{"id":"W2004405255","doi":"10.1021/ja054842f","title":"A Simple Method To Predict Protein Flexibility Using Secondary Chemical Shifts","year":2005,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":447,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Chemical shift; Protein dynamics; Allosteric regulation; Nuclear magnetic resonance spectroscopy; Biological system; Protein structure; Molecular dynamics; Computational chemistry; Chemical physics; Stereochemistry; Physical chemistry; Enzyme; Biochemistry","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":[0.0004529831,0.0001798655,0.0003233507,0.00001055003,0.00006542098,0.0000216706,0.0005442108,0.0001214058,0.00001431551],"category_scores_gemma":[0.0001910789,0.0001249521,0.0005767582,0.0002077587,0.0002284768,0.000008795285,0.0003547079,0.0004390565,8.128962e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001376866,"about_ca_system_score_gemma":0.0002252598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001945849,"about_ca_topic_score_gemma":0.000001226925,"domain_scores_codex":[0.9986595,0.00008808277,0.0004143388,0.0002552906,0.0002887602,0.0002940551],"domain_scores_gemma":[0.9988482,0.00002229668,0.0004337201,0.0003719929,0.0001309588,0.0001928205],"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":[0.0001590905,0.00004727706,0.0003401535,0.0000104492,0.00009274579,4.754749e-7,0.00007208877,0.0002136102,0.9886104,0.000005395758,0.001791663,0.008656647],"study_design_scores_gemma":[0.0003727325,0.0001162601,0.0003737948,0.00001625557,0.00004175944,0.00006541639,0.00007640836,0.0008120327,0.9852176,0.0005095646,0.01222805,0.0001701081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726825,0.0001124644,0.0261857,0.0007046527,0.00003559004,0.0001899067,0.00002246206,0.000006842667,0.00005989171],"genre_scores_gemma":[0.8342362,0.00000370884,0.1620429,0.002851797,0.0008184263,0.000004021731,0.000003352688,0.00001975573,0.00001986398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1384463,"threshold_uncertainty_score":0.5095401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006684643769196,"score_gpt":0.2975700798458689,"score_spread":0.287503233408177,"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."}}