{"id":"W2081167062","doi":"10.1038/nrg2443","title":"Universal health care, genomic medicine and Thailand: investing in today and tomorrow","year":2008,"lang":"en","type":"review","venue":"Nature Reviews Genetics","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Global Health Research; Discovery Centre; University Health Network","funders":"Inyuvesi Yakwazulu-Natali; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Thailand Center of Excellence for Life Sciences; African Union; Yale University","keywords":"Genomic medicine; Excellence; Pharmacogenomics; Precision medicine; Diversity (politics); Health care; Genotyping; Biology; Personalized medicine; Population; Genomics; Biotechnology; Genetics; Medicine; Computational biology; Economic growth; Environmental health; Political science; Genome; Genotype","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","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0003245866,0.0004590388,0.002790855,0.0004062149,0.00008914766,0.000004548395,0.0001415342,0.006576016,0.000009934952],"category_scores_gemma":[0.0001742833,0.0003007668,0.0001385705,0.0004604871,0.0003190552,0.00001413169,0.0001234388,0.007460169,0.000006153825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001475997,"about_ca_system_score_gemma":0.000387771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002199372,"about_ca_topic_score_gemma":0.00005380424,"domain_scores_codex":[0.9979855,0.0002275171,0.0008014088,0.0005334286,0.0001313288,0.0003208093],"domain_scores_gemma":[0.9989328,0.0001061728,0.0003087636,0.0004204276,0.00003390963,0.00019789],"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":[0.000003877195,0.000009845976,0.00008327029,0.02070577,0.0000516414,0.00009600767,0.0003472134,3.258776e-8,9.15043e-7,0.0001045715,0.003309514,0.9752873],"study_design_scores_gemma":[0.0005097345,0.0002349814,0.00006264047,0.03337049,0.0004443924,0.00179146,0.00004398196,0.000001881177,4.436347e-7,0.000007185295,0.9633096,0.0002232064],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00003895812,0.9949031,0.000003720335,0.002550535,0.0002361323,0.001504145,0.000007475343,0.00003547467,0.0007205015],"genre_scores_gemma":[0.000009823485,0.9960126,0.00172604,0.001761908,0.0002198347,0.00001248678,0.0000899242,0.00004269553,0.0001247191],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9750642,"threshold_uncertainty_score":0.9999444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03984948018478891,"score_gpt":0.351738273195403,"score_spread":0.3118887930106141,"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."}}