{"id":"W4402193846","doi":"10.1038/s41591-024-03225-x","title":"The WHO genomics program of work for equitable implementation of human genomics for global health","year":2024,"lang":"en","type":"letter","venue":"Nature Medicine","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"World Health Organization","keywords":"Genomics; Work (physics); Computational biology; Data science; Computer science; Biology; Genome; Genetics; Engineering; Gene","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":[0.001176453,0.000242679,0.0004764618,0.00006385049,0.00013548,0.00002188732,0.0005287093,0.0009537038,0.000005301175],"category_scores_gemma":[0.0001961389,0.0001561442,0.0002057763,0.0001521499,0.0004031023,0.000001600941,0.0001803006,0.000588545,4.804463e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001332588,"about_ca_system_score_gemma":0.0006970826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003408175,"about_ca_topic_score_gemma":0.0001356078,"domain_scores_codex":[0.997777,0.00003608275,0.0008125267,0.0003114366,0.0004420955,0.0006208024],"domain_scores_gemma":[0.9985391,0.00008690102,0.0004383374,0.0004208568,0.0004240432,0.0000907557],"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":[0.00007387488,0.0000175754,0.0000210129,0.001929677,0.0001938806,4.237181e-7,0.00009311621,3.988032e-7,0.002376683,0.0001288288,0.9119732,0.08319135],"study_design_scores_gemma":[0.0009056935,0.003027188,0.00005301745,0.0001701048,0.00009491303,0.000002203937,0.0002766205,0.00002144177,0.006109849,0.001262081,0.9879455,0.0001313658],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01136154,0.074211,0.00591143,0.8884104,0.003871999,0.01155005,0.003872497,0.00003826648,0.0007727894],"genre_scores_gemma":[0.05424824,0.036839,0.04669209,0.6671842,0.07451868,0.003164191,0.09859378,0.0006440865,0.01811569],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.2212262,"threshold_uncertainty_score":0.7355837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02107291514021037,"score_gpt":0.4053531972574316,"score_spread":0.3842802821172213,"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."}}