{"id":"W4383070034","doi":"10.3389/fonc.2023.1199741","title":"Computational pharmacogenotype extraction from clinical next-generation sequencing","year":2023,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Pharmacogenetics and Drug Metabolism","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Genotyping; Pharmacogenomics; DNA sequencing; 1000 Genomes Project; Reference genome; DPYD; Genetics; Exome sequencing; Whole genome sequencing; Biology; Computational biology; Genotype; Genome; Single-nucleotide polymorphism; Pharmacogenetics; Gene; Mutation","routes":{"ca_aff":true,"ca_fund":true,"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"],"consensus_categories":[],"category_scores_codex":[0.002102924,0.0002495192,0.0005111828,0.0004149369,0.0002260359,0.00002713742,0.0003160466,0.0006342476,0.0008979613],"category_scores_gemma":[0.000184115,0.0002773754,0.000146565,0.0006576175,0.0002139593,0.0002141648,0.0001072055,0.001194524,0.0006026083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003877836,"about_ca_system_score_gemma":0.0004830182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006837074,"about_ca_topic_score_gemma":0.00003657539,"domain_scores_codex":[0.996269,0.001457087,0.0008760627,0.0005957808,0.0002191501,0.000582887],"domain_scores_gemma":[0.9984631,0.0007254179,0.0002554206,0.000163131,0.0001123003,0.0002806281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005407935,0.0003921232,0.05962838,0.00001176577,0.000324148,0.0003719511,0.0009961791,0.07486487,0.1118462,0.0002315903,0.2276856,0.5231065],"study_design_scores_gemma":[0.003121222,0.00008620704,0.00773424,0.000004172606,0.0001382396,0.00001173544,0.0002798325,0.4982565,0.005621154,0.004028319,0.4804362,0.0002821081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9555135,0.002031325,0.007782132,0.001567225,0.02876117,0.000477207,0.0001246336,0.0002293171,0.003513425],"genre_scores_gemma":[0.9724188,0.00423854,0.01365183,0.005053155,0.0032378,0.0001061765,0.0007259332,0.00004972101,0.0005179966],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5228243,"threshold_uncertainty_score":0.9999678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4059619616281072,"score_gpt":0.5253191977642967,"score_spread":0.1193572361361895,"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."}}