{"id":"W1986128852","doi":"10.1016/j.gene.2006.04.024","title":"Large-scale analyses of synonymous substitution rates can be sensitive to assumptions about the process of mutation","year":2006,"lang":"en","type":"article","venue":"Gene","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Genome Atlantic; Genome Canada","keywords":"Codon usage bias; Synonymous substitution; Biology; Genetics; Selection (genetic algorithm); Molecular evolution; Silent mutation; Mutation; Constraint (computer-aided design); Substitution (logic); Amino acid substitution; Genome; Relevance (law); Mutation rate; Evolutionary biology; Gene; Computer science; 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":[0.00009395546,0.00007386331,0.000106247,0.00002733065,0.00007560172,0.000004572174,0.00006286713,0.00004041344,0.000002348899],"category_scores_gemma":[0.00002056054,0.00005720058,0.00005087287,0.0001007636,0.00006188156,4.263097e-7,0.00003057434,0.00001914018,6.399125e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005571925,"about_ca_system_score_gemma":0.00004044899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002036524,"about_ca_topic_score_gemma":0.001053068,"domain_scores_codex":[0.9994895,0.00002857944,0.0001616863,0.0001388305,0.00007317717,0.0001082056],"domain_scores_gemma":[0.9995301,0.000009511591,0.00008717642,0.0001422118,0.0002134793,0.00001756585],"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":[0.00002146156,0.0000375634,0.001684451,0.000009607526,0.00005157579,4.291142e-7,0.0003262822,0.007879091,0.9897505,0.00004411517,0.0001021838,0.00009273931],"study_design_scores_gemma":[0.0001383246,0.00006999297,0.06144039,0.00000433823,0.00004820067,0.000003543875,0.0004416926,0.0000806677,0.9373739,0.00006586693,0.0002707985,0.00006225835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955882,0.000615449,0.003068459,0.0001284573,0.00004194058,0.0001448828,0.0002029948,0.000001423473,0.0002081778],"genre_scores_gemma":[0.9991179,0.00005477032,0.0004640736,0.00006669817,0.0000778814,0.00001518822,0.0001177367,0.000005856809,0.00007986317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05975594,"threshold_uncertainty_score":0.2332572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01692258928081309,"score_gpt":0.298184380442869,"score_spread":0.2812617911620559,"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."}}