{"id":"W4406780977","doi":"10.1093/gbe/evaf008","title":"Convergent Evolution and Predictability of Gene Copy Numbers Associated with Diets in Mammals","year":2025,"lang":"en","type":"article","venue":"Genome Biology and Evolution","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Core Research for Evolutional Science and Technology; Japan Science and Technology Agency; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Jiangsu Science and Technology Department; Institute of Genetics; National Institute of Genetics","keywords":"Biology; Predictability; Convergent evolution; Gene; Evolutionary biology; Genetics; Platypus; Copy-number variation; Phylogenetics; Zoology; Genome; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002826772,0.0001562402,0.0003138686,0.00156079,0.0002050996,0.0003547117,0.0002385049,0.0002626469,0.000611307],"category_scores_gemma":[0.001522446,0.0002077345,0.000221302,0.0007070865,0.0005084366,0.0002791497,0.0003526224,0.0002897338,0.0001897963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001686605,"about_ca_system_score_gemma":0.00007048625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005204882,"about_ca_topic_score_gemma":0.0005999048,"domain_scores_codex":[0.9997335,0.00005462587,0.00001660052,0.0001230106,0.00005023888,0.0000219544],"domain_scores_gemma":[0.9988526,0.000538515,0.0003679821,0.00009294404,0.00006500685,0.00008292497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004525843,0.00003347416,0.4197079,0.00008237096,0.0002085916,0.0002953607,0.0003191025,0.001302836,0.5603729,0.0004131739,0.00005888769,0.01675267],"study_design_scores_gemma":[0.000005752845,0.00004924681,0.9870243,0.000005360073,0.00003203586,0.0004673878,0.00005196031,0.002219161,0.009424563,0.0004812375,0.0002264409,0.00001266433],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983349,0.0002439229,0.001028351,0.00001346823,0.000001154132,0.000001835502,0.0001365453,0.00001308447,0.0002267445],"genre_scores_gemma":[0.9983037,0.0001067246,0.001141388,0.000009924603,0.000004496701,0.000005063884,0.0002868786,0.000009280879,0.0001324582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00156079,"threshold_uncertainty_score":0.002045035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005346054586283154,"score_gpt":0.2143074545706357,"score_spread":0.2089613999843525,"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."}}