{"id":"W4365151016","doi":"10.1016/j.jpha.2023.04.005","title":"In vivo solid phase microextraction for therapeutic monitoring and pharmacometabolomic fingerprinting of lung during in vivo lung perfusion of FOLFOX","year":2023,"lang":"en","type":"article","venue":"Journal of Pharmaceutical Analysis","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"In vivo; Chemistry; Pharmacology; FOLFOX; Lung; Therapeutic drug monitoring; Pharmacokinetics; Perfusion; Metabolite; Solid-phase microextraction; Metabolomics; Oxaliplatin; Chromatography; Medicine; Gas chromatography–mass spectrometry; Mass spectrometry; Internal medicine; Cancer; Colorectal cancer; Biochemistry","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":[0.0009015844,0.0001430697,0.0005734169,0.0008845013,0.00004746809,0.00001091648,0.0001239906,0.00007293328,0.00003840792],"category_scores_gemma":[0.00009751491,0.0001295199,0.0003091868,0.0008757688,0.00004730516,0.00001993862,0.00009342586,0.0001769261,7.776415e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003167684,"about_ca_system_score_gemma":0.00002646271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001179166,"about_ca_topic_score_gemma":0.000004432412,"domain_scores_codex":[0.9985325,0.00007874203,0.0007650936,0.0002027458,0.0001670081,0.0002538923],"domain_scores_gemma":[0.9991823,0.0000921898,0.0004329533,0.00009263932,0.0001332871,0.0000666664],"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":[0.0005047862,0.0001763261,0.05994328,0.0001427295,0.0008554445,0.00000633333,0.0001104843,0.0008090296,0.9366275,0.000007069051,0.00002411809,0.0007928869],"study_design_scores_gemma":[0.002639757,0.00008238235,0.01087842,0.00003712114,0.001016522,0.000007556089,0.0001681634,0.0146745,0.9700213,0.00002255048,0.0003400708,0.0001116235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940162,0.004517713,0.001003549,0.0001548335,0.0001519101,0.0001234856,0.0000162468,0.000002186485,0.00001383785],"genre_scores_gemma":[0.9891638,0.01022202,0.0003612096,0.00001272966,0.0001624555,0.000005882564,0.000001437943,0.00001266824,0.00005784787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04906486,"threshold_uncertainty_score":0.5281668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141618819115709,"score_gpt":0.390828517422514,"score_spread":0.3694123292313569,"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."}}