{"id":"W1972660398","doi":"10.1073/pnas.1305688110","title":"NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers","year":2013,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":253,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Conformational isomerism; Folding (DSP implementation); Conformational ensembles; Nuclear magnetic resonance spectroscopy; Function (biology); Protein folding; Chemistry; Biomolecular structure; Biomolecule; Molecular recognition; Chemical physics; Nanotechnology; Molecular dynamics; Protein structure; Computational biology; Computational chemistry; Materials science; Biology; Molecule; Stereochemistry; Evolutionary biology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006788087,0.000515985,0.0005818412,0.0006416716,0.0004373123,0.0008771456,0.0009866026,0.001084042,0.001278675],"category_scores_gemma":[0.0008551409,0.0004077472,0.0003631564,0.000428396,0.001788336,0.003400097,0.0007581912,0.002318358,0.0003580417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004230407,"about_ca_system_score_gemma":0.0003820321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006750626,"about_ca_topic_score_gemma":0.000721895,"domain_scores_codex":[0.9998457,0.00004620544,0.00001189642,0.00003688575,0.00004227379,0.00001686644],"domain_scores_gemma":[0.9994307,0.0002439009,0.0000593132,0.0001904768,0.00004351008,0.00003211091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00007502455,0.00008066341,0.001185287,0.0003165467,0.00005811064,0.0003702262,0.0006432119,0.1146784,0.4181931,0.4140131,0.001431388,0.04895502],"study_design_scores_gemma":[0.00003531338,0.0001746279,0.00165604,0.00004900693,0.00003980281,0.0004518927,0.0002788579,0.5119637,0.04589414,0.4068968,0.03244694,0.0001129802],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05188047,0.003532679,0.9375628,0.001047673,0.00009485311,0.0000248239,0.0001805249,0.0006636402,0.005012595],"genre_scores_gemma":[0.5735785,0.008162598,0.4122948,0.0004185222,0.0003223563,0.0001325836,0.0003424811,0.0001920669,0.004556193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001278675,"threshold_uncertainty_score":0.004277587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05575566223953361,"score_gpt":0.284803687391152,"score_spread":0.2290480251516184,"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."}}