{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002198841,0.00008522608,0.0001407113,0.00004250229,0.00006498532,0.000003206885,0.00004467941,0.000168413,0.000005661494],"category_scores_gemma":[0.00005378921,0.00007516979,0.00001845966,0.00007442492,0.0002022382,0.000002485823,0.00004934129,0.00004413023,3.901075e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002343281,"about_ca_system_score_gemma":0.0000492076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001349868,"about_ca_topic_score_gemma":0.0001280916,"domain_scores_codex":[0.9993765,0.00007191532,0.0001413014,0.0002359606,0.00003044875,0.0001438389],"domain_scores_gemma":[0.9997569,0.00001364144,0.00005940361,0.00008806637,0.00005011055,0.00003185418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001757636,0.00004237194,0.8338658,0.00002258862,0.00005005061,3.515952e-7,0.00003527189,0.00002419535,0.1651286,0.0005351099,0.00004870056,0.00007114029],"study_design_scores_gemma":[0.0006953219,0.0003031727,0.9956294,0.00002166157,0.00002447081,0.000002909864,0.0001326583,0.00005565706,0.002150066,0.0005383088,0.0003625994,0.00008377426],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995155,0.002281803,0.001868515,0.00006760035,0.00006291035,0.0001228372,0.00008005102,0.00000537573,0.0003558741],"genre_scores_gemma":[0.9992929,0.0002771145,0.0001101776,0.00002889596,0.00001449054,0.000004633039,0.0001334795,0.00000189672,0.0001364333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1629786,"threshold_uncertainty_score":0.3065335,"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."}}