{"id":"W3032327206","doi":"10.1097/olq.0000000000001206","title":"Gen2EpiGUI: User-Friendly Pipeline for Analyzing Whole-Genome Sequencing Data for Epidemiological Studies of Neisseria gonorrhoeae","year":2020,"lang":"en","type":"article","venue":"Sexually Transmitted Diseases","topic":"Bacterial Infections and Vaccines","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Institutes of Health Research","keywords":"Neisseria gonorrhoeae; Whole genome sequencing; Pipeline (software); Genome; Computational biology; Graphical user interface; Medicine; Bioinformatics; Data mining; Genetics; Computer science; Biology; Gene; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003155331,0.0003106635,0.0008720943,0.00007733049,0.0002684032,0.00001815487,0.0005126305,0.0001838653,0.0001064016],"category_scores_gemma":[0.001657162,0.0002474208,0.0002226424,0.0002269911,0.0001705707,0.0002290179,0.0001104306,0.000126408,0.00001236263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002625867,"about_ca_system_score_gemma":0.0001394688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003185562,"about_ca_topic_score_gemma":0.00002718314,"domain_scores_codex":[0.9979029,0.0001858989,0.000778157,0.0006757463,0.00001151845,0.0004457411],"domain_scores_gemma":[0.9978145,0.001083907,0.0002329151,0.0005050372,0.0002783799,0.00008522617],"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":[0.001713768,0.0002341004,0.003775053,0.0006894193,0.001287838,5.374139e-7,0.0004172641,0.0001978222,0.9780207,0.0006624408,0.008728703,0.004272355],"study_design_scores_gemma":[0.01629443,0.005774031,0.02735194,0.0002953275,0.005567692,0.00003199864,0.008610642,0.002175142,0.01545584,0.001874043,0.9142649,0.002304007],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8568467,0.0252321,0.09454928,0.002866085,0.0007829826,0.001464859,0.01799524,0.0002523013,0.00001038537],"genre_scores_gemma":[0.9877077,0.0003794497,0.002087738,0.0005300523,0.000365013,0.0001640262,0.008595643,0.00004262049,0.000127792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9625649,"threshold_uncertainty_score":0.9999978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1040305689166006,"score_gpt":0.3418210564785523,"score_spread":0.2377904875619517,"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."}}