{"id":"W4385064112","doi":"10.1007/s00439-023-02587-5","title":"Genomics and inclusion of Indigenous peoples in high income countries","year":2023,"lang":"en","type":"review","venue":"Human Genetics","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"National Health and Medical Research Council; Macquarie University","keywords":"Biology; Indigenous; Human genetics; Genomics; Genome Biology; Inclusion (mineral); Metabolic disease; Molecular medicine; Genetics; Evolutionary biology; Gene; Genome; Anthropology; Ecology; Endocrinology","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":[0.0003903556,0.0004131635,0.001058037,0.0001573747,0.0004032208,0.00002818665,0.0005022729,0.0007377182,0.000005602553],"category_scores_gemma":[0.00003856577,0.0004145989,0.0002192107,0.0001559619,0.0002888675,0.000001506872,0.003364333,0.0002143269,0.000006366948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006488264,"about_ca_system_score_gemma":0.0004630429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006014226,"about_ca_topic_score_gemma":0.0009382218,"domain_scores_codex":[0.9979232,0.0001266255,0.0007990017,0.0005599439,0.0002306256,0.0003605866],"domain_scores_gemma":[0.9987453,0.00004976511,0.0004046202,0.0006288121,0.00008370667,0.00008779096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000145712,0.001055233,0.02628001,0.2877177,0.003840237,0.0001753472,0.0749461,0.0006368866,0.00995734,0.001594175,0.002420089,0.5912312],"study_design_scores_gemma":[0.0007485881,0.0005924952,0.002271633,0.003298761,0.000484866,0.00002519801,0.0003340843,0.000004851798,0.0007230678,0.0006850571,0.9897079,0.001123444],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.2772684,0.7219703,0.000008070856,0.000002949235,0.0001164813,0.0004490925,0.000142459,0.000009561679,0.00003267304],"genre_scores_gemma":[0.007207891,0.9911262,0.0003587565,0.00002624449,0.0003093777,0.00003531023,0.000465829,0.0001144303,0.0003559444],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9872879,"threshold_uncertainty_score":0.9998306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01930438057167452,"score_gpt":0.2986295008122393,"score_spread":0.2793251202405648,"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."}}