{"id":"W4391321732","doi":"10.1002/mrc.5431","title":"Slice through the water—Exploring the fundamental challenge of water suppression for benchtop NMR systems","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Chemistry","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":7,"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; Government of Ontario","keywords":"Chemistry; Analyte; Nuclear magnetic resonance spectroscopy; Two-dimensional nuclear magnetic resonance spectroscopy; Proton NMR; Analytical Chemistry (journal); Solvent; Dispersion (optics); NMR spectra database; Biological system; Spectral line; Chromatography; Physics; Organic chemistry; Optics","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":[0.0001213093,0.0001195599,0.0001185183,0.000005752372,0.0001200172,0.00006854496,0.0002796054,0.00002790867,0.0003194228],"category_scores_gemma":[0.000001228593,0.00005089858,0.00007117829,0.00005518191,0.00008258237,0.00007216797,0.00007873152,0.0001696453,0.00001349506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002058295,"about_ca_system_score_gemma":0.00001326396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001716221,"about_ca_topic_score_gemma":0.000001236546,"domain_scores_codex":[0.9991517,0.00001305732,0.0002288431,0.0002261888,0.0001213355,0.0002588941],"domain_scores_gemma":[0.9995393,0.00008978419,0.00002065513,0.0003166941,0.00001688286,0.00001667215],"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":[0.00005353515,0.000251841,0.0008022471,0.0009902542,0.00003940594,0.000002823717,0.01222509,0.0003487269,0.9335849,0.01716584,0.003741518,0.03079377],"study_design_scores_gemma":[0.0001698627,0.00002254926,0.00006695738,0.0001885963,0.00001540181,0.000001055391,0.00135406,0.001256715,0.6730643,0.004451444,0.3193078,0.0001012314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681928,0.006980938,0.0003801254,0.003946043,0.0002876597,0.0007267828,0.0001109611,0.00003334383,0.0193414],"genre_scores_gemma":[0.9946687,0.00005833766,0.00004652327,0.00000819461,0.0003871201,0.001118754,0.00003985398,0.00001538297,0.003657185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3155663,"threshold_uncertainty_score":0.3497455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02316395778356742,"score_gpt":0.3005176322117684,"score_spread":0.2773536744282009,"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."}}