{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002611892,0.002680848,0.001493297,0.001788827,0.0008355623,0.001684606,0.002605156,0.0009314043,0.04719779],"category_scores_gemma":[0.004694817,0.001163871,0.002096728,0.001414265,0.0004727003,0.001262054,0.00236924,0.001892076,0.01357146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008287359,"about_ca_system_score_gemma":0.002111631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004180278,"about_ca_topic_score_gemma":0.006123007,"domain_scores_codex":[0.9993794,0.0001457759,0.00004970743,0.0002171009,0.0001240632,0.00008399259],"domain_scores_gemma":[0.9985641,0.0008298114,0.00009302563,0.0001680189,0.0002208001,0.0001243631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003779486,0.0003769604,0.01982874,0.004587851,0.001696198,0.001007296,0.001220393,0.0137071,0.03469487,0.007334449,0.7669384,0.1448282],"study_design_scores_gemma":[0.002785913,0.000559922,0.03149169,0.0006232368,0.0005954459,0.001575377,0.0004631673,0.2746345,0.07797161,0.02830373,0.580267,0.0007283604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01660565,0.000807825,0.2575874,0.0008177976,0.0004325188,0.0005749921,0.1279642,0.587858,0.007351641],"genre_scores_gemma":[0.09456849,0.001412541,0.5316756,0.002028944,0.0001923524,0.00363461,0.2439999,0.1153031,0.007184479],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04719779,"threshold_uncertainty_score":0.1578923,"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."}}