{"id":"W2604472206","doi":"10.54648/euro2018008","title":"Food Fraud: Protecting European Consumers Through Effective Deterrence","year":2018,"lang":"en","type":"article","venue":"European Public Law","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council; Queen's University; Queen's University Belfast","keywords":"European union; Legislature; Deterrence (psychology); Member states; Deterrence theory; Food safety; Political science; Member state; Business; Law; International trade","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009658402,0.0001717896,0.00009731544,0.00003509492,0.0004831863,0.00020736,0.0004343356,0.0000431017,0.00009850597],"category_scores_gemma":[0.0003773345,0.0001672498,0.00007745613,0.0001729195,0.0004645427,0.00002182462,0.0001913151,0.0001579807,0.001198729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001281072,"about_ca_system_score_gemma":0.00002775855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007747188,"about_ca_topic_score_gemma":0.00004104527,"domain_scores_codex":[0.9977522,0.0009845832,0.0002811929,0.0005429288,0.0001480388,0.0002910556],"domain_scores_gemma":[0.9987721,0.00001979554,0.0001789471,0.000651887,0.0002804032,0.00009680527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001173999,0.0003619919,0.001372321,0.00006311831,0.0003984889,0.00001137348,0.002114516,0.000002217801,0.8403307,0.08952872,0.02133654,0.04436264],"study_design_scores_gemma":[0.0004462358,0.0005236334,0.0030059,0.00001576753,0.00001083686,0.00002258606,0.0001346136,0.000007954598,0.2067311,0.00005847239,0.78877,0.0002729492],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2882429,0.0001856328,0.03104,0.0006894322,0.0009678144,0.0007619397,0.00002239715,0.0002032025,0.6778867],"genre_scores_gemma":[0.9963092,0.000008823173,0.0008711856,0.0009771929,0.0004948052,0.00002209954,0.00007661514,0.00005942476,0.001180628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7674334,"threshold_uncertainty_score":0.999579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329502483594456,"score_gpt":0.2682258492962956,"score_spread":0.2349308244603511,"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."}}