{"id":"W4281561633","doi":"10.1126/science.abk0853","title":"Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals","year":2022,"lang":"en","type":"article","venue":"Science","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":206,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; University of Alberta; University of British Columbia","funders":"Leibniz-Gemeinschaft; Research England; Natural Sciences and Engineering Research Council of Canada; Max-Planck-Institut für demografische Forschung; Research School of Biology, Australian National University; Uppsala Universitet; Universität Zürich; Centre National de la Recherche Scientifique; Vetenskapsrådet; MAVA Foundation; University of Pretoria; Koninklijke Nederlandse Akademie van Wetenschappen; Nederlands Instituut voor Ecologie; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Center for Research Resources; Australian Government; Agence Nationale de la Recherche; Royal Society Te Apārangi; National Science Foundation; University of Aberdeen; Svenska Forskningsrådet Formas; University of St Andrews; University of Exeter; University of Alberta; National Computational Infrastructure; National Cancer Institute; Leakey Foundation; Biotechnology and Biological Sciences Research Council; Université de Sherbrooke; Emory University; Natural Environment Research Council; Leibniz-Institut für Zoo- und Wildtierforschung; Norges Forskningsråd; University of Oxford; Norges Teknisk-Naturvitenskapelige Universitet; Directorate for Biological Sciences; National Geographic Society; National Institutes of Health; Muséum National d'Histoire Naturelle; Sight Research UK; Université de Montpellier; Illinois State University","keywords":"Selection (genetic algorithm); Biology; Natural selection; Variance (accounting); Population; Adaptive evolution; Evolutionary biology; Genetic Fitness; Genetic drift; Quantitative genetics; Genetic variability; Genetic variation; Biological evolution; Genetics; Demography; Computer science; Machine learning; Gene; Genotype","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007530171,0.00007205029,0.00009567828,0.00005354541,0.0003230972,0.00002412127,0.0003536897,0.0000240206,0.0001915359],"category_scores_gemma":[0.00003106197,0.00003347326,0.00002145404,0.001885504,0.0002700691,0.0002130664,0.0001602154,0.0001549299,0.00001075212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000147961,"about_ca_system_score_gemma":0.00006129524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007146531,"about_ca_topic_score_gemma":0.0001442357,"domain_scores_codex":[0.9987427,0.00007108378,0.0001691886,0.0004596596,0.000320758,0.0002366255],"domain_scores_gemma":[0.9997837,0.00002756784,0.00007028835,0.0000481798,0.00002710363,0.00004317836],"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":[0.00006704321,0.0001927399,0.3790959,0.000001538082,5.554315e-7,0.00001834538,0.0003308096,0.0001613016,0.6010109,0.0004844954,0.00004164669,0.01859472],"study_design_scores_gemma":[0.00007769771,0.0002819155,0.9958411,0.000005897361,7.269438e-7,0.00001312819,0.00109422,0.0001464872,0.001195801,0.0009581723,0.0002866775,0.00009810825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977433,0.0007868166,0.000003130337,0.0004672029,0.0001549301,0.0002098799,0.00001008832,0.00002216089,0.000602462],"genre_scores_gemma":[0.9997458,0.000009799875,0.00004713287,0.00003073139,0.00004490056,0.00004907865,0.00000234202,4.338118e-7,0.00006975815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6167452,"threshold_uncertainty_score":0.2485035,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03405788648271788,"score_gpt":0.2363209242678947,"score_spread":0.2022630377851768,"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."}}