,0.00013189,0.000175627,0.0004664427,0.00001296457,0.00001513673,0.00003071306,0.002046153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4774435,"threshold_uncertainty_score":0.9999819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04358137407409245,"score_gpt":0.1668442262202896,"score_spread":0.1232628521461971,"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."}}