{"id":"W4375815422","doi":"10.2196/40673","title":"Genomic Insights Into the Evolution and Demographic History of the SARS-CoV-2 Omicron Variant: Population Genomics Approach","year":2023,"lang":"en","type":"article","venue":"JMIR Bioinformatics and Biotechnology","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Statens Serum Institut; Robert Koch Institut; Centre Hospitalier Universitaire Vaudois; Université de Lausanne; Université Catholique de Louvain","keywords":"Lineage (genetic); Evolutionary biology; Biology; Selection (genetic algorithm); Genomics; Population; Subdivision; Demographic history; Population genomics; Genetic diversity; Genome; Cluster (spacecraft); Genetics; Genetic variation; Computational biology; Gene; Geography; Computer science; Demography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006249546,0.0003393673,0.000329608,0.001525374,0.0003405839,0.0005490931,0.0003731137,0.0004764257,0.0009014674],"category_scores_gemma":[0.001083308,0.0001462873,0.0004523193,0.001250838,0.0003397866,0.0005840342,0.0005012287,0.000913683,0.0001139654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006031906,"about_ca_system_score_gemma":0.0004149327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00297495,"about_ca_topic_score_gemma":0.003997498,"domain_scores_codex":[0.9998462,0.0000450788,0.000005864641,0.00006695221,0.00002158093,0.0000143659],"domain_scores_gemma":[0.9996004,0.0002207268,0.00008298879,0.00002975183,0.00003267842,0.00003358968],"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":[0.0006865149,0.0003572649,0.3207487,0.0004636261,0.0005984116,0.0008600412,0.001945281,0.08065162,0.4439804,0.02642793,0.0007098734,0.1225704],"study_design_scores_gemma":[0.00005109519,0.0004490669,0.6799495,0.0000967623,0.0003209464,0.0009924455,0.001507631,0.2496487,0.01365463,0.04584545,0.007394745,0.0000891059],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9067854,0.0009263633,0.08872741,0.0004690123,0.00001581203,0.00007365892,0.000800954,0.0001334708,0.002067897],"genre_scores_gemma":[0.9499319,0.0006825941,0.04804515,0.000187589,0.00002674603,0.00005397069,0.0007447398,0.000028573,0.000298827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00297495,"threshold_uncertainty_score":0.005915284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02302699393187364,"score_gpt":0.2689144451511498,"score_spread":0.2458874512192762,"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."}}