{"id":"W2193923663","doi":"10.1038/bjc.2015.414","title":"1H-NMR urinary metabolomic profiling for diagnosis of gastric cancer","year":2015,"lang":"en","type":"article","venue":"British Journal of Cancer","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":110,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Alexandra Hospital; University of Alberta; University of Alberta Hospital","funders":"Alberta Innovates; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale; University of Alberta; Alberta Innovates - Health Solutions; Government of Canada","keywords":"Metabolomics; Receiver operating characteristic; Metabolite; Biomarker; Urine; Logistic regression; Medicine; Urinary system; Area under the curve; Internal medicine; Chromatography; 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":[0.001080627,0.000433904,0.0005075887,0.0009289414,0.0002062088,0.0004388916,0.0001846997,0.0004682281,0.0007598331],"category_scores_gemma":[0.002039509,0.000145975,0.0002803793,0.0006319122,0.0002970477,0.0002101566,0.0003598046,0.0003882718,0.0001833725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002722498,"about_ca_system_score_gemma":0.0002716051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005696589,"about_ca_topic_score_gemma":0.001239368,"domain_scores_codex":[0.9996711,0.0001570013,0.00002058013,0.00005269232,0.00006979626,0.00002873212],"domain_scores_gemma":[0.9991922,0.0003296867,0.0002632108,0.00004324511,0.00009057215,0.00008110446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003106454,0.0002785011,0.7896539,0.0003781388,0.0002516121,0.0005115276,0.0001617334,0.002539732,0.1213842,0.0002030769,0.000926926,0.08060423],"study_design_scores_gemma":[0.00009874558,0.00197538,0.8925977,0.0001230662,0.0004214644,0.003499765,0.000359975,0.03225583,0.0623492,0.001410526,0.004840294,0.00006802463],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9856732,0.006254615,0.005853153,0.0005117417,0.00002760525,0.00004092951,0.0004684068,0.00007542224,0.001094849],"genre_scores_gemma":[0.9916508,0.001073085,0.006702895,0.00009958309,0.00003620559,0.00001848259,0.0002419679,0.000008716065,0.0001683478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001080627,"threshold_uncertainty_score":0.005715013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492082351949974,"score_gpt":0.3039605933262345,"score_spread":0.2790397698067348,"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."}}