{"id":"W2403036549","doi":"10.1016/j.yrtph.2016.05.021","title":"Regulatory bioinformatics for food and drug safety","year":2016,"lang":"en","type":"article","venue":"Regulatory Toxicology and Pharmacology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Food Inspection Agency","funders":"European Food Safety Authority","keywords":"Regulatory science; Summit; Quality (philosophy); Computer science; Exploit; Data science; Drug development; Risk analysis (engineering); Bioinformatics; Business; Medicine; Drug; Biology","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":[0.04421105,0.001139373,0.001619066,0.003817519,0.002714947,0.01019347,0.003804926,0.0065941,0.02474217],"category_scores_gemma":[0.0870569,0.0007936463,0.002260821,0.004995603,0.006140772,0.00986183,0.006652021,0.01104651,0.01587044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005128461,"about_ca_system_score_gemma":0.0214835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002723971,"about_ca_topic_score_gemma":0.001703138,"domain_scores_codex":[0.9610928,0.02335734,0.002341539,0.002948656,0.009089055,0.001170704],"domain_scores_gemma":[0.9201258,0.04117259,0.005205288,0.01202996,0.0180666,0.003399761],"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":[0.0002324208,0.0001061385,0.001294164,0.001929498,0.0001299031,0.0002454318,0.0005786225,0.003353098,0.002135544,0.485604,0.2330527,0.2713385],"study_design_scores_gemma":[0.00005259899,0.00008875838,0.0004611268,0.0008953347,0.00003953898,0.0002266038,0.0001420094,0.002908514,0.001468922,0.2262139,0.7674612,0.00004151442],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003631418,0.05452273,0.3884709,0.3423591,0.01216398,0.001001666,0.004979998,0.009806427,0.1830638],"genre_scores_gemma":[0.1489542,0.1003556,0.5094113,0.1519091,0.01652019,0.003224535,0.01682005,0.003640737,0.04916416],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04421105,"threshold_uncertainty_score":0.2338132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007703522070249536,"score_gpt":0.2703689833126097,"score_spread":0.2626654612423601,"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."}}