{"id":"W3130954900","doi":"10.7554/elife.63409","title":"COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest","year":2021,"lang":"en","type":"article","venue":"eLife","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fusion Genomics (Canada); University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Stanley Center for Psychiatric Research, Broad Institute","keywords":"Lineage (genetic); Mutation; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Biology; Genome; Pandemic; Transmission (telecommunications); Clade; Mutation rate; Virology; Genetics; Computational biology; Gene; Phylogenetics; Medicine; Computer science; Infectious disease (medical specialty); Disease","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":[0.0037739,0.001122288,0.001163564,0.004634766,0.0009988653,0.002493019,0.001850634,0.001013714,0.04813172],"category_scores_gemma":[0.009801785,0.0008933443,0.0009475531,0.003760149,0.0003607422,0.002616349,0.003363771,0.001022946,0.02770763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071022,"about_ca_system_score_gemma":0.002370311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01522714,"about_ca_topic_score_gemma":0.01889697,"domain_scores_codex":[0.9984362,0.0001995099,0.0001811071,0.0004984837,0.0005019295,0.0001828324],"domain_scores_gemma":[0.9947765,0.001199918,0.001029242,0.001221359,0.001165443,0.0006075476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.003387614,0.0002605036,0.0991402,0.001384076,0.0003207542,0.0009363798,0.001462881,0.00236624,0.02597121,0.008436992,0.6641781,0.1921551],"study_design_scores_gemma":[0.0003522781,0.000267031,0.04648357,0.0004773989,0.0001677393,0.001088464,0.0004615324,0.02069144,0.02854159,0.005826241,0.8953483,0.0002945439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.05509244,0.001802594,0.07119545,0.001600345,0.0007123323,0.001323129,0.5981803,0.1747147,0.09537872],"genre_scores_gemma":[0.1514615,0.001497672,0.2334007,0.001455177,0.0003390385,0.001243575,0.561155,0.0239755,0.02547184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04813172,"threshold_uncertainty_score":0.1610167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1193237528560362,"score_gpt":0.4010284568550354,"score_spread":0.2817047039989992,"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."}}