{"id":"W4385514138","doi":"10.1021/acs.analchem.3c01362","title":"Application of <sup>15</sup>N-Edited <sup>1</sup>H–<sup>13</sup>C Correlation NMR Spectroscopy─Toward Fragment-Based Metabolite Identification and Screening via HCN Constructs","year":2023,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; The Scarborough Hospital; University of Toronto","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Krembil Foundation; Canada Foundation for Innovation; Government of Ontario","keywords":"Heteronuclear single quantum coherence spectroscopy; Chemistry; Heteronuclear molecule; Metabolite; Two-dimensional nuclear magnetic resonance spectroscopy; Metabolomics; Nuclear magnetic resonance spectroscopy; Chemical shift; Carbon-13 NMR; NMR spectra database; Nuclear magnetic resonance; Stereochemistry; Spectral line; Chromatography; Biochemistry; Physical 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":[0.00040483,0.0004552903,0.0002200148,0.0001266577,0.00018417,0.0002409551,0.0003435146,0.0003832936,0.0007019747],"category_scores_gemma":[0.0002445443,0.0001654055,0.0001924193,0.0001606812,0.0003872115,0.0002213269,0.0002917253,0.0006543857,0.0002794426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003337477,"about_ca_system_score_gemma":0.0003653245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054409,"about_ca_topic_score_gemma":0.002446561,"domain_scores_codex":[0.9998217,0.00001914942,0.000008943041,0.00005942424,0.00006484066,0.00002599526],"domain_scores_gemma":[0.9997885,0.00004699285,0.00007091906,0.00002531764,0.00003991527,0.00002843554],"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":[0.00003262987,0.000008499712,0.00006288887,0.00002232269,0.000002852357,0.00003002538,0.000009916201,0.0001422426,0.9983894,0.00009462552,0.00003562155,0.001168999],"study_design_scores_gemma":[0.000004014465,0.0001036431,0.0006204939,0.000003408228,0.000007325438,0.00006201171,0.000008682233,0.0015712,0.9954227,0.00004163555,0.002148299,0.000006636425],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8536195,0.0009947007,0.1384855,0.0002905661,0.0001143588,0.0002359393,0.001199705,0.0007683007,0.004291439],"genre_scores_gemma":[0.8154237,0.001646835,0.1748191,0.000368049,0.00003467689,0.0002969362,0.002620929,0.0001828258,0.004606926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001054409,"threshold_uncertainty_score":0.002421498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01016259973563507,"score_gpt":0.2527481440565248,"score_spread":0.2425855443208897,"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."}}