{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005414372,0.0002058771,0.0002832125,0.000101043,0.0001647715,0.00000841607,0.0001442631,0.0003064443,0.0000942652],"category_scores_gemma":[0.00004687317,0.0001633114,0.00009095352,0.00005090957,0.0006170474,0.00001421223,0.0001808144,0.00007273575,0.000003127148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002255791,"about_ca_system_score_gemma":0.00006520258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.721879e-7,"about_ca_topic_score_gemma":0.00001558993,"domain_scores_codex":[0.9987363,0.0001303019,0.0003468332,0.000397185,0.00005840978,0.0003309648],"domain_scores_gemma":[0.9992512,0.0001254753,0.0001487677,0.000262033,0.00007360579,0.0001388461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000215135,0.00005076923,0.001397897,0.00005523898,0.0002502988,0.000001544926,0.00005076414,0.000001052735,0.9368219,0.001777423,0.03676916,0.0226088],"study_design_scores_gemma":[0.001880417,0.0006222034,0.003265905,0.000008106784,0.0001431237,0.00007105342,0.00002907065,0.00006220004,0.7476861,0.001155432,0.2447975,0.0002789335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930549,0.001802205,0.002673364,0.001134671,0.0001446973,0.0004633166,0.00003670324,0.00004956339,0.0006405256],"genre_scores_gemma":[0.9934502,0.001039069,0.001704444,0.001460385,0.0001934342,0.0000905538,0.00002597325,0.00002652521,0.002009466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2080283,"threshold_uncertainty_score":0.6659646,"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."}}