{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0185861,0.0005621146,0.0005297425,0.001602923,0.002437851,0.009176539,0.001433228,0.009869301,0.00340904],"category_scores_gemma":[0.0316871,0.0004006426,0.0005816053,0.0008621829,0.006232162,0.006003228,0.007903043,0.004211514,0.0009204311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001706934,"about_ca_system_score_gemma":0.005046247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002889374,"about_ca_topic_score_gemma":0.002643011,"domain_scores_codex":[0.9830878,0.009091415,0.0007807774,0.001290866,0.004163243,0.001585817],"domain_scores_gemma":[0.9861659,0.005985735,0.002779709,0.002087399,0.0022539,0.0007273704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002065794,0.0006109325,0.02412187,0.0004822956,0.0001089244,0.0009159039,0.006726157,0.001879278,0.003539619,0.6148543,0.03376539,0.3127887],"study_design_scores_gemma":[0.0002040935,0.001029593,0.04367089,0.004050004,0.0001881749,0.002243124,0.0104062,0.009166103,0.01110086,0.2738627,0.6438295,0.0002487706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.277651,0.01616764,0.05212599,0.1307295,0.00105856,0.0005703054,0.0001264068,0.0003427259,0.521228],"genre_scores_gemma":[0.9409791,0.003408279,0.01238698,0.02590063,0.00029875,0.0001731722,0.00006654809,0.00003550362,0.01675125],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0185861,"threshold_uncertainty_score":0.09829384,"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."}}