{"id":"W2171283513","doi":"10.1186/1471-2105-8-342","title":"A replica exchange Monte Carlo algorithm for protein folding in the HP model","year":2007,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; Mitacs; Michael Smith Health Research BC","keywords":"Protein structure prediction; Replica; Lattice protein; Protein folding; Ab initio; Monte Carlo method; Algorithm; Computer science; Statistical potential; Protein design; Ground state; Protein structure; Statistical physics; Physics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007123401,0.0001533509,0.0001265895,0.00005486027,0.00008467209,0.00003541932,0.0002903018,0.0001865707,7.183652e-7],"category_scores_gemma":[0.00008106795,0.000112258,0.00009705406,0.0001069251,0.00003884735,0.00001047159,0.00008406879,0.00009951762,0.000001413241],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002069267,"about_ca_system_score_gemma":0.00006415741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001373757,"about_ca_topic_score_gemma":0.0001901001,"domain_scores_codex":[0.9990063,0.00001316031,0.0003470234,0.0001491184,0.0001442134,0.0003402181],"domain_scores_gemma":[0.9993145,0.00001595046,0.0001195593,0.0004457009,0.00005725258,0.00004705243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008328174,0.000342787,0.000940188,0.001991452,0.0001867181,0.00001532775,0.009847897,0.01709675,0.05706165,0.006460208,0.008498117,0.8967261],"study_design_scores_gemma":[0.0007360906,0.0001908287,0.0000783874,0.00002309056,0.00001231457,0.00001920862,0.00053077,0.9841906,0.006885674,0.0006506596,0.006454814,0.0002275326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04648437,0.0002708047,0.9506157,0.00004535154,0.00004603436,0.001209623,0.00005623847,0.00001487773,0.001256992],"genre_scores_gemma":[0.1446876,0.00003462501,0.8534911,0.0007947134,0.0002275331,0.0002345782,0.00009243,0.00002645086,0.000410974],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9670939,"threshold_uncertainty_score":0.4577747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665344085801572,"score_gpt":0.2644799402148487,"score_spread":0.247826499356833,"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."}}