{"id":"W4394619873","doi":"10.1038/d41586-024-01001-y","title":"AI can help to tailor drugs for Africa — but Africans should lead the way","year":2024,"lang":"en","type":"article","venue":"Nature","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Discovery Centre","funders":"","keywords":"Lead (geology); Drug development; Data science; Computer science; Risk analysis (engineering); Business; Drug; Medicine; Pharmacology; Biology","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":[0.0003996853,0.000176764,0.0001334562,0.00007392509,0.000133675,0.0001272105,0.0005191248,0.0009074425,0.00002775822],"category_scores_gemma":[0.0003818305,0.0001084987,0.0001560257,0.0002403455,0.0001316693,0.000003038506,0.0001933163,0.0009391806,0.00005184325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003044029,"about_ca_system_score_gemma":0.0002017174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001455888,"about_ca_topic_score_gemma":0.00008309069,"domain_scores_codex":[0.998538,0.00002818434,0.0001948284,0.0003279156,0.0004181572,0.0004929543],"domain_scores_gemma":[0.999144,0.00006316126,0.00002068067,0.0003892252,0.0001804719,0.0002024395],"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":[0.00008648611,0.00003482939,0.00001289603,0.0001653245,0.00009347203,0.000003913903,0.000946691,0.00000565399,0.1148396,0.0004851187,0.8382291,0.04509696],"study_design_scores_gemma":[0.0001628166,0.0003355395,0.00003914734,0.00002399417,0.00002001607,0.000004375705,0.0006754604,0.0004063337,0.07414272,0.0003371709,0.9236877,0.0001647254],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1515104,0.04258098,0.02441532,0.7146224,0.007925423,0.006271588,0.004547429,0.0003448318,0.04778161],"genre_scores_gemma":[0.9681031,0.0002305474,0.000976392,0.006739214,0.001116937,0.0001100248,0.0001610665,0.00003274374,0.02252995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8165928,"threshold_uncertainty_score":0.6999027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972123428006069,"score_gpt":0.3099230952159221,"score_spread":0.2902018609358614,"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."}}