{"id":"W3151764565","doi":"10.1111/cjag.12277","title":"COVID‐19 and the Canadian cattle/beef sector: A second look","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Beef cattle; Quarter (Canadian coin); Agricultural economics; Business; Production (economics); Divergence (linguistics); 2019-20 coronavirus outbreak; Supply chain; Economics; Agricultural science; Animal science; Geography; Biology; Marketing; Outbreak","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":[0.001029486,0.0003169299,0.0003455089,0.001553261,0.002853153,0.0045391,0.0007315717,0.001187326,0.01101397],"category_scores_gemma":[0.002694018,0.0001493426,0.0005360314,0.00297781,0.001688402,0.001312595,0.001397275,0.002134818,0.0003451115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05268648,"about_ca_system_score_gemma":0.06082418,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.988022,"about_ca_topic_score_gemma":0.990968,"domain_scores_codex":[0.9987829,0.00008248185,0.00001281677,0.00005218851,0.0003762252,0.0006932463],"domain_scores_gemma":[0.9977478,0.0002032968,0.000280551,0.00004588455,0.001165345,0.0005569672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004599666,0.0002685494,0.429697,0.0005385016,0.0002391555,0.001575464,0.004144273,0.009811716,0.001037389,0.1808718,0.2840714,0.0872848],"study_design_scores_gemma":[0.00004354168,0.0001321832,0.6287152,0.000882509,0.0001404124,0.0002067254,0.02862678,0.009543514,0.0005684259,0.02059201,0.3103456,0.0002030419],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4005709,0.03804696,0.001300244,0.3153406,0.001168548,0.0001220496,0.01244833,0.00007838818,0.230924],"genre_scores_gemma":[0.9492845,0.01808007,0.0005734796,0.009133619,0.0003031511,0.00001632276,0.002179279,0.00002240182,0.02040729],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05268648,"threshold_uncertainty_score":0.382269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03952351091016755,"score_gpt":0.1877257982712619,"score_spread":0.1482022873610944,"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."}}