{"id":"W3126607732","doi":"10.1016/j.bpj.2020.12.034","title":"Volume and compressibility differences between protein conformations revealed by high-pressure NMR","year":2021,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Photoreceptor and optogenetics research","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Division of Molecular and Cellular Biosciences; Fonds de recherche du Québec – Nature et technologies; City University of New York; National Science Foundation","keywords":"Conformational isomerism; Compressibility; Chemistry; Population; Volume (thermodynamics); High pressure; Chemical physics; Crystallography; Thermodynamics; Molecule; Physics; Organic chemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001328852,0.0001231774,0.0002313395,0.00003270924,0.0003677912,0.0003117567,0.000281125,0.00006815963,0.0002648682],"category_scores_gemma":[0.0003146004,0.00009732972,0.00006421572,0.0001835727,0.0002664303,0.0002008262,0.0001688361,0.0004672111,0.00003527344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001762882,"about_ca_system_score_gemma":0.00008220745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000131337,"about_ca_topic_score_gemma":7.60422e-7,"domain_scores_codex":[0.9983534,0.0003099927,0.0002647214,0.0002599839,0.0005144766,0.0002974802],"domain_scores_gemma":[0.9991412,0.0001502917,0.00009409941,0.0001895957,0.000120106,0.0003047468],"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":[0.00001487088,0.00009350926,0.006013686,0.00002059661,0.00001064236,0.000007948913,0.00006249252,9.330101e-7,0.9915622,0.0002033139,0.0008435748,0.001166155],"study_design_scores_gemma":[0.0005128219,0.0001208865,0.08483253,0.00003323397,0.00001899643,0.00002150457,0.00002781156,0.001086128,0.9093617,0.001358218,0.002456057,0.0001701742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981419,0.0000531094,0.000452481,0.0005884396,0.00006552938,0.0001584371,0.0002280519,0.00001914619,0.0002929383],"genre_scores_gemma":[0.9986263,0.00004464514,0.0001408438,0.0000663704,0.0002180195,0.000009244754,0.000007165877,0.000007870074,0.0008795539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08220064,"threshold_uncertainty_score":0.3968991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03850658998705288,"score_gpt":0.2983275144630064,"score_spread":0.2598209244759536,"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."}}