{"id":"W4412492594","doi":"10.1093/nargab/lqaf099","title":"Modeling RNA duplex dynamics with Gibbs sampling enhances base-pair prediction accuracy and reveals structural activity profiles","year":2025,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Research in Immunology and Cancer","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Google","keywords":"RNA; Base pair; Duplex (building); Nucleic acid secondary structure; Nucleic acid structure; Biological system; Statistical physics; Algorithm; Computational biology; Computer science; Physics; Biology; Genetics; DNA","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":[0.0002322006,0.0001890902,0.0001831682,0.00005956993,0.000246774,0.0001081797,0.0001025075,0.0001636712,0.000002020133],"category_scores_gemma":[0.00005562122,0.0001507386,0.00003465532,0.00006498052,0.00005886053,0.00002813679,0.0001115294,0.0000954202,4.574124e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002760017,"about_ca_system_score_gemma":0.00008678288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001786208,"about_ca_topic_score_gemma":0.00002261838,"domain_scores_codex":[0.9992129,0.00002304391,0.0002586404,0.0002089282,0.00009177162,0.0002046888],"domain_scores_gemma":[0.9995142,0.000026184,0.0001208168,0.0002077459,0.00006912417,0.00006196529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000337152,0.00001954086,0.001103991,0.0004935352,0.0001534736,6.792883e-7,0.0003077891,0.002624362,0.8642547,0.0007531387,0.00003897495,0.1299127],"study_design_scores_gemma":[0.0005152009,0.0002700121,0.0004554108,0.000117175,0.0000594348,0.00002175807,0.0006501004,0.7684335,0.2281633,0.0006440856,0.0003688834,0.0003010519],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8907549,0.0003893873,0.1080516,0.0001194523,0.0000762624,0.0003271126,0.0001021279,0.00001741139,0.0001616753],"genre_scores_gemma":[0.9563514,0.0007798373,0.04248518,0.0001016323,0.00006398073,0.00001682118,0.00009360646,0.00001241659,0.00009509536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7658092,"threshold_uncertainty_score":0.6146943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01157170296863191,"score_gpt":0.2411867423526377,"score_spread":0.2296150393840058,"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."}}