{"id":"W4403030858","doi":"10.1021/acs.analchem.4c03200","title":"Steady-State Free Precession (SSFP) NMR Spectroscopy for Sensitivity Enhancement in Complex Environmental and Biological Samples Using Both High-Field and Low-Field NMR","year":2024,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Fonds de recherche du Québec – Nature et technologies; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Krembil Foundation; Canada Foundation for Innovation; Government of Ontario; Centre for Environmental Research in the Anthropocene, University of Toronto Scarborough","keywords":"Chemistry; Steady-state free precession imaging; Field (mathematics); Nuclear magnetic resonance spectroscopy; Spectroscopy; Nuclear magnetic resonance; Analytical Chemistry (journal); Sensitivity (control systems); Environmental chemistry; Stereochemistry; Physics; Quantum mechanics","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":[0.0001061384,0.0001620196,0.0002098345,0.00001682527,0.00009402475,0.00007491058,0.00006430074,0.00006443975,0.0004191544],"category_scores_gemma":[0.00001030695,0.0001421006,0.00005120412,0.0000538238,0.00008767157,0.00005841684,0.000114251,0.0001966575,0.000002476075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003779665,"about_ca_system_score_gemma":0.00002034039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001304352,"about_ca_topic_score_gemma":0.000006024125,"domain_scores_codex":[0.9990444,0.00001542435,0.0001978759,0.0004031058,0.00008174087,0.0002574296],"domain_scores_gemma":[0.999391,0.0003091895,0.00003354749,0.000164857,0.00000430073,0.00009706616],"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":[0.00004501504,0.0001373382,0.01122538,0.00007036787,0.00004114822,0.000003268071,0.00004042958,0.000008223163,0.9841331,0.00238701,0.0003176871,0.001590988],"study_design_scores_gemma":[0.0005400461,0.0001052105,0.003778523,0.0001152862,0.00005684031,0.000003227215,0.0001979182,0.03468616,0.9437571,0.01585525,0.0005992634,0.0003052494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9578969,0.00008998792,0.04062947,0.0004715511,0.00001049599,0.0001619583,0.0001487447,0.0000170424,0.0005738239],"genre_scores_gemma":[0.9972283,0.00003523381,0.002303749,0.00007039205,0.0001532297,0.00002185872,0.00008545133,0.00001004368,0.00009178832],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04037611,"threshold_uncertainty_score":0.5794696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02111687985816756,"score_gpt":0.3289631050923945,"score_spread":0.3078462252342269,"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."}}