{"id":"W2027147643","doi":"10.1021/ct400312d","title":"Sampling of Protein Folding Transitions: Multicanonical Versus Replica Exchange Molecular Dynamics","year":2013,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Institut national de la recherche scientifique; National Institutes of Health; Hacettepe Üniversitesi; National Institute for Health and Care Research; University of Oklahoma","keywords":"Replica; Molecular dynamics; Limiting; Force field (fiction); Protein folding; Chemical physics; Folding (DSP implementation); Sampling (signal processing); Statistical physics; Umbrella sampling; Chemistry; Computer science; Computational chemistry; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001597501,0.0004051391,0.0006829654,0.0004204924,0.0004047563,0.0005346664,0.0008915077,0.000752754,0.0005757611],"category_scores_gemma":[0.005247402,0.0002309524,0.0003335054,0.0004055701,0.0006176023,0.0009128398,0.000562426,0.0006769316,0.0000705344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007477743,"about_ca_system_score_gemma":0.000640878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003790665,"about_ca_topic_score_gemma":0.00316959,"domain_scores_codex":[0.9996222,0.0001500971,0.00001822184,0.00004932384,0.0001147649,0.0000452991],"domain_scores_gemma":[0.9981426,0.00105445,0.0001633715,0.000342328,0.0001524757,0.0001447866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001436806,0.0003145057,0.005645909,0.0001263919,0.0001204126,0.0001391317,0.0002792303,0.9241163,0.02442122,0.01696534,0.0002594517,0.02617529],"study_design_scores_gemma":[0.00004805719,0.00006832982,0.000238391,0.000003087667,0.000005943211,0.00001093136,0.00000722282,0.9961132,0.002782284,0.0006320328,0.00008444135,0.000006087116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9625603,0.0003968836,0.03462484,0.0002190805,0.00003281899,0.00003961989,0.00005523086,0.0002578562,0.001813333],"genre_scores_gemma":[0.9800903,0.0001241972,0.01941554,0.00002915044,0.000008325355,0.0000387596,0.00004514238,0.00003899109,0.0002097763],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003790665,"threshold_uncertainty_score":0.008448482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01015757260161737,"score_gpt":0.2722489808181577,"score_spread":0.2620914082165404,"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."}}