{"id":"W2574993108","doi":"10.5740/jaoacint.16-0269","title":"Baseline Practices for the Application of Genomic Data Supporting Regulatory Food Safety","year":2017,"lang":"en","type":"article","venue":"Journal of AOAC International","topic":"Enterobacteriaceae and Cronobacter Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Public Health Agency of Canada; Canadian Food Inspection Agency","funders":"","keywords":"Traceability; Food safety; Transparency (behavior); Leverage (statistics); Consistency (knowledge bases); Business; Risk analysis (engineering); Computer science; Data science; Computer security; Biology; Food science","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":[0.001222702,0.000051699,0.0000813537,0.00002483762,0.0001079806,0.00006054609,0.001181621,0.00003882438,0.00002200047],"category_scores_gemma":[0.0007315866,0.00003688343,0.00007083306,0.000005953817,0.00005786717,0.00003442858,0.0003006879,0.00007447501,8.922911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001407051,"about_ca_system_score_gemma":0.0001079384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001163184,"about_ca_topic_score_gemma":0.00005066163,"domain_scores_codex":[0.9992779,0.00002674022,0.0003362666,0.0001127886,0.0001663703,0.00007985764],"domain_scores_gemma":[0.9973825,0.00005434934,0.001655235,0.0005338663,0.0003474206,0.00002667616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009707251,0.0001051679,0.0282237,0.00002343259,0.0005565689,8.072128e-7,0.00002958678,0.00004764761,0.9385313,0.0002650961,0.003250388,0.02799556],"study_design_scores_gemma":[0.002169079,0.000696683,0.1652981,0.00004470236,0.0001201937,0.0001123807,0.0002682999,0.003582493,0.1844886,0.0002039109,0.6428581,0.0001574846],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618299,0.0002028905,0.03432286,0.002702237,0.0003608811,0.0001424335,0.0001987093,8.629043e-7,0.0002392099],"genre_scores_gemma":[0.9968553,0.0001778953,0.001611499,0.00005870282,0.0009603834,0.000003308272,0.0001491884,0.000007807007,0.0001758989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7540427,"threshold_uncertainty_score":0.2195765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05845139254704362,"score_gpt":0.4000829743123454,"score_spread":0.3416315817653017,"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."}}