{"id":"W2743306408","doi":"10.1002/dta.2256","title":"Determination of GnRH and its synthetic analogues' abuse in doping control: Small bioactive peptide UPLC–MS/MS method extension by addition of <i>in vitro</i> and <i>in vivo</i> metabolism data; evaluation of LH and steroid profile parameter fluctuations as suitable biomarkers","year":2017,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Hormonal and reproductive studies","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Buserelin; In vivo; Chemistry; Chromatography; Luteinizing hormone; Gonadotropin-releasing hormone; Solid phase extraction; Urine; High-performance liquid chromatography; Hormone; Endocrinology; Pharmacology; Internal medicine; Medicine; Biochemistry; Biology; Receptor; Agonist","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002546339,0.0001441713,0.000679012,0.0004866051,0.00009824275,0.00001829573,0.00005558194,0.00006226997,0.000002413742],"category_scores_gemma":[0.003714796,0.0001180273,0.00003705601,0.0003950074,0.0001867383,0.0002434191,0.00006969454,0.000106704,4.87181e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001904378,"about_ca_system_score_gemma":0.00002975771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001955987,"about_ca_topic_score_gemma":0.0004958485,"domain_scores_codex":[0.9983766,0.0003038878,0.0004582999,0.0004840961,0.0002381057,0.0001389987],"domain_scores_gemma":[0.9979693,0.0008511619,0.0004621373,0.0002893392,0.0003841682,0.0000438989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000398956,0.0002324625,0.1074591,0.0003251079,0.0005663497,0.000004538424,0.002603341,0.00008188156,0.8370403,0.000004140455,0.000005898137,0.0512779],"study_design_scores_gemma":[0.002578735,0.00007581584,0.5747064,0.0004936014,0.003181107,0.000009211877,0.001224491,0.3426028,0.07470718,0.0002575696,0.000002527654,0.0001606501],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958896,0.002907169,0.0002957483,0.000133747,0.00001053435,0.0004147239,0.0002724397,0.000004583846,0.00007145725],"genre_scores_gemma":[0.9928116,0.0003817117,0.006642576,0.000009885809,0.00001078838,0.00002615321,0.00009554662,0.000007540322,0.00001424314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7623331,"threshold_uncertainty_score":0.4813013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04775756985409013,"score_gpt":0.3229064619211731,"score_spread":0.275148892067083,"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."}}