{"id":"W2929086967","doi":"10.1111/cjag.12194","title":"The price of sanctions: An empirical analysis of German export losses due to the Russian agricultural ban","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"German; Sanctions; Agriculture; International trade; Economics; International economics; Business; Political science; Geography","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":[0.000890139,0.000283194,0.0004002219,0.001484246,0.0002924513,0.001214721,0.0002427111,0.0004251721,0.002172389],"category_scores_gemma":[0.002592329,0.000120526,0.0003956225,0.001699521,0.0006360466,0.00080113,0.000581636,0.0006627877,0.0004010752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005687838,"about_ca_system_score_gemma":0.0001842112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008191953,"about_ca_topic_score_gemma":0.004386318,"domain_scores_codex":[0.9996821,0.00007191037,0.0000260109,0.00005759708,0.00008460016,0.00007784683],"domain_scores_gemma":[0.997013,0.001266327,0.001221789,0.0001494049,0.0002014586,0.0001480611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000399309,0.0002999995,0.9620968,0.00007972684,0.0002954819,0.0006975229,0.001038507,0.01777696,0.001067519,0.002104317,0.001598713,0.0125452],"study_design_scores_gemma":[0.000009040436,0.0001167414,0.9853904,0.00001871133,0.00004543482,0.0001101135,0.001047768,0.01170937,0.0003288229,0.0003529572,0.0008544746,0.00001605641],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989047,0.00006244115,0.0000792365,0.00002464475,0.000001428036,0.000003152674,0.0002401326,0.000003077409,0.0006811551],"genre_scores_gemma":[0.9990053,0.00005299845,0.00002544744,0.000006011118,0.000002673994,0.000002093185,0.0006645172,0.000002226255,0.0002387824],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008191953,"threshold_uncertainty_score":0.01628852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02336824051741292,"score_gpt":0.2032529753795054,"score_spread":0.1798847348620925,"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."}}