{"id":"W3028710516","doi":"10.1038/s41467-019-12438-5","title":"Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute; University of Ottawa","funders":"Common Fund; National Institute of Diabetes and Digestive and Kidney Diseases; Wellcome Trust; National Human Genome Research Institute; National Institute of General Medical Sciences; National Institute of Mental Health; National Heart, Lung, and Blood Institute; National Institute on Aging; British Heart Foundation; National Cancer Institute; U.S. Department of Health and Human Services; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Rosetrees Trust","keywords":"Genome; Biology; Genetics; Exome; Computational biology; Human genome; Exome sequencing; Haplotype; 1000 Genomes Project; Mutation; Gene; Single-nucleotide polymorphism; Allele","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":[0.00005580977,0.00008004078,0.0001121658,0.00003414528,0.00007760529,0.00001173934,0.0004189876,0.0001373429,0.00001006728],"category_scores_gemma":[0.00006815972,0.00007736337,0.00004087939,0.0000875582,0.00007432865,0.000002924903,0.0003443081,0.0001756542,0.000001698738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002857176,"about_ca_system_score_gemma":0.00003238238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001326822,"about_ca_topic_score_gemma":0.0003046564,"domain_scores_codex":[0.9995153,0.00004838839,0.0001495613,0.0001552555,0.00004088391,0.00009060391],"domain_scores_gemma":[0.9992573,0.00001638509,0.00005899978,0.0005532344,0.00005001522,0.00006405981],"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":[0.0000667537,0.0005645354,0.2618028,0.00008777261,0.0001706263,0.000007568913,0.001126217,0.00009214923,0.7246478,0.004275634,0.004568407,0.002589771],"study_design_scores_gemma":[0.00223891,0.0002322873,0.8786486,0.0000382188,0.0000708636,0.00001121655,0.001006571,0.00146056,0.01050981,0.0001972643,0.1050957,0.0004900502],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9596665,0.03768417,0.0000142219,0.001453351,0.00002243227,0.0001355614,0.00009523797,0.000007722166,0.0009208344],"genre_scores_gemma":[0.994888,0.002717111,0.001597079,0.0004637177,0.00002797924,0.000008177736,0.0002539957,0.0000113217,0.00003259526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7141379,"threshold_uncertainty_score":0.3154786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0201968448620921,"score_gpt":0.2866555216317059,"score_spread":0.2664586767696138,"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."}}