{"id":"W2888062132","doi":"10.1101/gr.233999.117","title":"Exonic splice regulation imposes strong selection at synonymous sites","year":2018,"lang":"en","type":"article","venue":"Genome Research","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Medical Research Council; Medical Research Council Canada; Boehringer Ingelheim Fonds","keywords":"Biology; splice; Genetics; Negative selection; Synonymous substitution; Natural selection; Computational biology; RNA splicing; Selection (genetic algorithm); Constraint (computer-aided design); Silent mutation; Evolutionary biology; Mutation; Codon usage bias; Gene; Computer science; RNA; Genome","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":[0.0008683032,0.0001055782,0.0000926383,0.0001874546,0.0004486065,0.00004434621,0.0002339227,0.0001289452,0.0003073779],"category_scores_gemma":[0.0001461195,0.0001018071,0.00004726377,0.0003567851,0.0002231543,0.000006517344,0.0003202479,0.0001604522,0.0002974335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001136319,"about_ca_system_score_gemma":0.000118646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002016971,"about_ca_topic_score_gemma":0.0006877464,"domain_scores_codex":[0.9981294,0.0001907243,0.0001354627,0.0004201302,0.0004445213,0.0006797693],"domain_scores_gemma":[0.9990864,0.00002569783,0.00003160008,0.0003635232,0.0003265543,0.000166214],"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":[0.0001419328,0.00002375873,0.003158653,0.00001700702,0.00002659242,0.0000017331,0.00002713981,0.0000143944,0.9894111,0.00006141503,0.006089388,0.001026872],"study_design_scores_gemma":[0.0006020691,0.001805502,0.02760653,0.00001633763,0.000006015189,0.00005707003,0.0001583871,0.001410665,0.8923366,0.00009033269,0.07562888,0.0002816325],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878809,0.0009006278,0.0006686148,0.0001097856,0.00002402797,0.0002888799,0.000007307089,0.00003166985,0.01008818],"genre_scores_gemma":[0.9459717,0.0002297587,0.0003734713,0.00001610356,0.0007403069,0.00003172224,0.00009482352,0.00004427995,0.05249782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09707453,"threshold_uncertainty_score":0.4151573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05215454730691459,"score_gpt":0.3681003541730715,"score_spread":0.3159458068661569,"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."}}