{"id":"W1970064806","doi":"10.1038/sj.tpj.6500361","title":"Pharmacogenetics and pharmacogenomics: origin, status, and the hope for personalized medicine","year":2006,"lang":"en","type":"article","venue":"The Pharmacogenomics Journal","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":129,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pharmacogenomics; Pharmacogenetics; Personalized medicine; Precision medicine; Medicine; Disease; Drug; Ethnic group; Drug response; Bioinformatics; Gene; Pharmacology; Genetics; Biology; Internal medicine; Genotype; Pathology; Political science","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":["sts"],"category_scores_codex":[0.005922575,0.0008009776,0.0009087083,0.000253409,0.002569141,0.0002455186,0.001002104,0.0002303425,0.0008307797],"category_scores_gemma":[0.0001240367,0.0004854494,0.0003403002,0.0003252611,0.003305616,0.0001992542,0.0003585737,0.001860587,0.00002716526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001534736,"about_ca_system_score_gemma":0.0002637477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009794506,"about_ca_topic_score_gemma":0.00001054606,"domain_scores_codex":[0.9946716,0.001392715,0.001318717,0.0006706321,0.0004576017,0.001488733],"domain_scores_gemma":[0.9954794,0.002149711,0.0007989184,0.0003333753,0.0004240499,0.0008145327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0174954,0.000609273,0.005679016,0.0002510276,0.004095404,0.000116405,0.008161003,0.004065462,0.6313423,0.06609626,0.09374123,0.1683472],"study_design_scores_gemma":[0.03563749,0.00009614515,0.0002803164,0.00001490737,0.003125609,0.00112916,0.0003718383,0.0184481,0.01238758,0.01476547,0.9131042,0.000639205],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8170495,0.1501686,0.001987416,0.02058796,0.004750261,0.002654368,0.0004594334,0.00009971274,0.002242724],"genre_scores_gemma":[0.8395876,0.1339551,0.0006899919,0.01488054,0.008068712,0.0002429912,0.00005057252,0.0001841933,0.00234038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8193629,"threshold_uncertainty_score":0.9997597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09054567564092775,"score_gpt":0.4204349707298063,"score_spread":0.3298892950888785,"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."}}