{"id":"W2968316706","doi":"10.1186/s13072-019-0296-3","title":"Accurate ethnicity prediction from placental DNA methylation data","year":2019,"lang":"en","type":"article","venue":"Epigenetics & Chromatin","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; BC Children's Hospital; Canada Research Chairs; University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Environmental Health Sciences; National Institutes of Health","keywords":"Population stratification; Biology; Ancestry-informative marker; Confounding; Population; Ethnic group; Single-nucleotide polymorphism; Genotyping; SNP; Genetics; Genetic association; DNA methylation; Evolutionary biology; Bioinformatics; Computational biology; Genotype; Demography; Gene; Medicine; Internal medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004550158,0.0002561219,0.0002230597,0.000054622,0.00009971915,0.00006437306,0.0005375981,0.0002973742,0.0002157501],"category_scores_gemma":[0.0001565181,0.0002675064,0.00007346054,0.0001366526,0.00005182618,0.0000179978,0.0004372296,0.0001489635,0.0002060624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003489372,"about_ca_system_score_gemma":0.00009473098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009832751,"about_ca_topic_score_gemma":0.00009282828,"domain_scores_codex":[0.9979073,0.0001918181,0.0004812359,0.0007772369,0.0003348086,0.0003075759],"domain_scores_gemma":[0.9980635,0.0000595991,0.0002462999,0.00141589,0.0000948079,0.0001199183],"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":[0.00004307719,0.00006693898,0.01230461,0.00001473752,0.00006616834,7.396256e-7,0.00007511164,0.001362232,0.9811375,0.00001757579,0.0006262647,0.004285098],"study_design_scores_gemma":[0.0009096205,0.0002901651,0.1115153,0.00002652187,0.00005310304,0.000001044299,0.00007134128,0.01546294,0.8482251,0.0002685406,0.02281677,0.0003595469],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809185,0.002399179,0.01298576,0.00008055739,0.0007136264,0.0004569679,0.0007287426,0.00004235118,0.001674309],"genre_scores_gemma":[0.9873405,0.0007282718,0.004557172,0.00007926198,0.000553623,0.00001234305,0.00611667,0.00005167013,0.0005605106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1329124,"threshold_uncertainty_score":0.9999777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02726001531824641,"score_gpt":0.2858376523860335,"score_spread":0.2585776370677871,"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."}}