{"id":"W2004252276","doi":"10.1021/ja003447g","title":"Measurement of Slow (μs−ms) Time Scale Dynamics in Protein Side Chains by <sup>15</sup>N Relaxation Dispersion NMR Spectroscopy:  Application to Asn and Gln Residues in a Cavity Mutant of T4 Lysozyme","year":2001,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":306,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences","keywords":"Chemistry; Side chain; Dispersion (optics); Nuclear magnetic resonance spectroscopy; Relaxation (psychology); Dynamics (music); Mutant; Transverse relaxation-optimized spectroscopy; Spectroscopy; Protein dynamics; Molecular dynamics; Nuclear magnetic resonance; Analytical Chemistry (journal); Crystallography; Stereochemistry; Fluorine-19 NMR; Computational chemistry; Chromatography; Organic chemistry; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002158587,0.0002233386,0.0001465189,0.0001366922,0.000167137,0.0001399636,0.0002733847,0.0003508586,0.0004672608],"category_scores_gemma":[0.0004140354,0.0001057251,0.00007853893,0.000107976,0.0003367689,0.0002302405,0.0002507118,0.0004100061,0.0001232925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002489409,"about_ca_system_score_gemma":0.0001327597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004932802,"about_ca_topic_score_gemma":0.0005680954,"domain_scores_codex":[0.9999354,0.000009796969,0.000003140912,0.00001935337,0.00002510266,0.000007255238],"domain_scores_gemma":[0.9997568,0.00008580314,0.00005623325,0.00002734684,0.00003756768,0.00003635913],"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":[0.00003809646,0.000005600747,0.0002337907,0.00001058294,0.000001271312,0.0000150586,0.00001233658,0.00006818555,0.9973171,0.00003857807,0.00001235809,0.002247079],"study_design_scores_gemma":[0.00001864625,0.0002579891,0.003749076,0.000003419502,0.000005510559,0.000285992,0.00002430044,0.003980014,0.9907035,0.0001364666,0.0008245333,0.00001056709],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809504,0.0003555761,0.01796678,0.00005768744,0.00001161079,0.0000191134,0.00006714803,0.0001539814,0.0004178055],"genre_scores_gemma":[0.9725233,0.0003455597,0.02622991,0.00002394685,0.000007889628,0.00005144542,0.00008395579,0.00002308311,0.0007108725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004932802,"threshold_uncertainty_score":0.0018062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005158815261684976,"score_gpt":0.2436655438127285,"score_spread":0.2385067285510435,"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."}}