{"id":"W3104869804","doi":"10.1002/edm2.201","title":"Metabolic dysfunction in pregnancy: Fingerprinting the maternal metabolome using proton nuclear magnetic resonance spectroscopy","year":2020,"lang":"en","type":"article","venue":"Endocrinology Diabetes & Metabolism","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta; University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates","keywords":"Gestational diabetes; Metabolomics; Medicine; Metabolome; Pregnancy; Diabetes mellitus; Metabolic syndrome; Internal medicine; Bioinformatics; Endocrinology; Biology; Gestation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002536076,0.0004721799,0.0007521973,0.0001619013,0.0002677143,0.00007752719,0.0006310109,0.0001637237,0.0001418326],"category_scores_gemma":[0.0003219672,0.0003815361,0.0002206708,0.0005208915,0.0002777977,0.0000251929,0.0005861508,0.0004998836,0.00004987586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000173896,"about_ca_system_score_gemma":0.00004986583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004684933,"about_ca_topic_score_gemma":0.00001249389,"domain_scores_codex":[0.996757,0.0003360517,0.0006009387,0.0009203942,0.0002498508,0.001135747],"domain_scores_gemma":[0.9989347,0.00003442182,0.0002453289,0.0005769049,0.0000826883,0.0001259722],"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":[0.0001009027,0.00006472437,0.06147022,0.00004386179,0.0001432184,0.00001348029,0.0002071955,0.00005971284,0.9261264,0.003846006,0.0001366225,0.007787608],"study_design_scores_gemma":[0.001760393,0.0002181953,0.1695011,0.0000374613,0.0002161328,0.00001862156,0.0001278808,0.0007241776,0.5626457,0.0004421713,0.2637487,0.0005594215],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.883586,0.11333,0.0000952542,0.001078476,0.0005623145,0.0007982885,0.00002222749,0.00005093936,0.0004764169],"genre_scores_gemma":[0.9865391,0.007135666,0.003639261,0.001414452,0.0008155831,0.0002212106,0.00001264081,0.00008448664,0.0001376618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3634807,"threshold_uncertainty_score":0.9998637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318078509224522,"score_gpt":0.2343772250862156,"score_spread":0.2211964399939704,"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."}}