{"id":"W2158486577","doi":"10.1534/g3.112.001941","title":"Ancestry Informative Marker Set for Han Chinese Population","year":2012,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"National Institute of General Medical Sciences; National Natural Science Foundation of China; Shanghai Rising-Star Program; National Science Foundation","keywords":"Han chinese; Genetic genealogy; Population; Chinese population; Chinese people; Ancestry-informative marker; China; Genetics; Geography; Demography; Genealogy; Biology; Evolutionary biology; History; Allele frequency; Gene; Single-nucleotide polymorphism; Allele; Genotype; Sociology","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":[],"consensus_categories":[],"category_scores_codex":[0.0004480279,0.0002575322,0.000257069,0.00006276038,0.0001877384,0.00002176167,0.0002096637,0.0002858613,0.00002389767],"category_scores_gemma":[0.00003808934,0.0002371841,0.0001561874,0.0001219585,0.00005360765,0.000009673445,0.0001299688,0.00006671969,0.0000256568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003406352,"about_ca_system_score_gemma":0.00005166236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001206869,"about_ca_topic_score_gemma":0.00003195302,"domain_scores_codex":[0.9984991,0.0000883427,0.0004248441,0.0002701983,0.000116896,0.0006006016],"domain_scores_gemma":[0.9990395,0.00004112828,0.0002426455,0.000406787,0.0001046865,0.0001652394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000339678,0.00003488398,0.8316639,0.00002423663,0.00009328755,7.18633e-8,0.0002141253,0.0008426905,0.005426905,0.00001960156,0.001667572,0.1599787],"study_design_scores_gemma":[0.0005820763,0.0002031483,0.6909276,0.000003727747,0.00004909913,0.00001383854,0.0002484985,0.0008782322,0.001762745,0.0003223041,0.3045846,0.0004240539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8669388,0.1235436,0.007493371,0.0001084852,0.0006408336,0.0004639442,0.0001423631,0.00001964488,0.000648949],"genre_scores_gemma":[0.9637513,0.01473941,0.01752018,0.0004696423,0.001161393,0.0001226865,0.001476315,0.00003983816,0.000719275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3029171,"threshold_uncertainty_score":0.9672085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02559311856531799,"score_gpt":0.3123775221790598,"score_spread":0.2867844036137419,"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."}}