{"id":"W2039767677","doi":"10.1002/rcm.2372","title":"Screening for amphetamine and amphetamine‐type drugs in doping analysis by liquid chromatography/mass spectrometry","year":2006,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"Chemistry; Chromatography; Detection limit; Mass spectrometry; Amphetamine; Diethyl ether; Extraction (chemistry); Liquid chromatography–mass spectrometry; Urine; Phenethylamines; Atmospheric-pressure chemical ionization; Ether; Analytical Chemistry (journal); Chemical ionization; Ionization; Ion; Organic chemistry; Stereochemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002044245,0.000474349,0.001066492,0.003516576,0.0004893274,0.00006471781,0.001127254,0.0006016089,0.0005257406],"category_scores_gemma":[0.0001887046,0.0005332657,0.0003984619,0.008536221,0.0008109982,0.0002430331,0.0002536575,0.001328992,0.00001370404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002533493,"about_ca_system_score_gemma":0.00006291724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003069008,"about_ca_topic_score_gemma":0.0009145795,"domain_scores_codex":[0.9960414,0.0009259912,0.001110783,0.0007497329,0.0002400614,0.0009320038],"domain_scores_gemma":[0.9959009,0.002011338,0.0004037532,0.001399281,0.0001132938,0.0001714231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001278065,0.002515951,0.721018,0.0001813834,0.004982222,0.00002219581,0.000750303,0.005187388,0.2328689,0.02371766,0.0038482,0.003629699],"study_design_scores_gemma":[0.02540217,0.002935329,0.4472875,0.0002711682,0.01130528,0.00008171808,0.005823576,0.3239491,0.1055359,0.02258329,0.04895916,0.005865815],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9406418,0.02365013,0.02479731,0.003190618,0.0002611063,0.0009000797,0.0001539945,0.0002129467,0.006191974],"genre_scores_gemma":[0.9441019,0.003687367,0.05051001,0.0003648692,0.0001022664,0.0001394963,0.0006763659,0.0000468561,0.0003708416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3187617,"threshold_uncertainty_score":0.9997119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04470121969446741,"score_gpt":0.3764035460801314,"score_spread":0.331702326385664,"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."}}