{"id":"W4389454348","doi":"10.1371/journal.pgen.1010625","title":"Exploring the genetic diversity of the Japanese population: Insights from a large-scale whole genome sequencing analysis","year":2023,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; National Center of Neurology and Psychiatry; Japan Agency for Medical Research and Development; Japan Society for the Promotion of Science London; National Center for Geriatrics and Gerontology; National Cerebral and Cardiovascular Center; National Center for Global Health and Medicine; Ministry of Education, Culture, Sports, Science and Technology; National Center for Child Health and Development","keywords":"Biology; Population; Genetic diversity; Archipelago; Genetics; Haplotype; Shotgun sequencing; Population genomics; Population genetics; Evolutionary biology; Genomics; Genome; Allele; Demography; Ecology; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000619252,0.0003158293,0.0004847088,0.001359605,0.0006071919,0.0007571219,0.0002863232,0.0003396418,0.0007932493],"category_scores_gemma":[0.0008108523,0.0001967017,0.0006560567,0.002321661,0.0003745126,0.0002776493,0.0007068106,0.0003751853,0.000192678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000286669,"about_ca_system_score_gemma":0.0004996908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01273956,"about_ca_topic_score_gemma":0.03059068,"domain_scores_codex":[0.9997137,0.0000425957,0.00002144131,0.0001376791,0.00003835183,0.00004614882],"domain_scores_gemma":[0.9995735,0.0000983324,0.00008598227,0.00005513044,0.00008879331,0.00009824354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000308309,0.0001034389,0.8206672,0.0003514304,0.001314419,0.001547787,0.005872551,0.001876274,0.1188701,0.0007373301,0.001371133,0.04698022],"study_design_scores_gemma":[0.00001121459,0.00004446736,0.9929021,0.0000204959,0.0003530141,0.0003384988,0.001045976,0.001255883,0.0007940833,0.0002987096,0.002917821,0.00001776191],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957633,0.0005072361,0.001728258,0.00004827983,0.000003635894,0.00001064047,0.00151319,0.00001309521,0.0004122259],"genre_scores_gemma":[0.9876823,0.0006062421,0.004979035,0.00009377942,0.00001222117,0.00002164425,0.006183682,0.00002297335,0.0003981576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01273956,"threshold_uncertainty_score":0.02533084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06290230709632923,"score_gpt":0.2536802889948777,"score_spread":0.1907779818985485,"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."}}