{"id":"W4389753517","doi":"10.1016/j.jacadv.2023.100769","title":"Ensuring Equity, Diversity, and Inclusiveness in Genetic Analysis Will Empower the Future of Precision Medicine","year":2023,"lang":"en","type":"editorial","venue":"JACC Advances","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Saint John Regional Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Equity (law); Precision medicine; Diversity (politics); Political science; Biology; Genetics; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002729526,0.0001958404,0.000382261,0.0001546324,0.0002007571,0.00001090991,0.0004589557,0.0002988911,0.000007963474],"category_scores_gemma":[0.0002509378,0.0001325641,0.0001201065,0.000296362,0.0001446677,0.000005291961,0.003767742,0.0001495329,3.873309e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001754036,"about_ca_system_score_gemma":0.00006022051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001142375,"about_ca_topic_score_gemma":0.001074523,"domain_scores_codex":[0.9987002,0.00006858294,0.0002638854,0.0004167215,0.0003721105,0.0001785069],"domain_scores_gemma":[0.9990551,0.000186651,0.0002194461,0.0003401107,0.0001467183,0.00005189713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001966606,0.0004490053,0.1271401,0.002294746,0.004489227,0.0003136332,0.003785436,0.01605138,0.0115511,0.00004269681,0.7324087,0.09950738],"study_design_scores_gemma":[0.0009375974,0.0003003735,0.03535632,0.0001803414,0.000859851,0.000001413949,0.0007797547,0.00004086779,0.0002902965,0.001440111,0.9593778,0.0004352909],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5139505,0.08383853,0.0001060468,0.0002064465,0.4009638,0.0003513285,0.0004298552,0.00001151861,0.0001419976],"genre_scores_gemma":[0.5941945,0.09161986,0.0001059059,0.00003803702,0.312679,0.00002180052,0.0009068382,0.00004872248,0.0003853776],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2269691,"threshold_uncertainty_score":0.5405806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007081416787909064,"score_gpt":0.2970046047936726,"score_spread":0.2899231880057636,"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."}}