{"id":"W1996774767","doi":"10.1016/j.jchromb.2010.12.020","title":"A validated enantioselective assay for the simultaneous quantitation of (R)-, (S)-fluoxetine and (R)-, (S)-norfluoxetine in ovine plasma using liquid chromatography with tandem mass spectrometry (LC/MS/MS)","year":2010,"lang":"en","type":"article","venue":"Journal of Chromatography B","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Child and Family Research Institute; Eli Lilly and Company","keywords":"Chemistry; Chromatography; Tandem mass spectrometry; Analyte; Selected reaction monitoring; Detection limit; Liquid chromatography–mass spectrometry; Fluoxetine; Mass spectrometry; High-performance liquid chromatography; Extraction (chemistry)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001733328,0.001641392,0.001263509,0.001100686,0.0009452227,0.0007275369,0.001321451,0.001636748,0.001383418],"category_scores_gemma":[0.001803979,0.000863312,0.0008684074,0.0005344562,0.0009143009,0.0006115023,0.0007370542,0.001378206,0.001390933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009725416,"about_ca_system_score_gemma":0.002459683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003452047,"about_ca_topic_score_gemma":0.01048084,"domain_scores_codex":[0.9977735,0.0004713963,0.0001464623,0.0005767563,0.0008497273,0.0001821443],"domain_scores_gemma":[0.9990124,0.0001905151,0.0002213258,0.000119412,0.0003018048,0.0001546459],"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":[0.00077179,0.0001901035,0.001693477,0.0001655636,0.0001340212,0.0002785297,0.00006337051,0.0002029617,0.9772932,0.0002065164,0.0006941187,0.0183063],"study_design_scores_gemma":[0.0003205786,0.001891972,0.007752821,0.00005326462,0.0002454096,0.003979073,0.00005377907,0.003449815,0.9746728,0.0001236801,0.007371047,0.00008580711],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7028466,0.02141192,0.2481373,0.001192895,0.00137004,0.003556649,0.007117753,0.003811425,0.01055541],"genre_scores_gemma":[0.7603003,0.008556099,0.2051739,0.00264709,0.0005362011,0.002031555,0.007793003,0.0002897852,0.01267198],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003452047,"threshold_uncertainty_score":0.009166837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008732208996318777,"score_gpt":0.2470164362540316,"score_spread":0.2382842272577128,"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."}}