{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007186494,0.0006645572,0.00122283,0.002839688,0.001185734,0.002353644,0.001440105,0.001243444,0.001116542],"category_scores_gemma":[0.03580717,0.0005451397,0.001252188,0.002194729,0.0009352713,0.002140564,0.002174211,0.001709734,0.000483471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008720838,"about_ca_system_score_gemma":0.00156925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007544845,"about_ca_topic_score_gemma":0.007334854,"domain_scores_codex":[0.9967657,0.001606112,0.0002255431,0.0008278289,0.0003773714,0.0001973643],"domain_scores_gemma":[0.9827731,0.01215948,0.001735245,0.001931467,0.0009531491,0.0004475958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00176781,0.0002900074,0.2123285,0.000728674,0.001516824,0.0009545319,0.003183731,0.327694,0.01588304,0.02866521,0.01077042,0.3962173],"study_design_scores_gemma":[0.0001261336,0.00008069436,0.02143678,0.0001209047,0.0001926095,0.0004242395,0.0004857856,0.915848,0.005218533,0.05233769,0.003645806,0.00008284245],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3642305,0.001126831,0.6276056,0.00099628,0.00009742509,0.0001452186,0.001540087,0.002078418,0.002179584],"genre_scores_gemma":[0.6892031,0.0002475256,0.3067844,0.0002252099,0.000084264,0.00009750801,0.002086584,0.0004050992,0.0008662033],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007544845,"threshold_uncertainty_score":0.03800625,"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."}}