{"id":"W3113372188","doi":"10.1177/1755738020972128","title":"Pharmacogenomics: Prescribing based on genetic variation","year":2020,"lang":"en","type":"article","venue":"InnovAiT Education and inspiration for general practice","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Pharmacogenomics; Polypharmacy; Medicine; Drug; Pharmacogenetics; Drug response; Disease; Intensive care medicine; Clinical decision support system; Function (biology); Adverse effect; Clinical Practice; Decision support system; Pharmacology; Family medicine; Computer science; Data mining; Internal medicine; 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":[0.002271851,0.0003765142,0.0005953466,0.001503387,0.0003510191,0.001684716,0.0004645517,0.001186194,0.009784919],"category_scores_gemma":[0.01047156,0.0001778672,0.000553189,0.002794482,0.0005467763,0.001067157,0.0006744874,0.001171498,0.003051535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009579636,"about_ca_system_score_gemma":0.0009494689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00619787,"about_ca_topic_score_gemma":0.005253845,"domain_scores_codex":[0.9970478,0.001351339,0.000348117,0.0003926917,0.0007518668,0.0001080856],"domain_scores_gemma":[0.9943181,0.003308126,0.001234678,0.0003579949,0.0005015985,0.0002795125],"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":[0.0005482069,0.0002552946,0.3335392,0.0007949578,0.0004878664,0.001836566,0.0004652389,0.00327179,0.002343601,0.02379028,0.1007322,0.5319349],"study_design_scores_gemma":[0.0002177875,0.0004861584,0.5539181,0.002605124,0.0007130823,0.01657426,0.0006561295,0.02378176,0.004542594,0.1486759,0.2475849,0.0002442668],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"review","genre_scores_codex":[0.2567638,0.06078028,0.103293,0.2597865,0.002931673,0.0005788661,0.03024386,0.00538142,0.2802406],"genre_scores_gemma":[0.8448597,0.03311516,0.0621598,0.0249156,0.003773315,0.0002152225,0.009095531,0.0006762532,0.02118932],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.009784919,"threshold_uncertainty_score":0.0327338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1459867145202045,"score_gpt":0.4460471017501133,"score_spread":0.3000603872299088,"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."}}