{"id":"W1981910484","doi":"10.1007/s00216-013-6993-z","title":"Determination of cocaine and methadone in urine samples by thin-film solid-phase microextraction and direct analysis in real time (DART) coupled with tandem mass spectrometry","year":2013,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"World Anti-Doping Agency","keywords":"DART ion source; Chromatography; Solid-phase microextraction; Chemistry; Ion-mobility spectrometry; Urine; Sample preparation; Dart; Extraction (chemistry); Mass spectrometry; Tandem mass spectrometry; Analytical Chemistry (journal); Gas chromatography–mass spectrometry; Ion; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007309756,0.0002995894,0.0009365623,0.0003274102,0.00007913569,0.00003278615,0.00009652888,0.0004709737,0.00110907],"category_scores_gemma":[0.0002100285,0.000240497,0.0001039443,0.001129054,0.0009979826,0.0001385193,0.00006183732,0.0005928491,0.000004640245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006460746,"about_ca_system_score_gemma":0.00003802541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003426174,"about_ca_topic_score_gemma":0.0002197668,"domain_scores_codex":[0.9980126,0.0001613578,0.0006327885,0.0005792395,0.0001884515,0.0004255382],"domain_scores_gemma":[0.9983323,0.0009168414,0.0001707198,0.0001645908,0.00009370493,0.0003218104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001219352,0.001800644,0.2710841,0.0002542835,0.002560545,0.0001596278,0.0001557676,0.0001715968,0.7194858,0.0001974499,0.0003034403,0.002607431],"study_design_scores_gemma":[0.004875599,0.0003899756,0.03761818,0.00003590366,0.004194662,0.00005140897,0.0002703494,0.8588946,0.09224207,0.0007703934,0.0001077961,0.0005490121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966013,0.0004193578,0.0004450225,0.001037118,0.000008865349,0.0001598608,0.00005343024,0.00002329455,0.001251748],"genre_scores_gemma":[0.9975737,0.0006811786,0.0006457725,0.0001400234,0.00003259405,0.00001222078,0.0001005832,0.00001188569,0.0008020641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.858723,"threshold_uncertainty_score":0.9998041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366436773834694,"score_gpt":0.3636401904052965,"score_spread":0.3399758226669496,"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."}}