{"id":"W3024799945","doi":"10.1021/acschemneuro.0c00270","title":"Investigation of Early Death-Induced Changes in Rat Brain by Solid Phase Microextraction via Untargeted High Resolution Mass Spectrometry: <i>In Vivo</i> versus Postmortem Comparative Study","year":2020,"lang":"en","type":"article","venue":"ACS Chemical Neuroscience","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Addiction and Mental Health; University of Waterloo","funders":"Ontario Brain Institute; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Merck; Pfizer","keywords":"Neurochemical; In vivo; Neurochemistry; Metabolomics; Metabolite; Mass spectrometry; Solid-phase microextraction; Forensic toxicology; Chemistry; Postmortem Changes; Neuroscience; Biology; Gas chromatography–mass spectrometry; Pathology; Medicine; Biochemistry; Chromatography; Neurology; Genetics","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":[0.0001986076,0.0001999805,0.0003248296,0.00009945211,0.00004805211,0.00002154167,0.0002517877,0.00009339384,0.000003757028],"category_scores_gemma":[0.0002671004,0.000205696,0.00003592372,0.0008308572,0.0001171099,0.00002135896,0.0001136347,0.0002042216,0.000001005094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004176025,"about_ca_system_score_gemma":0.00003653448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001066768,"about_ca_topic_score_gemma":0.00005845535,"domain_scores_codex":[0.9983525,0.0001219211,0.0003309469,0.0006425398,0.0002397139,0.0003124251],"domain_scores_gemma":[0.9994143,0.00004908684,0.0001832771,0.0001888312,0.00005391564,0.0001105721],"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":[0.0006084191,0.0001838967,0.003085106,0.000006891992,0.000008055586,0.000004765605,0.000207416,0.000005899999,0.995571,0.00001215118,0.0002818799,0.00002453877],"study_design_scores_gemma":[0.002551015,0.002217476,0.003568969,0.00000473744,0.00001255454,0.000001259284,0.0001301302,0.0002428618,0.9909331,0.00002122009,0.0001370392,0.0001797066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979725,0.0001167672,0.0002730826,0.0009790187,0.0001880792,0.0004006676,0.00003423402,0.00001137332,0.0000243127],"genre_scores_gemma":[0.9991249,0.00005454722,0.000238597,0.000440409,0.00006155718,0.00002397937,0.0000343486,0.00001191822,0.000009704913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004637949,"threshold_uncertainty_score":0.8388039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04440250602738062,"score_gpt":0.3114059400491536,"score_spread":0.267003434021773,"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."}}