{"id":"W2970146138","doi":"10.1007/978-1-4939-9690-2_13","title":"NMR-Based Urinary Metabolomics Applications","year":2019,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Metabolomics; Standardization; Data science; Computer science; Field (mathematics); Biochemical engineering; Engineering; Bioinformatics; Biology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007937427,0.0008897507,0.0006886855,0.001110492,0.0003378708,0.0009356777,0.0006431858,0.001251535,0.00407691],"category_scores_gemma":[0.001521108,0.0003749061,0.0005053373,0.001510535,0.0002889071,0.0006035989,0.001073972,0.0006493073,0.001490408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002642724,"about_ca_system_score_gemma":0.0004829855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303769,"about_ca_topic_score_gemma":0.001864824,"domain_scores_codex":[0.9994985,0.0001498777,0.00002238147,0.0001191651,0.0001629662,0.00004706416],"domain_scores_gemma":[0.999424,0.0001799926,0.00005952893,0.0000751328,0.000211532,0.00004990182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007508179,0.000151984,0.004390321,0.001102919,0.0001555597,0.0003565822,0.00008673062,0.001798286,0.8425066,0.00160033,0.00387567,0.1432241],"study_design_scores_gemma":[0.000116138,0.000632857,0.01285921,0.0001988754,0.0003406696,0.003043359,0.0002201274,0.03274161,0.9031016,0.00439583,0.04216409,0.0001855927],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2244912,0.03656736,0.6806442,0.004072716,0.00143905,0.0005686829,0.009578588,0.006485464,0.03615284],"genre_scores_gemma":[0.6744295,0.01972921,0.2869588,0.002242464,0.001029872,0.0003960014,0.002296467,0.0005524224,0.01236528],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00407691,"threshold_uncertainty_score":0.01363856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01345822003684047,"score_gpt":0.35722530686262,"score_spread":0.3437670868257795,"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."}}