{"id":"W2591676680","doi":"10.1177/1178623x17694346","title":"Diagnostic Applications of Nuclear Magnetic Resonance–Based Urinary Metabolomics","year":2017,"lang":"en","type":"review","venue":"Magnetic Resonance Insights","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 Winnipeg","funders":"","keywords":"Metabolomics; Urinary system; Magnetic resonance imaging; Nuclear magnetic resonance; Medicine; Physics; Chemistry; Radiology; Internal medicine; Chromatography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002419071,0.0008329477,0.002220908,0.0003049866,0.0003644026,0.00007967059,0.001472255,0.0006463444,0.0001273686],"category_scores_gemma":[0.0005115794,0.000720344,0.0007863938,0.000355227,0.0006195916,0.000008321969,0.0005635639,0.0004055939,0.00008033847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003977888,"about_ca_system_score_gemma":0.0003858421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002480417,"about_ca_topic_score_gemma":0.00002092492,"domain_scores_codex":[0.9964344,0.0002245138,0.001132504,0.001228302,0.0003866067,0.0005937081],"domain_scores_gemma":[0.9960763,0.0002254211,0.0008132575,0.002496834,0.0002159712,0.0001722194],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003235361,0.0002781661,0.00001999212,0.002324039,0.00005359768,0.00002614766,0.00001637918,5.62673e-7,0.000095717,0.001245998,0.00248436,0.9934227],"study_design_scores_gemma":[0.0005138976,0.0008318876,0.0003708934,0.001325134,0.0006681913,0.00002907443,0.000007382331,0.0000109261,0.00005945934,0.0002237505,0.9952438,0.0007155671],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001647667,0.9929336,0.00004475686,0.00002812131,0.0003110442,0.001739455,0.000299257,0.00002777457,0.004451244],"genre_scores_gemma":[0.00030506,0.9931773,0.001908563,0.00008159457,0.0005246572,0.000878274,0.000234563,0.000154601,0.002735405],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9927595,"threshold_uncertainty_score":0.9995248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03019351987567496,"score_gpt":0.297250377358958,"score_spread":0.267056857483283,"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."}}