{"id":"W3097829611","doi":"10.1038/s41598-020-76245-5","title":"Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vietnamese; Population; Allele; Genetics; Biology; Allele frequency; Single-nucleotide polymorphism; Genotype; Genome-wide association study; Disease; Ancestry-informative marker; Computational biology; Medicine; Gene; Environmental health","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":[0.0005859173,0.0002041148,0.000215066,0.001116893,0.0003259575,0.000508119,0.0002260172,0.0001514924,0.00117777],"category_scores_gemma":[0.001924279,0.0001083969,0.0002342457,0.001584826,0.0001582212,0.0001287387,0.0003966158,0.0001940225,0.0001777626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002252782,"about_ca_system_score_gemma":0.0005513193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01314253,"about_ca_topic_score_gemma":0.01609069,"domain_scores_codex":[0.9995214,0.0001257927,0.00005407611,0.0001507808,0.0000899705,0.00005799865],"domain_scores_gemma":[0.9990952,0.0002850416,0.0002266336,0.00009715789,0.0001813112,0.0001146977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001206654,0.00005401659,0.9517623,0.0001502019,0.0001499351,0.002615569,0.001494269,0.0003865126,0.01912092,0.000209502,0.001291404,0.02264479],"study_design_scores_gemma":[0.00001066617,0.00007119538,0.9870674,0.00005277629,0.00007671117,0.002480058,0.001577742,0.001138051,0.002629109,0.0002207257,0.004662751,0.00001290421],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944108,0.0004096549,0.001412615,0.0001778076,0.000009216001,0.00004857971,0.002877653,0.00001456022,0.0006390404],"genre_scores_gemma":[0.9928285,0.000464364,0.002108307,0.0001193407,0.00001458471,0.00005045334,0.004004269,0.000009717816,0.0004005021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01314253,"threshold_uncertainty_score":0.02613205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04140714834629855,"score_gpt":0.2862096877553721,"score_spread":0.2448025394090736,"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."}}