{"id":"W2951411417","doi":"","title":"Making molecular biology fun: Fish fraud in Ontario","year":2019,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fish <Actinopterygii>; Biology; Fishery; Business","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002396732,0.0002157778,0.0002047004,0.0003044567,0.00007653566,0.00009985171,0.0005982522,0.0003091615,0.0001303959],"category_scores_gemma":[0.00002587063,0.000267165,0.0001158806,0.0002488909,0.00007307107,0.00004600733,0.0002452355,0.0003561396,0.0003674813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001281565,"about_ca_system_score_gemma":0.0001497102,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005478934,"about_ca_topic_score_gemma":0.04946653,"domain_scores_codex":[0.9984049,0.0001826515,0.0002559099,0.0006649385,0.000143663,0.0003479017],"domain_scores_gemma":[0.9989111,0.00001416672,0.0001587187,0.0007093416,0.0001160208,0.00009063305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006906323,0.00005906884,0.8695237,0.00001346735,0.00003255014,0.00001550728,0.00008352727,0.00002320051,0.1296267,0.0004713452,0.00000242652,0.00007945458],"study_design_scores_gemma":[0.001000811,0.0001169825,0.9016073,0.00004913416,0.0000185051,0.00001368555,0.0001219017,2.775678e-7,0.06142189,0.00005873757,0.03522947,0.0003613041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967567,0.00004296647,0.001082698,0.0001581786,0.0003823173,0.0002824392,0.00001479753,0.00003290847,0.001246955],"genre_scores_gemma":[0.9856304,0.00001267078,0.00005913293,0.0006436746,0.00003135317,0.000002180949,0.000198791,0.00002834603,0.01339343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06820481,"threshold_uncertainty_score":0.9999781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09819275446941812,"score_gpt":0.3362315055987257,"score_spread":0.2380387511293076,"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."}}