{"id":"W4387440647","doi":"10.1002/mrc.5401","title":"Low‐field, not low quality: 1D simplification, selective detection, and heteronuclear 2D experiments for improving low‐field NMR spectroscopy of environmental and biological samples","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Chemistry","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"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; Fonds de recherche du Québec – Nature et technologies; Government of Ontario","keywords":"Chemistry; Heteronuclear molecule; Heteronuclear single quantum coherence spectroscopy; Field (mathematics); Nuclear magnetic resonance spectroscopy; Carbon-13 NMR; Spectroscopy; Environmental analysis; Biochemical engineering; Organic chemistry; Physics; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.0001044683,0.0001524887,0.0001996435,0.00002247923,0.0001162371,0.00003039853,0.0001102651,0.00008397314,0.0001307588],"category_scores_gemma":[0.00002625124,0.0001577471,0.00004266075,0.0001019984,0.0001088917,0.00004596605,0.00007108936,0.000139597,0.000003224369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002774575,"about_ca_system_score_gemma":0.00001585431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001000767,"about_ca_topic_score_gemma":0.000003394495,"domain_scores_codex":[0.9989328,0.00001756827,0.0003017745,0.0004126011,0.00008827421,0.0002469164],"domain_scores_gemma":[0.9993997,0.0002167465,0.000110697,0.0002049677,0.00001391071,0.00005401867],"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":[0.00007993607,0.0000980992,0.01571478,0.00005890745,0.0000050733,1.806822e-7,0.0001710632,0.000001675844,0.9609939,0.00009775373,0.00003519308,0.02274343],"study_design_scores_gemma":[0.0005256812,0.0001418442,0.04101264,0.0000225276,0.00000578146,6.56426e-7,0.0005665963,0.0003451913,0.9556217,0.001286992,0.0003138345,0.0001565748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978431,0.000249944,0.001177309,0.0001243171,0.00001517952,0.000306571,0.0001009411,0.00002270523,0.0001599062],"genre_scores_gemma":[0.9986793,0.0000747321,0.0007355426,0.00004435909,0.00009546639,0.0002406641,0.00002446539,0.00001419895,0.00009131414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02529786,"threshold_uncertainty_score":0.6432739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545954532201303,"score_gpt":0.307738529240293,"score_spread":0.2922789839182799,"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."}}