{"id":"W3135165039","doi":"10.1002/rcm.9080","title":"Detection of urinary arimistane metabolites in humans using liquid chromatography–mass spectrometry: Complementary results to gas chromatography mass spectrometric data and its application to antidoping analyses","year":2021,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Hormonal and reproductive studies","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Chemistry; Chromatography; Metabolite; Mass spectrometry; Urine; Gas chromatography–mass spectrometry; Gas chromatography; Tandem mass spectrometry; Liquid chromatography–mass spectrometry; Hydroxylation; Biochemistry; Enzyme","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":[0.0009356777,0.0007178334,0.0004971927,0.001311796,0.000273282,0.0004437723,0.0003692741,0.0009849735,0.0005581806],"category_scores_gemma":[0.001408522,0.0002420777,0.0004033666,0.0008416437,0.0005475458,0.0003512929,0.0002886882,0.0005436961,0.000286812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002155947,"about_ca_system_score_gemma":0.0004909091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000691195,"about_ca_topic_score_gemma":0.001017501,"domain_scores_codex":[0.9988273,0.0003087314,0.00005908493,0.0002886337,0.0004588023,0.00005748223],"domain_scores_gemma":[0.9994565,0.0001427595,0.0001760064,0.00005410555,0.0001219436,0.00004876148],"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":[0.001837005,0.0002617678,0.04138824,0.0004795089,0.0002891862,0.0004559446,0.0001491734,0.0002711448,0.9016678,0.0001510719,0.0002855346,0.05276373],"study_design_scores_gemma":[0.0001059101,0.00459089,0.1396028,0.00009865794,0.0005559142,0.00547717,0.0001480805,0.004511453,0.8389458,0.0004441227,0.005427029,0.00009227029],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.91153,0.0279192,0.05508475,0.0004702181,0.0001520537,0.0002952681,0.001364461,0.0007271138,0.002456922],"genre_scores_gemma":[0.9564909,0.005697527,0.03527437,0.0007089709,0.0001501911,0.0001736076,0.0004490142,0.00004858158,0.001006828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001311796,"threshold_uncertainty_score":0.004948378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08926823702321778,"score_gpt":0.3739345521620684,"score_spread":0.2846663151388506,"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."}}