{"id":"W4246161596","doi":"10.31230/osf.io/v84rd","title":"Mislabelled: Montreal Investigation Results and How to Fix Canada's Seafood Fraud Problem","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Traceability; Fish <Actinopterygii>; Business; Agency (philosophy); Labelling; Food standards; Wildlife; Food supply; Fishery; Environmental protection; Food safety; International trade; Geography; Agricultural economics; Engineering; Biology; Ecology; Economics","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":[0.01887495,0.001508834,0.001269473,0.006847023,0.02070047,0.01613688,0.008786332,0.01390119,0.03727172],"category_scores_gemma":[0.1148723,0.001236925,0.001601504,0.005963663,0.01052014,0.007707851,0.006517668,0.01544097,0.009005914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0914011,"about_ca_system_score_gemma":0.2959379,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9421872,"about_ca_topic_score_gemma":0.9570515,"domain_scores_codex":[0.9658662,0.004207702,0.002136932,0.002899729,0.01996508,0.004924353],"domain_scores_gemma":[0.7941227,0.01466989,0.007244546,0.005755129,0.1543724,0.02383528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003344675,0.00001968633,0.005530612,0.0003034593,0.00003011125,0.0005676926,0.00107374,0.00005413774,0.0001771557,0.004655121,0.953153,0.0344019],"study_design_scores_gemma":[0.00002648966,0.00002997409,0.00750745,0.001874404,0.00008440237,0.0008406269,0.004110657,0.0002514966,0.0006122554,0.003119072,0.9813854,0.0001578372],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.003409591,0.01225149,0.001982426,0.9011449,0.02684789,0.0002781179,0.002332981,0.0006673981,0.05108516],"genre_scores_gemma":[0.06827423,0.02097266,0.008991616,0.7874945,0.00782429,0.0002454623,0.003598919,0.001357526,0.1012408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0914011,"threshold_uncertainty_score":0.6631645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607496325155664,"score_gpt":0.2307080667259973,"score_spread":0.2146331034744407,"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."}}