{"id":"W2006225823","doi":"10.1021/ja906842s","title":"Selective Characterization of Microsecond Motions in Proteins by NMR Relaxation","year":2009,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Microsecond; Millisecond; Chemistry; Chemical physics; Nanosecond; Protein dynamics; Relaxation (psychology); Biological system; Amplitude; Characterization (materials science); Molecular dynamics; Nuclear magnetic resonance; Computational chemistry; Nanotechnology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003148828,0.0002388542,0.0001428007,0.0002725613,0.0001972576,0.0002119805,0.0002716343,0.0003215987,0.00069258],"category_scores_gemma":[0.0005493914,0.0001158698,0.00007859378,0.000216347,0.0003635367,0.0003206866,0.00024517,0.0006291383,0.0002553188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001631436,"about_ca_system_score_gemma":0.0001785464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005441282,"about_ca_topic_score_gemma":0.0009129242,"domain_scores_codex":[0.9999008,0.00001626596,0.00000332621,0.00003412889,0.00003056658,0.00001490476],"domain_scores_gemma":[0.9997792,0.00008270779,0.00007260628,0.00002361102,0.00002428833,0.00001767915],"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":[0.00002623622,0.00001081393,0.0005197634,0.00004662723,0.000004431663,0.00001797881,0.00003430425,0.0001529538,0.993879,0.0003088446,0.00006588537,0.004933175],"study_design_scores_gemma":[0.000008867409,0.0001587267,0.01113227,0.00001080354,0.00001680086,0.000221266,0.00006392333,0.005120164,0.9792755,0.0003690618,0.003606023,0.00001654678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8665549,0.003847414,0.1236908,0.0002377681,0.00004805496,0.00005720568,0.0004450025,0.0004288675,0.004689845],"genre_scores_gemma":[0.954889,0.002407444,0.03989502,0.0001109641,0.00004063595,0.0001102022,0.0003250528,0.0000526628,0.002169084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00069258,"threshold_uncertainty_score":0.002316892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002750975171652512,"score_gpt":0.2189367985258948,"score_spread":0.2161858233542423,"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."}}