{"id":"W2562631867","doi":"10.1111/nyas.13273","title":"A brief primer on genomic epidemiology: lessons learned from<i>Mycobacterium tuberculosis</i>","year":2016,"lang":"en","type":"review","venue":"Annals of the New York Academy of Sciences","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"National Human Genome Research Institute; Canada Research Chairs; Michael Smith Health Research BC; U.S. Food and Drug Administration; Public Health Agency of Canada","keywords":"Genomics; Mycobacterium tuberculosis; Transmission (telecommunications); Tuberculosis; Epidemiology; Biology; Molecular epidemiology; Computational biology; Genetic epidemiology; Data science; Genetics; Medicine; Genome; Computer science; Genotype; Gene; Pathology","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":[0.001614267,0.0009623001,0.001274819,0.003424998,0.0005484996,0.001971591,0.001021523,0.002634689,0.005192475],"category_scores_gemma":[0.00430898,0.0003838617,0.0007661311,0.003780377,0.001537386,0.005212475,0.001388132,0.005886111,0.002961064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057963,"about_ca_system_score_gemma":0.001803788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001844138,"about_ca_topic_score_gemma":0.003268325,"domain_scores_codex":[0.9994863,0.0001990493,0.00008135488,0.00006914258,0.0001274207,0.00003671441],"domain_scores_gemma":[0.9970134,0.002247511,0.0001879496,0.0000709729,0.0003225804,0.0001576264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000074663,0.00008268281,0.0005115909,0.0135065,0.00008246624,0.0006104424,0.0006097791,0.0005221522,0.001374162,0.03580114,0.3775986,0.5692259],"study_design_scores_gemma":[0.000002849796,0.00002318377,0.0003330218,0.003549969,0.00001402715,0.0008546072,0.0001031848,0.00003657067,0.00007336248,0.007431134,0.9875638,0.00001423772],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008981165,0.9811419,0.0008328307,0.01213559,0.004057617,0.00000698924,0.00005819428,0.00001603943,0.001660913],"genre_scores_gemma":[0.0008295656,0.9791803,0.001507759,0.01008308,0.006522453,0.00001730638,0.00009953126,0.00001112935,0.001748927],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005192475,"threshold_uncertainty_score":0.01737058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3552790310985692,"score_gpt":0.4740720395461648,"score_spread":0.1187930084475955,"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."}}