{"id":"W4391785812","doi":"10.1101/2024.02.12.579783","title":"Compensatory mutations potentiate constructive neutral evolution by gene duplication","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO","funders":"Fonds de Recherche du Québec - Santé; National Institute of Allergy and Infectious Diseases; Canadian Light Source; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of California, San Francisco; Office of Science; National Institutes of Health; Fonds de recherche du Québec – Nature et technologies; Eli Lilly and Company; Argonne National Laboratory; U.S. Department of Energy","keywords":"Gene duplication; Gene; Biology; Genetics; Mutation; Function (biology); Functional divergence; Mutant; Computational biology; Gene family; Genome","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":[0.001455438,0.0006926301,0.0007503201,0.0007999506,0.0004114877,0.0009773024,0.0007209404,0.0008503853,0.002374979],"category_scores_gemma":[0.0031356,0.0004178474,0.0004801025,0.0004757495,0.001268658,0.0008290151,0.002328332,0.001081083,0.0004759464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000568845,"about_ca_system_score_gemma":0.0003967015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001166045,"about_ca_topic_score_gemma":0.0002504679,"domain_scores_codex":[0.9987723,0.0003301798,0.00008978501,0.0002029844,0.0004215477,0.0001831483],"domain_scores_gemma":[0.998072,0.0008614336,0.0003418968,0.0003403316,0.0001516533,0.0002325908],"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":[0.0004243778,0.0001004695,0.009964951,0.0001821295,0.0001444271,0.001579288,0.0002310083,0.002901048,0.9652461,0.006303496,0.0002207841,0.012702],"study_design_scores_gemma":[0.0002487715,0.001300785,0.05231476,0.00009231411,0.0003994115,0.01041466,0.0005605174,0.05219669,0.8482352,0.02207735,0.01198673,0.0001728117],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9873667,0.0002747551,0.007767005,0.0001665947,0.00002875615,0.00003348981,0.00005922998,0.0002012054,0.004102325],"genre_scores_gemma":[0.9958066,0.000167383,0.003042645,0.0001278983,0.00001426687,0.00002973846,0.00004907202,0.00006039445,0.0007020834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002374979,"threshold_uncertainty_score":0.007945061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006971208105145251,"score_gpt":0.2082147611887747,"score_spread":0.2012435530836295,"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."}}