{"id":"W2076132513","doi":"10.2174/187569211798377171","title":"Not So Simple: Situating Postgenomics Personalized Medicine in the Regional Context in Africa for Global and Womens Health","year":2011,"lang":"en","type":"article","venue":"Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Economic and Social Research Council","keywords":"Context (archaeology); Personalized medicine; Public health; Genomics; Precision medicine; Global health; Medicine; Political science; Environmental health; Economic growth; Geography; Nursing; Bioinformatics; Genetics; Biology; Genome; Pathology","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.004035747,0.001088112,0.001659006,0.0004826889,0.0005585838,0.00005957514,0.0007911756,0.0002774601,0.0001941377],"category_scores_gemma":[0.0004888641,0.0007981646,0.0002253829,0.0005226376,0.003874904,0.00004395032,0.0003667236,0.000988203,0.000001726601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253939,"about_ca_system_score_gemma":0.0007066435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005084267,"about_ca_topic_score_gemma":0.000265292,"domain_scores_codex":[0.9934251,0.0005059419,0.002032019,0.001458842,0.0009564936,0.001621598],"domain_scores_gemma":[0.996686,0.0004799291,0.0007721962,0.0004331594,0.0003680332,0.001260611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01322279,0.002329051,0.01051275,0.004971974,0.001042238,0.00006201051,0.1365032,0.000008123739,0.0792652,0.005770979,0.03884152,0.7074702],"study_design_scores_gemma":[0.04840159,0.002897086,0.003016176,0.001167738,0.0006008045,0.0003375273,0.02770594,0.008831236,0.0001577865,0.001342164,0.9041538,0.001388136],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6860235,0.2884627,0.001143391,0.01722028,0.001507745,0.003379988,0.001987725,0.00003434196,0.000240275],"genre_scores_gemma":[0.6229012,0.3560415,0.0007574213,0.01205972,0.003714821,0.0002488919,0.004007992,0.0001225138,0.0001459407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8653123,"threshold_uncertainty_score":0.9994469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1543801698113977,"score_gpt":0.4053232881478397,"score_spread":0.250943118336442,"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."}}