{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009940009,0.0003883472,0.0005906594,0.002300476,0.0005802172,0.001039061,0.0003366638,0.0006565458,0.002668614],"category_scores_gemma":[0.003935616,0.0002288852,0.0007609084,0.003420043,0.0002886934,0.0005195668,0.001004279,0.0003928583,0.0004426786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002820556,"about_ca_system_score_gemma":0.0002931444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002823005,"about_ca_topic_score_gemma":0.005193124,"domain_scores_codex":[0.9989004,0.0002076909,0.00009566286,0.0005249009,0.0001597279,0.0001116535],"domain_scores_gemma":[0.998467,0.000890544,0.0002609531,0.0001543301,0.0001287471,0.00009839098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001988189,0.00009297254,0.795112,0.001629107,0.004388302,0.002845501,0.00101475,0.009868638,0.08766231,0.003372815,0.01393595,0.07808957],"study_design_scores_gemma":[0.00007692221,0.0001036711,0.9469675,0.0001579062,0.001084452,0.002629821,0.0005626402,0.008391205,0.006226168,0.004519056,0.02922088,0.00005983382],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9488513,0.003804788,0.00544537,0.0002805512,0.00002432595,0.00001885216,0.04001618,0.0002190871,0.001339502],"genre_scores_gemma":[0.9050519,0.001550217,0.008114248,0.0003586499,0.00003307432,0.00006399248,0.08370525,0.0001485009,0.0009740236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002823005,"threshold_uncertainty_score":0.008927405,"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."}}