{"id":"W3160243220","doi":"","title":"COVID-19 and the agri-food system in the United States and Canada","year":2020,"lang":"en","type":"article","venue":"Iowa State University Digital Repository (Iowa State University)","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Diversification (marketing strategy); Business; Toll; Flexibility (engineering); Pandemic; Distribution (mathematics); Production (economics); Economics; Coronavirus disease 2019 (COVID-19); Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002460876,0.0002962453,0.0004543981,0.0004408225,0.0005621714,0.000290754,0.0006589255,0.00007655013,0.000004906296],"category_scores_gemma":[0.0002797032,0.0002771806,0.00008407564,0.001006147,0.0005033859,0.0007575723,0.0003727852,0.0003572521,0.000007014597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001461909,"about_ca_system_score_gemma":0.000618665,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3426513,"about_ca_topic_score_gemma":0.09192361,"domain_scores_codex":[0.9982564,0.000170421,0.0003512573,0.0006089103,0.0001470149,0.0004660023],"domain_scores_gemma":[0.9978701,0.0007803227,0.0003610883,0.0003354912,0.00006323502,0.0005897496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006903149,0.0003084384,0.5985771,0.002293146,0.001754914,0.01461091,0.1140567,0.02893982,0.00003855276,0.2023433,0.02913693,0.001036991],"study_design_scores_gemma":[0.008901129,0.0003365633,0.01815042,0.00005949899,0.00008030895,0.0001107784,0.07243549,0.006950877,0.00001902839,0.001269205,0.8907062,0.0009804829],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810807,0.0002009257,0.001179138,0.003834562,0.0001310413,0.000567255,0.001283549,0.0000959477,0.0116269],"genre_scores_gemma":[0.9950607,0.0003830731,0.00001062615,0.002106269,0.00001944357,2.593222e-7,0.00004580408,0.00001824167,0.002355523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8615693,"threshold_uncertainty_score":0.9999681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01919967774900152,"score_gpt":0.166513836254819,"score_spread":0.1473141585058175,"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."}}