{"id":"W3209313881","doi":"10.1002/bmc.5274","title":"Urinary phenylethylamine metabolites as potential markers for sports drug testing purposes","year":2021,"lang":"en","type":"article","venue":"Biomedical Chromatography","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesministerium des Innern, für Bau und Heimat; World Anti-Doping Agency","keywords":"Metabolite; Urine; Chemistry; Urinary system; Population; Pharmacology; Oral administration; Chromatography; Internal medicine; Medicine; Biochemistry; Environmental health","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":[0.002260485,0.0007818502,0.0006324704,0.003185497,0.0005016797,0.001256712,0.0004902079,0.001064101,0.001491843],"category_scores_gemma":[0.003082055,0.0003867921,0.0005446635,0.002134557,0.0006014991,0.0004539839,0.0005452306,0.0007306624,0.0004987334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000350708,"about_ca_system_score_gemma":0.0006767539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001554436,"about_ca_topic_score_gemma":0.002627561,"domain_scores_codex":[0.9976427,0.0009993903,0.0001728186,0.0003199359,0.0007194577,0.0001455745],"domain_scores_gemma":[0.9980573,0.0005845688,0.0006814865,0.0001186008,0.0004349857,0.0001230008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003128788,0.0007155783,0.6594415,0.001167869,0.0008119316,0.001608082,0.0006000358,0.0008427392,0.1843525,0.0007576899,0.001135852,0.1454375],"study_design_scores_gemma":[0.00009020498,0.006060409,0.6882681,0.0004513614,0.001024721,0.007233511,0.0009164146,0.0066448,0.2730034,0.001201152,0.01499589,0.0001100516],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.925311,0.05079642,0.0138871,0.0004560437,0.0001871334,0.0002716019,0.002568622,0.0003672944,0.006154836],"genre_scores_gemma":[0.9823734,0.00583815,0.008814548,0.0002795437,0.0000877455,0.00007622807,0.0007516585,0.00002590753,0.001752845],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003185497,"threshold_uncertainty_score":0.01195478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03665500234599967,"score_gpt":0.35949165386083,"score_spread":0.3228366515148304,"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."}}