{"id":"W2588565694","doi":"10.1371/journal.pgen.1006585","title":"Differential paralog divergence modulates genome evolution across yeast species","year":2017,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Molecular and Cellular Biosciences; National Institute of General Medical Sciences; Canadian Institute for Advanced Research; Rita Allen Foundation; American Society for Microbiology; Howard Hughes Medical Institute; National Institutes of Health; National Science Foundation","keywords":"Biology; Genetics; Genome; Evolutionary biology; Human evolutionary genetics; Genome evolution; Divergence (linguistics); Saccharomyces cerevisiae; Yeast; Computational biology; Gene","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":[0.0002901993,0.0002727281,0.0002902095,0.0005536365,0.0002137777,0.0004534009,0.0003389781,0.0003870029,0.001399168],"category_scores_gemma":[0.0004926947,0.0002320631,0.0002702291,0.0003115518,0.0002674915,0.0002730143,0.0005344771,0.0005641981,0.0003714138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002676803,"about_ca_system_score_gemma":0.0001330664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003245383,"about_ca_topic_score_gemma":0.0007521936,"domain_scores_codex":[0.9997925,0.00003861099,0.00001936761,0.0000750125,0.00004327348,0.00003123147],"domain_scores_gemma":[0.9996588,0.000123597,0.000068511,0.00004593637,0.00005252711,0.00005056673],"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":[0.00007416459,0.00001419781,0.00268919,0.00002328075,0.00001179703,0.00006126377,0.00004845715,0.00009628239,0.9953371,0.00007069036,0.00001243467,0.00156114],"study_design_scores_gemma":[0.00004396952,0.0006568974,0.2956598,0.00002614073,0.0001136273,0.001849546,0.0005670337,0.006365292,0.6874828,0.0006040264,0.006579466,0.00005134556],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977957,0.0002406413,0.001217965,0.00002786848,0.000006844801,0.000006895585,0.0001514232,0.00005647499,0.0004960741],"genre_scores_gemma":[0.9974495,0.0001979167,0.001030806,0.00006048774,0.00000420336,0.00001309816,0.0005826574,0.00005948861,0.0006018476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001399168,"threshold_uncertainty_score":0.004680634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03368185063041779,"score_gpt":0.2887443875167319,"score_spread":0.2550625368863141,"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."}}