{"id":"W2161384597","doi":"10.1534/genetics.108.092254","title":"Bayesian Comparisons of Codon Substitution Models","year":2008,"lang":"en","type":"article","venue":"Genetics","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; University of Ottawa; Canadian Institute for Advanced Research","funders":"","keywords":"Nonsynonymous substitution; Substitution (logic); Bayes' theorem; Codon usage bias; Synonymous substitution; Genetic code; Biology; Probabilistic logic; Bayesian probability; Amino acid substitution; Computational biology; Computer science; Genetics; Artificial intelligence; Amino acid; Genome; Gene; Mutation","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00006955056,0.00009227577,0.0001170712,0.00002483682,0.00006691981,0.000003119915,0.0001341309,0.0001155248,0.00001563106],"category_scores_gemma":[0.00001187771,0.00009336731,0.0000618106,0.000049166,0.0000851896,0.000001477347,0.00004156779,0.00003156586,0.000006192437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004250289,"about_ca_system_score_gemma":0.00005373474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006916369,"about_ca_topic_score_gemma":0.00001144821,"domain_scores_codex":[0.9993755,0.00003706395,0.0001676755,0.000166506,0.0001122358,0.0001410357],"domain_scores_gemma":[0.9995279,0.000004675432,0.00006759074,0.0002878624,0.00005907792,0.0000528867],"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":[0.00002847533,0.00004541739,0.001206249,0.000009775695,0.00002105753,0.00000186419,0.00003779066,0.003500197,0.9925073,0.0007516155,0.001128891,0.0007613834],"study_design_scores_gemma":[0.000191164,0.0001444101,0.0005548823,0.000006537622,0.00001158121,0.00002306945,0.00001466264,0.001628094,0.986663,0.0004533371,0.01018935,0.0001198474],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6883127,0.001179042,0.3087341,0.00002681679,0.00008145155,0.0001144498,0.00001351086,0.000007743594,0.001530087],"genre_scores_gemma":[0.9828506,0.0006549115,0.01611982,0.00004482557,0.00008004942,0.000007786384,0.00003298397,0.00001260081,0.000196445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2945378,"threshold_uncertainty_score":0.3807408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03284451916791449,"score_gpt":0.2443446322328265,"score_spread":0.211500113064912,"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."}}