{"id":"W2919418030","doi":"10.1186/s12864-019-5542-3","title":"Gen2Epi: an automated whole-genome sequencing pipeline for linking full genomes to antimicrobial susceptibility and molecular epidemiological data in Neisseria gonorrhoeae","year":2019,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Reproductive tract infections research","field":"Immunology and Microbiology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of Saskatchewan","funders":"Canadian Institutes of Health Research","keywords":"Neisseria gonorrhoeae; Genome; Biology; Computational biology; Molecular epidemiology; Whole genome sequencing; Genetics; Multilocus sequence typing; Gene; Genotype","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":[0.00246198,0.002423686,0.0009620261,0.001853911,0.0008563379,0.001202262,0.00167178,0.0009712092,0.007151857],"category_scores_gemma":[0.003591795,0.001270741,0.00175461,0.001401177,0.0004701351,0.001199733,0.001915808,0.001281634,0.003546143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007261778,"about_ca_system_score_gemma":0.002159966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003524502,"about_ca_topic_score_gemma":0.005043169,"domain_scores_codex":[0.9991795,0.0001306751,0.00006231369,0.0003552409,0.00019159,0.00008073725],"domain_scores_gemma":[0.9988781,0.0004701808,0.0001739204,0.0001463998,0.0002344968,0.00009692487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00470158,0.0005336912,0.0202825,0.004923082,0.001439032,0.001308427,0.00188756,0.03719027,0.270795,0.005340616,0.252361,0.3992372],"study_design_scores_gemma":[0.001520004,0.001226115,0.06360623,0.0005371264,0.0005373621,0.00180376,0.0004949854,0.4678255,0.2103848,0.01776166,0.2336227,0.0006797663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05663183,0.00134976,0.5770243,0.0004384307,0.0002477384,0.0009930064,0.09375846,0.2654775,0.004078959],"genre_scores_gemma":[0.09152475,0.0006044247,0.7429898,0.0004773074,0.00006899314,0.001416011,0.1464241,0.01400595,0.002488609],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007151857,"threshold_uncertainty_score":0.02392542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.070641565053501,"score_gpt":0.3485653639974283,"score_spread":0.2779237989439273,"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."}}