{"id":"W2988834127","doi":"10.1002/pro.3785","title":"Temperature dependence of NMR chemical shifts: Tracking and statistical analysis","year":2019,"lang":"en","type":"article","venue":"Protein Science","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Chemical shift; Chemistry; Isotropy; Proton; Amide; Curvature; Nuclear magnetic resonance spectroscopy; Atmospheric temperature range; Linearity; Nuclear magnetic resonance; Thermodynamics; Physical chemistry; Physics; Stereochemistry","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":[0.0003158425,0.00009505804,0.0001488619,0.00006853116,0.00004805998,0.00004143813,0.0002817425,0.00008975269,0.00001960674],"category_scores_gemma":[0.0002062854,0.00007937424,0.00003697964,0.0004583705,0.0003910566,0.00001226042,0.0001589096,0.00009438594,0.000001741201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008295899,"about_ca_system_score_gemma":0.0001060867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001462957,"about_ca_topic_score_gemma":0.000007236205,"domain_scores_codex":[0.9989383,0.00001858379,0.0001499925,0.0004184321,0.0002727033,0.0002019545],"domain_scores_gemma":[0.9994398,0.00000987691,0.00006491216,0.0002972895,0.0001064732,0.00008166564],"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":[0.00002182883,0.000008516618,0.008966592,0.00001769931,0.00001814163,8.692163e-7,0.00002283974,0.00002676586,0.987757,0.001584567,0.000001754086,0.001573381],"study_design_scores_gemma":[0.0001645553,0.00009761849,0.01979686,0.00001323394,0.00003090965,0.000006420606,0.00002907096,0.0008715953,0.9779305,0.000846224,0.00006457756,0.0001484429],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933772,0.0002215875,0.005810905,0.0000322354,0.00001899792,0.0002184913,0.00001934611,0.000005000705,0.0002962292],"genre_scores_gemma":[0.9882985,0.000007739416,0.01155446,0.000044406,0.00002102278,0.000008443615,0.00001165119,0.000004645131,0.00004907544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01083026,"threshold_uncertainty_score":0.3236788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004396683031408381,"score_gpt":0.2479278037685122,"score_spread":0.2435311207371038,"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."}}