{"id":"W2949564312","doi":"10.1093/molbev/msy210","title":"The Many Nuanced Evolutionary Consequences of Duplicated Genes","year":2018,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":true,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Institute of General Medical Sciences; Welch Foundation; National Institutes of Health; National Science Foundation","keywords":"Neofunctionalization; Biology; Gene duplication; Functional divergence; Evolutionary biology; Gene; Divergence (linguistics); Function (biology); Evolvability; Human evolutionary genetics; In silico; Selection (genetic algorithm); Genetics; Epistasis; Genome; Evolutionary dynamics; Molecular evolution; Computational biology; Gene family; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":{"nature":"Retraction","reason":"Duplication of Content through Error by Journal/Publisher;","date":"11/30/2018 0:00","openalex_flagged":true},"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006779569,0.0002849681,0.0005015231,0.0005232799,0.0005725133,0.001166277,0.000676623,0.0007461897,0.0007952535],"category_scores_gemma":[0.001841084,0.0002562638,0.0004553059,0.0005862287,0.001367584,0.00164759,0.0008520696,0.0007807278,0.0001493725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006030515,"about_ca_system_score_gemma":0.0002806497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005850552,"about_ca_topic_score_gemma":0.0008284734,"domain_scores_codex":[0.9996561,0.00009423077,0.00002684775,0.0001116732,0.00007385834,0.00003733625],"domain_scores_gemma":[0.9996035,0.0001836512,0.0000662051,0.00007569611,0.0000348452,0.00003618259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006037901,0.00008391582,0.1034464,0.0007829979,0.0004383673,0.007372219,0.001791113,0.1275544,0.5362225,0.1545385,0.0006943506,0.06647141],"study_design_scores_gemma":[0.00006486227,0.0005754623,0.2702922,0.0002077208,0.0005181428,0.009535333,0.00277832,0.2343944,0.1062793,0.3566434,0.01821537,0.0004955875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.971827,0.001763096,0.0217691,0.0004889274,0.0000231714,0.00000907559,0.0001392269,0.00008510761,0.003895284],"genre_scores_gemma":[0.9929885,0.0008902334,0.005372364,0.00006177399,0.00001079178,0.000007272215,0.00007610362,0.0000264358,0.0005665315],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001166277,"threshold_uncertainty_score":0.004375458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005135468357849821,"score_gpt":0.2625186492925808,"score_spread":0.2573831809347309,"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."}}