{"id":"W3163983628","doi":"10.1111/cts.13083","title":"Pharmacogenomic‐based personalized medicine: Multistakeholder perspectives on implementational drivers and barriers in the Canadian healthcare system","year":2021,"lang":"en","type":"article","venue":"Clinical and Translational Science","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Health care; Pharmacogenomics; Personalized medicine; Medicine; Business; Public relations; Medical education; Family medicine; Knowledge management; Computer science; Political science; Bioinformatics; Pharmacology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002489773,0.0001290187,0.0001783107,0.0001220933,0.0008696881,0.0000380846,0.0001844745,0.00008566236,0.0004382988],"category_scores_gemma":[0.0001331914,0.00009716416,0.00004799219,0.0003561462,0.002025574,0.00007520959,0.00001302118,0.0004537537,0.000004186998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004778255,"about_ca_system_score_gemma":0.001300351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305758,"about_ca_topic_score_gemma":0.005777961,"domain_scores_codex":[0.9979841,0.0005450302,0.0003460487,0.0004581403,0.0003461895,0.0003204518],"domain_scores_gemma":[0.9982483,0.0008695961,0.00005670184,0.0000785861,0.0001591035,0.0005876634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004788925,0.0002588933,0.6047159,0.0001082346,0.0001276601,0.0002731133,0.02496911,0.000711627,0.006283227,0.3273593,0.000705693,0.03400834],"study_design_scores_gemma":[0.01418932,0.0001489103,0.8013978,0.00005680034,0.0002036363,0.00008038566,0.02069762,0.03110496,0.0007439759,0.001640294,0.1292488,0.0004875109],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9527321,0.002917514,0.0000437143,0.04066239,0.0006143684,0.0003606212,0.0002862434,0.00001247046,0.002370615],"genre_scores_gemma":[0.9903514,0.0003518556,0.0002338256,0.00880523,0.0001874259,0.00001910711,0.00002406286,0.000005180535,0.00002189445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.325719,"threshold_uncertainty_score":0.7463312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2621606496445811,"score_gpt":0.5196457410110468,"score_spread":0.2574850913664657,"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."}}