{"id":"W2074904129","doi":"10.1255/ejms.1236","title":"Liquid Chromatography-High Resolution/High Accuracy (Tandem) Mass Spectrometry-Based Identification of <i>in vivo</i> Generated Metabolites of the Selective Androgen Receptor Modulator ACP-105 for Doping Control Purposes","year":2014,"lang":"en","type":"article","venue":"European Journal of Mass Spectrometry","topic":"Hormonal and reproductive studies","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Chromatography; Chemistry; In vivo; Derivatization; Analyte; Tandem mass spectrometry; Hydroxylation; Mass spectrometry; Liquid chromatography–mass spectrometry; Urine; Pharmacology; Biochemistry; Enzyme; Medicine; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002079122,0.0005284655,0.0002201834,0.0004783873,0.0001978966,0.0002539566,0.0002115434,0.0004005788,0.0007991399],"category_scores_gemma":[0.0002792032,0.0001479393,0.0002932624,0.0003041458,0.0002689914,0.0002646587,0.0001544563,0.0003673284,0.0002939269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002013151,"about_ca_system_score_gemma":0.000409512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006201093,"about_ca_topic_score_gemma":0.001060267,"domain_scores_codex":[0.9997974,0.00003689072,0.00001007946,0.0000492258,0.00007909808,0.00002723811],"domain_scores_gemma":[0.9998443,0.0000248851,0.00006917011,0.000009455032,0.00003202567,0.00002012182],"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":[0.0003482572,0.00005598289,0.001372191,0.00005595904,0.00002488672,0.00008816136,0.00001764105,0.00008931541,0.9909897,0.0000736896,0.00007559238,0.006808497],"study_design_scores_gemma":[0.0000169561,0.0008289651,0.009413951,0.000008361422,0.00004740589,0.0004251928,0.00002954982,0.001193539,0.9867215,0.00005130455,0.00125113,0.00001214112],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9595851,0.005183048,0.02990036,0.0001449924,0.00007637539,0.0001594043,0.0010501,0.0003390209,0.003561639],"genre_scores_gemma":[0.9749405,0.002922426,0.01869121,0.0002927387,0.00003738111,0.0001122402,0.000721895,0.00004408992,0.002237332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007991399,"threshold_uncertainty_score":0.002673447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01120051606344154,"score_gpt":0.2374292232221625,"score_spread":0.2262287071587209,"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."}}