{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009210917,0.0008350202,0.0004115894,0.001017935,0.0004369839,0.000522074,0.000382095,0.0006575434,0.001423911],"category_scores_gemma":[0.001136022,0.0003625265,0.0004071477,0.0006302915,0.0005505494,0.0003776916,0.0003668177,0.0005426428,0.0005272065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003190366,"about_ca_system_score_gemma":0.0007401864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007314489,"about_ca_topic_score_gemma":0.001708076,"domain_scores_codex":[0.9986653,0.0002134991,0.00009416099,0.0003519004,0.0006036453,0.00007141829],"domain_scores_gemma":[0.9994394,0.0001151451,0.0002034037,0.00004267329,0.0001677899,0.00003156497],"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":[0.0006552845,0.000122385,0.008514578,0.000367066,0.00009763436,0.0003363283,0.0001250362,0.0001891735,0.9573107,0.0002541823,0.0004273823,0.03160024],"study_design_scores_gemma":[0.00004123823,0.001220905,0.03412896,0.0000828,0.0001726187,0.002244715,0.0001153773,0.003166365,0.9493214,0.0002111841,0.009225965,0.00006850471],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8761861,0.01789962,0.09215617,0.0003549247,0.0004244629,0.000790703,0.003116726,0.0005579201,0.008513231],"genre_scores_gemma":[0.8946628,0.008667941,0.08398055,0.0007277424,0.0001601831,0.001140594,0.002474382,0.0001670205,0.008018749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001423911,"threshold_uncertainty_score":0.004871249,"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."}}