{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001619266,0.0005074051,0.001325541,0.0007606995,0.0008965739,0.0007273515,0.0008654675,0.0003519293,0.006047948],"category_scores_gemma":[0.001816809,0.0004562325,0.0004783124,0.0003293224,0.0005786534,0.0007851397,0.00006234989,0.000780965,0.0002790018],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01000247,"about_ca_system_score_gemma":0.01031011,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7480351,"about_ca_topic_score_gemma":0.9988824,"domain_scores_codex":[0.995919,0.0000904903,0.001754232,0.0007331818,0.00001509042,0.001488031],"domain_scores_gemma":[0.9900304,0.0004418138,0.001273151,0.0005913855,0.0002356395,0.007427617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001545572,0.00003639472,0.07776929,0.0003415362,0.00170495,0.001125487,0.01580303,0.006708481,0.00002190034,0.7990304,0.09635389,0.0009501332],"study_design_scores_gemma":[0.005059931,0.0001691341,0.1200671,0.0000611989,0.0001045501,0.007419874,0.002889585,0.0002452348,0.00003696411,0.05266955,0.8099808,0.001296092],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.933674,0.005636469,0.00001247212,0.04127283,0.002332073,0.0003911574,0.001334133,0.00001213452,0.01533471],"genre_scores_gemma":[0.9817677,0.0002925392,0.0001082082,0.01244067,0.0009028603,0.00001786555,0.00007224317,0.00005186809,0.004346059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7463608,"threshold_uncertainty_score":0.9997889,"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."}}