{"id":"W4386441809","doi":"10.1101/2023.09.01.555871","title":"Human deleterious mutation rate slows adaptation and implies high fitness variance","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institutes of Health; John Templeton Foundation","keywords":"Mutation Accumulation; Fixation (population genetics); Biology; Mutation rate; Genetics; Mutation; Population; Adaptation (eye); Genetic Fitness; Evolutionary biology; Genetic load; Epistasis; Effective population size; Genetic drift; Genetic variation; Gene; Demography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006617284,0.0002446824,0.0003724266,0.0003057982,0.0002358035,0.0006286519,0.0002460648,0.0005412798,0.001826258],"category_scores_gemma":[0.003603837,0.0002013502,0.0002857704,0.0002878173,0.0006432431,0.0005200603,0.000461354,0.0004839129,0.0003001968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003544822,"about_ca_system_score_gemma":0.0003230371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001469902,"about_ca_topic_score_gemma":0.00113354,"domain_scores_codex":[0.9996964,0.0001192836,0.000009761476,0.000101038,0.00004198301,0.00003163578],"domain_scores_gemma":[0.9992002,0.0004033073,0.0001573671,0.0001312519,0.00004576049,0.00006216344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007577091,0.0001779144,0.2307957,0.0003685124,0.000607556,0.002071335,0.000564556,0.4035915,0.2178034,0.08539292,0.00525822,0.0526107],"study_design_scores_gemma":[0.0001140464,0.0003572188,0.1812691,0.00006592519,0.0001725542,0.002314814,0.0003698983,0.6115288,0.04647174,0.1498635,0.007328854,0.0001436085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9617866,0.000322729,0.03249568,0.0005914555,0.00004049633,0.000006783395,0.0001902956,0.0002184527,0.004347418],"genre_scores_gemma":[0.9972217,0.00008229145,0.00214338,0.00007583408,0.000006644964,0.000004293561,0.00004610637,0.00002094784,0.0003988819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001826258,"threshold_uncertainty_score":0.006109416,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0148604954255082,"score_gpt":0.2328688090081191,"score_spread":0.2180083135826109,"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."}}