{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002722361,0.0001013079,0.0002096173,0.0001078057,0.000080916,0.00004547536,0.00005621013,0.00007313993,0.00001036639],"category_scores_gemma":[0.001731668,0.00009442632,0.00002981833,0.0002166077,0.0001491756,0.0001136567,0.00007027641,0.0001441519,0.000007401831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004474554,"about_ca_system_score_gemma":0.0004090389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003798464,"about_ca_topic_score_gemma":0.0002959966,"domain_scores_codex":[0.9990878,0.00005897681,0.0002419249,0.0002571262,0.0001922057,0.0001619501],"domain_scores_gemma":[0.9991913,0.0002881677,0.00006018002,0.0002026339,0.0001946216,0.00006303476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001176473,0.0001850585,0.03210941,0.0006577316,0.00008005156,0.0001430186,0.001607687,5.227178e-7,0.9522303,0.0003964184,0.007718443,0.004753753],"study_design_scores_gemma":[0.001059825,0.00009513181,0.001839803,0.00009063898,0.00004140854,0.00009758487,0.0008557158,0.0006387596,0.9180202,0.00009773092,0.07707584,0.00008731877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915817,0.00384082,0.002013548,0.001938846,0.00003773685,0.0001740822,0.00003033071,0.00003520176,0.0003477545],"genre_scores_gemma":[0.9697345,0.0001105941,0.0003620283,0.02960486,0.00006649979,0.0000138954,0.00005041517,0.00001593387,0.00004127279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0693574,"threshold_uncertainty_score":0.3850594,"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."}}