{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002849187,0.0003188079,0.001109834,0.0009279262,0.0001581504,0.00002778049,0.0003886079,0.00006213818,0.00004989494],"category_scores_gemma":[0.002042226,0.0002137363,0.0005522476,0.001833197,0.0002807417,0.000176609,0.00004092612,0.0004047758,0.000002736641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001390799,"about_ca_system_score_gemma":0.0001503319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009246712,"about_ca_topic_score_gemma":0.000001472153,"domain_scores_codex":[0.9961434,0.0008337463,0.001508783,0.0004174452,0.0006944304,0.0004022025],"domain_scores_gemma":[0.9960112,0.0004152357,0.001829216,0.0004602796,0.001156911,0.0001271444],"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":[0.001574512,0.0002872231,0.01134072,0.0001479731,0.0008424494,0.000006892533,0.0000935369,0.0003643556,0.9842167,0.0006847052,0.0003401196,0.0001008229],"study_design_scores_gemma":[0.004442576,0.001939198,0.1402017,0.0002382358,0.0004361529,0.00002634177,0.000145823,0.0001810948,0.8514307,0.0003430648,0.0004242928,0.000190813],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966404,0.00323343,0.02754795,0.001144238,0.0004687688,0.0007529656,0.0001027743,0.00002292138,0.0003229812],"genre_scores_gemma":[0.9858512,0.0002837299,0.01282807,0.00007480135,0.0008311422,0.000008769592,0.00000756304,0.00005861255,0.00005611442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.132786,"threshold_uncertainty_score":0.8715915,"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."}}