{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005255685,0.001128206,0.001138924,0.00145893,0.0005706,0.001316081,0.002796136,0.002860191,0.002968545],"category_scores_gemma":[0.01554335,0.0006538483,0.001494544,0.001488397,0.002561872,0.002394256,0.001476443,0.002347404,0.0009464794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135316,"about_ca_system_score_gemma":0.0009590234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002082138,"about_ca_topic_score_gemma":0.001208188,"domain_scores_codex":[0.997106,0.001612144,0.0001003164,0.0007033275,0.0003331254,0.0001450042],"domain_scores_gemma":[0.9944249,0.003877318,0.0005263513,0.0007011497,0.000252418,0.0002179055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006928282,0.0002312238,0.04117883,0.0002343978,0.0003933317,0.00110856,0.0004319134,0.4459102,0.0193088,0.4344596,0.002483374,0.05356698],"study_design_scores_gemma":[0.00005606242,0.0001281461,0.002293071,0.000008033769,0.00002685355,0.0003305253,0.00002307418,0.8594104,0.0005403858,0.1360137,0.001139331,0.00003051021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09684458,0.0002447054,0.8976328,0.001005397,0.000107666,0.0001085851,0.0004937403,0.0004816644,0.003080773],"genre_scores_gemma":[0.823009,0.0002212777,0.1710634,0.0006224604,0.0001555203,0.0005368993,0.0008636764,0.0001681685,0.003359583],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005255685,"threshold_uncertainty_score":0.02779508,"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."}}