{"id":"W4407312430","doi":"10.1002/agr.22030","title":"Assessing the Impacts of Maritime Freight Rates on Global Beef Trade","year":2025,"lang":"en","type":"article","venue":"Agribusiness","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic Research Service; National Institute of Food and Agriculture; U.S. Department of Agriculture","keywords":"Economics; International trade; Business; Econometrics","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":[],"consensus_categories":[],"category_scores_codex":[0.0002907637,0.0001589256,0.0003686956,0.0000757783,0.0001218986,0.0001735939,0.0003416472,0.0001093032,0.00009777505],"category_scores_gemma":[0.00009579712,0.000134741,0.0001163619,0.0005207328,0.00008273062,0.0003216147,0.00005924654,0.0001084482,0.0001092524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000125249,"about_ca_system_score_gemma":0.00004211223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004910153,"about_ca_topic_score_gemma":0.00004626459,"domain_scores_codex":[0.9988811,0.0000133464,0.0005129448,0.0002788429,0.00002604877,0.0002877008],"domain_scores_gemma":[0.9992725,0.00009156979,0.000235706,0.0003376382,0.00002124516,0.0000413267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001916484,0.0001671226,0.2534072,0.0000739695,0.0001162163,0.00000388714,0.00004032732,0.0002938976,0.00003838423,0.7374235,0.006565657,0.001850657],"study_design_scores_gemma":[0.0004195917,0.00001943824,0.9313318,0.00006085293,0.00001233375,0.000003333244,0.0000731167,0.0005169066,0.0003094519,0.05192547,0.01516567,0.0001620298],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8962747,0.00173666,0.0005289602,0.007230316,0.0008913989,0.0001743355,0.0002320626,0.00003081438,0.09290073],"genre_scores_gemma":[0.9983413,0.0001128838,0.0001116988,0.001201218,0.00008377816,0.000006389823,0.00002394724,0.000008014691,0.0001107302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.685498,"threshold_uncertainty_score":0.5494578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03995060486682146,"score_gpt":0.2585677229543639,"score_spread":0.2186171180875424,"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."}}