{"id":"W2951384372","doi":"10.1093/molbev/msy242","title":"Beyond the SNP Threshold: Identifying Outbreak Clusters Using Inferred Transmissions","year":2018,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":167,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia; BC Centre for Disease Control","funders":"National Institute of General Medical Sciences; Engineering and Physical Sciences Research Council; National Institutes of Health","keywords":"Biology; Transmission (telecommunications); SNP; Single-nucleotide polymorphism; Genetics; Computational biology; Data mining; Computer science; Algorithm; Genotype; Telecommunications","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":[0.0004696019,0.0001124498,0.0001953724,0.0001057608,0.0003425268,0.000009302743,0.00007632253,0.0002056533,0.00004178868],"category_scores_gemma":[0.0002037047,0.00007187323,0.00007887126,0.0001512977,0.000598499,0.00004186419,0.00006745737,0.000228643,0.00002110751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000491498,"about_ca_system_score_gemma":0.00006131853,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002250712,"about_ca_topic_score_gemma":0.00006175254,"domain_scores_codex":[0.9989075,0.0002108106,0.0001921317,0.0002574487,0.00007370025,0.0003584024],"domain_scores_gemma":[0.9994878,0.00005082329,0.00003300174,0.0002218177,0.00007462169,0.0001319376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004972696,0.00008651847,0.1093071,0.00005177787,0.0003097001,0.00003257504,0.0004764569,0.00004546971,0.865326,0.01595399,0.002149286,0.005763866],"study_design_scores_gemma":[0.006519676,0.003013759,0.7416287,0.0003243288,0.0009481721,0.002053557,0.001063162,0.1084411,0.02258855,0.09071381,0.02174047,0.0009647458],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9058552,0.001877454,0.08289357,0.007841238,0.0001946222,0.0002475165,0.000004753336,0.00003206296,0.001053535],"genre_scores_gemma":[0.996517,0.00008332164,0.0010235,0.002101348,0.0001601061,0.000009668734,0.00003140735,0.000009677978,0.00006395904],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8427375,"threshold_uncertainty_score":0.2930905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04583162315229299,"score_gpt":0.3853673108950619,"score_spread":0.3395356877427689,"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."}}