{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02227943,0.00339887,0.003924458,0.003862086,0.004754234,0.01358039,0.005222984,0.0273961,0.02329951],"category_scores_gemma":[0.06713468,0.001314316,0.003796297,0.001549042,0.004782681,0.006196771,0.002837014,0.04224139,0.01723015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005112885,"about_ca_system_score_gemma":0.00813845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002796595,"about_ca_topic_score_gemma":0.009423515,"domain_scores_codex":[0.9832872,0.00292532,0.001541033,0.001243396,0.01012062,0.0008823577],"domain_scores_gemma":[0.8874087,0.05396513,0.004143404,0.002938497,0.03802626,0.01351804],"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":[0.00001353652,0.000007007415,0.00001187632,0.0001386082,0.00001478947,0.00004192822,0.00001063127,0.00002089888,0.00003113105,0.0007581807,0.9948882,0.004063257],"study_design_scores_gemma":[0.00007184871,0.00002301088,0.0002304269,0.0005098217,0.00005503964,0.0001525487,0.00005561036,0.0002312758,0.00007711977,0.005841989,0.9927149,0.00003633532],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00001253556,0.00257208,0.0002079962,0.04065134,0.9549792,0.00001763604,0.00003471195,0.00007843585,0.001445989],"genre_scores_gemma":[0.0002101693,0.001917821,0.0001880457,0.02032786,0.9721639,0.0000180771,0.00001575416,0.00003839725,0.005119856],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.0273961,"threshold_uncertainty_score":0.1178263,"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."}}