{"id":"W1905622249","doi":"10.1111/faf.12129","title":"Provenance of global seafood","year":2015,"lang":"en","type":"article","venue":"Fish and Fisheries","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Australian Research Council","keywords":"Fishing; Work (physics); Business; Fishery; Provenance; International trade; Biology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003748287,0.0004224135,0.0003858824,0.004549907,0.001078239,0.005955514,0.0006909068,0.0008484599,0.005887863],"category_scores_gemma":[0.01620759,0.00039662,0.0003964815,0.008546185,0.002334162,0.006093639,0.003324015,0.001023556,0.001756514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355725,"about_ca_system_score_gemma":0.002295014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008354491,"about_ca_topic_score_gemma":0.005930887,"domain_scores_codex":[0.997141,0.0006975016,0.0003068754,0.0006419806,0.001065594,0.0001471058],"domain_scores_gemma":[0.9844756,0.00358289,0.002256703,0.005817364,0.003535685,0.0003317859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005876599,0.00007416475,0.1235921,0.001962215,0.000256681,0.003123635,0.01283694,0.007148067,0.01412636,0.5144465,0.0220162,0.2998296],"study_design_scores_gemma":[0.0000178742,0.00006427417,0.02925136,0.001697772,0.0001587029,0.001345756,0.003424389,0.003136837,0.01042816,0.2197918,0.7305751,0.0001079647],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3329096,0.01896409,0.3006425,0.01003129,0.002170761,0.0004012756,0.08453535,0.002465982,0.2478791],"genre_scores_gemma":[0.8190432,0.01238193,0.1086875,0.000716833,0.0004484569,0.0001532886,0.03596437,0.0007712383,0.02183332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008354491,"threshold_uncertainty_score":0.01982307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641443685246896,"score_gpt":0.2538385430788288,"score_spread":0.2274241062263598,"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."}}