{"id":"W2987941611","doi":"10.1093/sysbio/syz075","title":"A Phenotype–Genotype Codon Model for Detecting Adaptive Evolution","year":2019,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonsynonymous substitution; Biology; Adaptation (eye); Phenotype; Trait; Evolutionary biology; Molecular evolution; Selection (genetic algorithm); Genetics; Neutral theory of molecular evolution; Null model; Natural selection; Gene; Phylogenetics; Ecology; Genome; Machine learning; Computer science","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":[0.0003275742,0.0001532189,0.0003195182,0.00003464032,0.00007455341,0.000007899768,0.0001490248,0.0001773729,0.000002554337],"category_scores_gemma":[0.0001193429,0.0001271269,0.0001088007,0.00003850579,0.00003712338,5.16561e-7,0.0001134449,0.00004466901,0.00002257648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002637615,"about_ca_system_score_gemma":0.00005730063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001384828,"about_ca_topic_score_gemma":0.00004220737,"domain_scores_codex":[0.998996,0.00008252535,0.0002927691,0.0003381764,0.00004021998,0.0002502848],"domain_scores_gemma":[0.9992976,0.00004745267,0.0001676358,0.000320688,0.0001320652,0.00003459019],"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":[0.0001335619,0.00002270606,0.004056758,0.002484706,0.0002300765,8.17827e-8,0.0002108452,0.003375488,0.9822964,0.007095261,0.00002298151,0.0000711497],"study_design_scores_gemma":[0.00430549,0.004411629,0.004585399,0.001217621,0.0004728649,0.0000291323,0.002236087,0.8791077,0.05814172,0.04359136,0.0001797561,0.001721219],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8332984,0.001901705,0.162908,0.00001847738,0.0002932909,0.001241916,0.00002748044,0.000006934572,0.0003037948],"genre_scores_gemma":[0.9949878,0.000008395466,0.004409431,0.00006888584,0.0001002096,0.0001932876,0.00001561368,0.0000195159,0.0001967936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9241546,"threshold_uncertainty_score":0.5184083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02000913384105648,"score_gpt":0.244702027844687,"score_spread":0.2246928940036305,"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."}}