{"id":"W3043435966","doi":"10.1093/bioinformatics/btaa469","title":"Finding the direct optimal RNA barrier energy and improving pathways with an arbitrary energy model","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Institute of Genetics; Artificial Intelligence Research Center; National Institute of Advanced Industrial Science and Technology","keywords":"Heuristics; Computer science; Source code; Hamming distance; Code (set theory); Folding (DSP implementation); Energy (signal processing); RNA; Theoretical computer science; Algorithm; Chemistry; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001141394,0.0001751993,0.0001325857,0.00001880597,0.0001723036,0.00008003612,0.0002055392,0.0001145263,0.000005356411],"category_scores_gemma":[0.00002995703,0.0001144193,0.00004305367,0.00005398889,0.00005746581,0.00002390568,0.0001168893,0.0000505918,7.799058e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004852371,"about_ca_system_score_gemma":0.0000870021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001215238,"about_ca_topic_score_gemma":0.000007623641,"domain_scores_codex":[0.9992423,0.00002975501,0.0001977072,0.0001726289,0.0001356376,0.0002219424],"domain_scores_gemma":[0.9994435,0.00001250822,0.0001038705,0.0002535422,0.00002843225,0.0001580966],"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":[0.0003112732,0.00002788464,0.00002720011,0.00008768599,0.0001090163,0.000006997077,0.001667502,0.002450549,0.8786367,0.005403687,0.0004395119,0.110832],"study_design_scores_gemma":[0.0002478859,0.0005089105,0.000003109945,0.00001151885,0.00002410638,0.00001468933,0.0004158722,0.3696821,0.6240785,0.0001209314,0.004644219,0.0002481621],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4713139,0.001007503,0.5147833,0.0003613975,0.00008220471,0.0002396565,0.0001020905,0.00008530439,0.01202463],"genre_scores_gemma":[0.9489147,0.0001651262,0.04838731,0.002155143,0.0001547542,0.0000250603,0.00004976979,0.00002861084,0.0001194973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4776008,"threshold_uncertainty_score":0.4665884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01524650807310749,"score_gpt":0.1968845897067588,"score_spread":0.1816380816336513,"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."}}