{"id":"W2123551980","doi":"10.1039/c5mb00470e","title":"Potential of serum metabolites for diagnosing post-stroke cognitive impairment","year":2015,"lang":"en","type":"article","venue":"Molecular BioSystems","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; University of Lethbridge","keywords":"Stroke (engine); Kynurenine; Metabolite; Cognition; Medicine; Pathological; Metabolomics; Internal medicine; Omics; Kynurenine pathway; Cognitive impairment; Biomarker; Oxidative stress; Inflammation; Bioinformatics; Psychiatry; Biology; Biochemistry; Tryptophan","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000403793,0.0002217684,0.0003673808,0.0001061803,0.00005854271,0.00002797808,0.0001615771,0.000126161,0.000005238768],"category_scores_gemma":[0.0003007354,0.0002025731,0.0002720381,0.00009886001,0.00006975717,0.00000420241,0.0001455199,0.00004846356,0.000003551328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001499092,"about_ca_system_score_gemma":0.00009164005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003532798,"about_ca_topic_score_gemma":0.00001002774,"domain_scores_codex":[0.9986133,0.00009237207,0.0003469409,0.0003845688,0.0002267759,0.0003360543],"domain_scores_gemma":[0.9988521,0.00001913253,0.000192876,0.0002623183,0.000536843,0.0001366869],"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":[0.0001490932,0.000109514,0.001389498,0.00007001275,0.0004044324,0.000005994812,0.00005311303,0.00001652299,0.9967617,0.0003252648,0.0002656814,0.0004492153],"study_design_scores_gemma":[0.001666609,0.0009542426,0.0008865081,0.00002781135,0.0001683395,0.00001834141,0.0007781222,0.00006319841,0.9906426,0.00006364271,0.004486864,0.0002436953],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.980853,0.009831424,0.006547549,0.0001453507,0.0005254172,0.0007317847,0.001027855,0.00001292901,0.000324641],"genre_scores_gemma":[0.9977382,0.0001095152,0.001234157,0.0001574314,0.0002183253,0.00009584286,0.0001527196,0.00003522724,0.0002586178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01688511,"threshold_uncertainty_score":0.8260691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006915566103802,"score_gpt":0.2517316053704467,"score_spread":0.2416624497094087,"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."}}