{"id":"W2125789792","doi":"10.1093/jat/32.8.631","title":"Effects of Tissue Type and the Dose-Death Interval on the Detection of Acute Ketamine Exposure in Bone and Marrow with Solid-Phase Extraction and ELISA with Liquid Chromatography-Tandem Mass Spectrometry Confirmation","year":2008,"lang":"en","type":"article","venue":"Journal of Analytical Toxicology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chromatography; Chemistry; Ketamine; Tandem mass spectrometry; Solid phase extraction; Detection limit; Bone marrow; Extraction (chemistry); Liquid chromatography–mass spectrometry; Mass spectrometry; Internal medicine; Medicine; Anesthesia","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":[],"consensus_categories":[],"category_scores_codex":[0.0003267783,0.0001099207,0.0003850403,0.0001489373,0.00004870804,0.00000697622,0.00004447371,0.00008714017,0.000006754308],"category_scores_gemma":[0.0001442822,0.00005590005,0.00003622994,0.0001962008,0.0003903855,0.000009198388,0.0000242228,0.0001656813,4.725434e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008504008,"about_ca_system_score_gemma":0.00002534302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003335275,"about_ca_topic_score_gemma":0.00001457596,"domain_scores_codex":[0.9992341,0.0001273767,0.00029484,0.0001185405,0.0001169001,0.0001081858],"domain_scores_gemma":[0.999258,0.0001833327,0.0003178151,0.0000824321,0.0001179018,0.00004055788],"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":[0.005663759,0.0001435544,0.001499252,0.00003331966,0.0005135993,0.00003733322,0.00007111279,0.000003429936,0.9913836,0.0003822912,0.00002401463,0.0002447383],"study_design_scores_gemma":[0.00823555,0.03126561,0.08923561,0.00007667504,0.0005767984,0.001744862,0.0002080135,0.0002714606,0.867709,0.0001458722,0.0003797283,0.0001508337],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963849,0.001522855,0.001434345,0.0003839516,0.0000322729,0.000162019,0.000003592183,0.000001060836,0.00007505929],"genre_scores_gemma":[0.9963338,0.003225225,0.0003035822,0.00005632643,0.0000497197,0.000003097659,0.000001373759,0.000006482603,0.00002034681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1236746,"threshold_uncertainty_score":0.2279538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009086167106220832,"score_gpt":0.2805785991433931,"score_spread":0.2714924320371723,"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."}}