{"id":"W1509210383","doi":"","title":"U.S. Agricultural Trade: Trends, Composition, Direction, and Policy","year":2011,"lang":"en","type":"book","venue":"University of North Texas Digital Library (University of North Texas)","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; International trade; Subsidy; European union; Commodity; Agricultural economics; International economics; Economics; Index (typography); Agricultural policy; Balance of trade; Business; Common Agricultural Policy; Product (mathematics); Geography; Market economy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007155137,0.0004937184,0.0002232605,0.002327858,0.001580481,0.004591655,0.0005111512,0.001583126,0.0164181],"category_scores_gemma":[0.001645721,0.000196384,0.0003113146,0.007609577,0.0006965545,0.002361686,0.0008270891,0.001322283,0.006513054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004706058,"about_ca_system_score_gemma":0.006264195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08872381,"about_ca_topic_score_gemma":0.1215883,"domain_scores_codex":[0.9993281,0.0001057383,0.00005218534,0.0001068363,0.000273692,0.0001335356],"domain_scores_gemma":[0.9989094,0.0001254247,0.0001878574,0.00003272136,0.0005489552,0.0001956603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001460986,0.0001201825,0.0425783,0.0007415639,0.00004249694,0.0002234066,0.0006601546,0.0002867449,0.0005329769,0.03398112,0.7278588,0.1928282],"study_design_scores_gemma":[0.00002885257,0.00005895339,0.09513582,0.001339595,0.00004438875,0.0002150154,0.002062618,0.0004662719,0.0002967741,0.005609201,0.8947138,0.00002874721],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.08394179,0.1547261,0.0008997345,0.2062591,0.004914054,0.0001356019,0.04756281,0.0009185019,0.5006424],"genre_scores_gemma":[0.5022179,0.201047,0.005464252,0.06514745,0.002803833,0.0002772438,0.04782852,0.000296343,0.1749173],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08872381,"threshold_uncertainty_score":0.1764147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044630744364598,"score_gpt":0.1516638852259818,"score_spread":0.1412175777823358,"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."}}