{"id":"W2342618458","doi":"10.5539/ijef.v8n5p39","title":"Impact of Russian Non-Tariff Measures on European Union Agricultural Exports","year":2016,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science Foundation of Ministry of Education of China; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China","keywords":"Tariff; Agriculture; European union; International trade; China; International economics; Business; Order (exchange); Economics; Political science; Geography; Finance","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001088329,0.0003628901,0.0003219048,0.0009161396,0.0003120486,0.001648752,0.0002448754,0.0002404071,0.002649543],"category_scores_gemma":[0.003144182,0.00008717452,0.0007661529,0.0009578499,0.0004869728,0.000605548,0.0008599705,0.0004569579,0.0003395974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002666,"about_ca_system_score_gemma":0.0004603293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008258539,"about_ca_topic_score_gemma":0.003139981,"domain_scores_codex":[0.9992817,0.0002617837,0.00006056696,0.0001142073,0.0001738386,0.0001080557],"domain_scores_gemma":[0.998535,0.0004082205,0.0006204613,0.0001581859,0.000212753,0.0000653911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002104084,0.00046761,0.7222239,0.0006139757,0.00146479,0.00322609,0.00106446,0.07252886,0.01500005,0.05898213,0.008353243,0.1139707],"study_design_scores_gemma":[0.00005985157,0.0003738104,0.9516453,0.0001012053,0.0003235104,0.0004959379,0.001175153,0.01738165,0.007084228,0.003711627,0.01760917,0.00003846431],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823743,0.0007559141,0.0005172832,0.000309841,0.00003356081,0.000006497405,0.0003357791,0.00006128837,0.01560558],"genre_scores_gemma":[0.9974924,0.0003356809,0.000112717,0.0000474295,0.00001144488,0.000002366143,0.0003554415,0.00001695409,0.001625607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008258539,"threshold_uncertainty_score":0.01642096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387077706187983,"score_gpt":0.2159051157345407,"score_spread":0.1820343386726609,"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."}}