{"id":"W2615415179","doi":"10.1016/j.bpj.2017.07.023","title":"Conformational Heterogeneity and FRET Data Interpretation for Dimensions of Unfolded Proteins","year":2017,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Changchun Institute of Applied Chemistry; Canadian Institutes of Health Research; National Natural Science Foundation of China; National Science Foundation","keywords":"Förster resonance energy transfer; Radius of gyration; Single-molecule FRET; Conformational ensembles; Physics; Crystallography; Intrinsically disordered proteins; Small-angle X-ray scattering; Gyration; Chemistry; Chemical physics; Protein structure; Nuclear magnetic resonance; Scattering; Mathematics","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":[0.001336839,0.0003644526,0.0003553395,0.001164204,0.0003576855,0.0008692121,0.0006857599,0.0004160727,0.0006980211],"category_scores_gemma":[0.003469935,0.0002206798,0.0003561833,0.0006306923,0.0004600754,0.001035044,0.0006109375,0.0007923247,0.0001979391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005029598,"about_ca_system_score_gemma":0.0003160148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002865354,"about_ca_topic_score_gemma":0.0002953449,"domain_scores_codex":[0.9996158,0.0001004258,0.00003494834,0.0001004813,0.0001005047,0.0000479468],"domain_scores_gemma":[0.9986433,0.0005884459,0.0001665584,0.0003414589,0.0001900295,0.00007022253],"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":[0.0006368058,0.00007672481,0.008374945,0.0001336313,0.00005403611,0.0004496266,0.0002944865,0.01262536,0.9011111,0.01614377,0.0006211092,0.05947851],"study_design_scores_gemma":[0.00001649562,0.00008619102,0.01191298,0.00002098365,0.00004775297,0.0009259306,0.0002224074,0.2801811,0.6931592,0.01076169,0.00259913,0.00006614693],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6193085,0.0003772679,0.376513,0.0002819923,0.00004111556,0.00005539213,0.0005401645,0.001133354,0.001749196],"genre_scores_gemma":[0.917878,0.0001139955,0.08089999,0.00004693102,0.00001482198,0.00007081475,0.0003499958,0.0002062412,0.0004193089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001336839,"threshold_uncertainty_score":0.007070005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02036692392715382,"score_gpt":0.3018780103127116,"score_spread":0.2815110863855578,"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."}}