{"id":"W2123356980","doi":"10.1002/pro.2606","title":"Protein unfolding rates correlate as strongly as folding rates with native structure","year":2014,"lang":"en","type":"article","venue":"Protein Science","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Protein folding; Topology (electrical circuits); Native state; Contact order; Folding (DSP implementation); Protein engineering; Chemistry; Denaturation (fissile materials); Protein stability; Stability (learning theory); Chemical physics; Crystallography; Biophysics; Biology; Computer science; Mathematics; Biochemistry; Enzyme","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005585757,0.0003360313,0.0002300574,0.0001211417,0.000527884,0.0002275168,0.0007410931,0.0001673418,0.0000352732],"category_scores_gemma":[0.0006399484,0.0002560189,0.00005453117,0.0005721547,0.000742922,0.00005416582,0.0002883818,0.0002664446,0.00001587739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005032414,"about_ca_system_score_gemma":0.0004516009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008123758,"about_ca_topic_score_gemma":0.00004236538,"domain_scores_codex":[0.9976138,0.00008704349,0.0002457988,0.0008698761,0.0005466482,0.0006368551],"domain_scores_gemma":[0.9986898,0.0000163299,0.0002318138,0.0005361014,0.0003230748,0.0002028595],"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":[0.0001391785,0.00001130307,0.0005537302,0.0000216922,0.00001895726,0.000004465544,0.00009853584,0.0004066623,0.9856576,0.01026245,0.00000676438,0.002818597],"study_design_scores_gemma":[0.0005621354,0.00100669,0.0003909977,0.0001098826,0.00001154613,0.00005200301,0.00012862,0.001641614,0.9867743,0.007581888,0.001307148,0.0004332009],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869843,0.0002113552,0.00855391,0.0001433496,0.00009953226,0.00114877,0.0000102448,0.00004190268,0.002806655],"genre_scores_gemma":[0.9900163,0.000003921018,0.008692649,0.0001344185,0.0001499442,0.0001101805,0.00001886568,0.00003282047,0.0008409185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003032001,"threshold_uncertainty_score":0.9999892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004615517132194791,"score_gpt":0.2525782823053929,"score_spread":0.2479627651731981,"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."}}