{"id":"W2023879359","doi":"10.1126/science.1062633","title":"Harnessing Genomics and Biotechnology to Improve Global Health Equity","year":2001,"lang":"en","type":"letter","venue":"Science","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health","funders":"","keywords":"Equity (law); Action plan; Genomics; Global health; Developing country; Business; Biotechnology; Economic growth; Health equity; Political science; Genome; Health care; Biology; Economics; Genetics; Management; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01065966,0.000930967,0.0009462922,0.0007150579,0.004582744,0.008142008,0.002172015,0.09012778,0.006245407],"category_scores_gemma":[0.02773697,0.0006545534,0.001115796,0.0007568197,0.01288761,0.01220104,0.003633493,0.05198256,0.003814721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006404322,"about_ca_system_score_gemma":0.006376222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004437636,"about_ca_topic_score_gemma":0.007715076,"domain_scores_codex":[0.9915636,0.00420053,0.0004359589,0.0008922109,0.001838671,0.001069152],"domain_scores_gemma":[0.9861323,0.01000811,0.0007749801,0.0004442246,0.001015703,0.001624759],"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":[0.0001731164,0.0001318001,0.001145174,0.0002065236,0.00004664001,0.001962786,0.001023048,0.000300299,0.000814308,0.05534106,0.9118254,0.02702992],"study_design_scores_gemma":[0.0003417162,0.000194943,0.001835699,0.0005869409,0.00004010533,0.00161602,0.002643567,0.0009961291,0.0006148593,0.09082853,0.9001939,0.0001076083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003214253,0.001207176,0.0001186859,0.9944842,0.002112697,0.000008833604,0.000007446143,0.00001014986,0.001729285],"genre_scores_gemma":[0.00463629,0.000775199,0.0003206405,0.9872268,0.003957185,0.0000312981,0.000005488942,0.000005932846,0.003041219],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.09012778,"threshold_uncertainty_score":0.05637437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910686408977638,"score_gpt":0.3344653411614051,"score_spread":0.3153584770716287,"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."}}