{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01090667,0.001777064,0.001709229,0.001775778,0.002452112,0.006096308,0.00172711,0.005855579,0.0491145],"category_scores_gemma":[0.024643,0.0005389487,0.001538205,0.001884627,0.005450164,0.01397079,0.004923653,0.01663214,0.01872356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002399353,"about_ca_system_score_gemma":0.007076694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004225018,"about_ca_topic_score_gemma":0.002968425,"domain_scores_codex":[0.9968863,0.001478789,0.000162895,0.0003105393,0.000658648,0.0005027804],"domain_scores_gemma":[0.9850221,0.007119118,0.001180422,0.001198602,0.002524574,0.002955066],"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":[0.001013579,0.0004471655,0.005897571,0.001938279,0.000655706,0.0006601521,0.0006514145,0.002608149,0.00772415,0.1629046,0.4741859,0.3413133],"study_design_scores_gemma":[0.0002661795,0.0003182707,0.00163227,0.001532348,0.0001965989,0.0005033839,0.0008503856,0.001350511,0.001901092,0.2259546,0.7653801,0.0001142504],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003534297,0.04959203,0.01934795,0.856609,0.01641271,0.0001758918,0.001152986,0.0009871476,0.05218806],"genre_scores_gemma":[0.1438376,0.1160647,0.08177095,0.578927,0.02011762,0.0006748203,0.002142361,0.001256371,0.05520857],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.0491145,"threshold_uncertainty_score":0.1643044,"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."}}