{"id":"W2508426564","doi":"10.1002/anie.201605843","title":"Enhancing the Sensitivity of CPMG Relaxation Dispersion to Conformational Exchange Processes by Multiple‐Quantum Spectroscopy","year":2016,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Dispersion (optics); Relaxation (psychology); Conformational isomerism; Chemistry; Protonation; Spectroscopy; Quantum chemical; Nuclear magnetic resonance spectroscopy; Sensitivity (control systems); Deuterium; Quantum; Chemical physics; Nuclear magnetic resonance; Molecular physics; Analytical Chemistry (journal); Atomic physics; Molecule; Physics; Stereochemistry; Optics; Quantum mechanics; Organic chemistry; Ion","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":[0.002057999,0.0005625584,0.0005573034,0.0005117811,0.00043932,0.0006016796,0.001052251,0.00146302,0.001435105],"category_scores_gemma":[0.003321433,0.0003367104,0.0001690567,0.0005587376,0.001257644,0.0007823655,0.0009434876,0.002067686,0.0003661371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007131704,"about_ca_system_score_gemma":0.0004594447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009449557,"about_ca_topic_score_gemma":0.0009489006,"domain_scores_codex":[0.9991359,0.0002047512,0.00002252518,0.0002169988,0.0003096204,0.0001101816],"domain_scores_gemma":[0.9984393,0.001005007,0.0001588257,0.0001808272,0.0001400461,0.00007610676],"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":[0.0000628229,0.00002890122,0.00009568191,0.00004856921,0.000004472568,0.00004564657,0.00004930283,0.0006484912,0.9859539,0.0009619042,0.0001055088,0.01199485],"study_design_scores_gemma":[0.00001730837,0.0001418344,0.0003842696,0.000008684642,0.000005142218,0.0001353326,0.00001151157,0.01498189,0.9818853,0.0007096294,0.001698442,0.00002066919],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.518896,0.001665195,0.4717988,0.0008460038,0.0001690507,0.0002155086,0.0002240932,0.001515561,0.004669776],"genre_scores_gemma":[0.7910849,0.001187679,0.2046397,0.0002151002,0.00006032069,0.0002225955,0.0002262694,0.0001793104,0.002184131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002057999,"threshold_uncertainty_score":0.01088387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005623167898812389,"score_gpt":0.2353027248756191,"score_spread":0.2296795569768067,"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."}}