{"id":"W2902282663","doi":"10.1016/j.jchromb.2018.12.003","title":"An LC-MS/MS method for quantification of abiraterone, its active metabolites D(4)-abiraterone (D4A) and 5α-abiraterone, and their inactive glucuronide derivatives","year":2018,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Prostate Cancer Treatment and Research","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Centre hospitalier de l'Université Laval; Centre hospitalier universitaire de Québec","funders":"Fondation CHU de Québec","keywords":"Chemistry; Chromatography; Selected reaction monitoring; Prostate cancer; Abiraterone acetate; Abiraterone; Analyte; Prodrug; CYP17A1; Pharmacology; Tandem mass spectrometry; Mass spectrometry; Androgen deprivation therapy; Androgen receptor; Biochemistry; Cancer; Enzyme; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008173298,0.001180827,0.0005143728,0.001555717,0.001196078,0.0006074301,0.0008938322,0.00130313,0.002280865],"category_scores_gemma":[0.001249664,0.0005563208,0.0005006996,0.0007171514,0.0005222281,0.0006076579,0.0007389333,0.00128681,0.001906058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009191354,"about_ca_system_score_gemma":0.002782322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002523358,"about_ca_topic_score_gemma":0.005045302,"domain_scores_codex":[0.9988012,0.0001295391,0.00008354189,0.0003056214,0.0005991852,0.00008082468],"domain_scores_gemma":[0.9993698,0.0001035884,0.00009673852,0.00004940647,0.0002422123,0.0001382586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000499734,0.0001220618,0.001765767,0.0002324478,0.0001007762,0.0001752616,0.0000482032,0.0002581422,0.9601943,0.000431834,0.001191748,0.03497979],"study_design_scores_gemma":[0.0001307018,0.0006487249,0.00549757,0.00006486086,0.0001712667,0.002861584,0.00007528198,0.005747483,0.9620141,0.0005549119,0.02213163,0.0001018242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.461574,0.02939127,0.4622229,0.001537588,0.002026581,0.002687338,0.009509019,0.008051053,0.02300015],"genre_scores_gemma":[0.6413319,0.008281577,0.3070746,0.003526825,0.0002952132,0.002419616,0.005555687,0.0003011771,0.03121339],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002523358,"threshold_uncertainty_score":0.007630229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03459903610339165,"score_gpt":0.3580245495373112,"score_spread":0.3234255134339195,"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."}}