{"id":"W2104797721","doi":"10.1371/journal.pgen.1004023","title":"Reconstructing Native American Migrations from Whole-Genome and Whole-Exome Data","year":2013,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":202,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"National Institute on Minority Health and Health Disparities; National Center for Research Resources; National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; National Heart, Lung, and Blood Institute; Wellcome Trust; National Human Genome Research Institute; University of California, San Francisco; American Asthma Foundation; Biotechnology and Biological Sciences Research Council; Robert Wood Johnson Foundation; Sandler Foundation; National Institutes of Health; National Science Foundation","keywords":"Biology; Demographic history; Population; Evolutionary biology; Genetic genealogy; Population genetics; Native american; Genotyping; Genealogy; Ethnology; Genetic variation; Demography; Genetics; Genotype; History","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":[0.001406866,0.0004966373,0.000510445,0.002992866,0.0009581672,0.001131528,0.0005645725,0.0007230833,0.001910225],"category_scores_gemma":[0.002718567,0.000461491,0.0008506682,0.002945955,0.0004715291,0.0008611943,0.001133037,0.0010676,0.0007969084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003939947,"about_ca_system_score_gemma":0.0006009203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01183706,"about_ca_topic_score_gemma":0.02221402,"domain_scores_codex":[0.9996879,0.00008496465,0.00001964421,0.0001378453,0.00002559797,0.0000439768],"domain_scores_gemma":[0.999281,0.0002997681,0.0001213913,0.000133246,0.00008859573,0.0000760373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00118388,0.000317566,0.6956237,0.0008618496,0.002913173,0.002369407,0.005378262,0.05393296,0.05578278,0.01032051,0.01966971,0.1516462],"study_design_scores_gemma":[0.0001334098,0.000094257,0.7994433,0.0003158766,0.0007417883,0.001210779,0.005246272,0.1075845,0.002576361,0.03238065,0.05011715,0.0001557604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9445415,0.002404183,0.0364206,0.0007140782,0.00009602413,0.00004037224,0.01180469,0.0006835778,0.003294982],"genre_scores_gemma":[0.9281316,0.001965533,0.04518951,0.0003943804,0.0000745301,0.00009277694,0.02272856,0.0002755775,0.001147392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01183706,"threshold_uncertainty_score":0.02353632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0377245989440799,"score_gpt":0.2842147733986887,"score_spread":0.2464901744546088,"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."}}