{"id":"W1964593823","doi":"10.1002/bies.201500025","title":"Why organisms age: Evolution of senescence under positive pleiotropy?","year":2015,"lang":"en","type":"review","venue":"BioEssays","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"European Research Council; Vetenskapsrådet","keywords":"Pleiotropy; Biology; Genetic Fitness; Senescence; Evolutionary biology; Longevity; Selection (genetic algorithm); Argument (complex analysis); Mutation Accumulation; Allele; Genetics; Biological evolution; Phenotype; Genome; Gene","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":[0.0008141168,0.0006983053,0.001113058,0.001599036,0.000340435,0.001177024,0.0009436745,0.002101825,0.001726722],"category_scores_gemma":[0.0009285852,0.0002454958,0.0004219351,0.001502404,0.001382073,0.002430529,0.0008137693,0.00183781,0.001369984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008935853,"about_ca_system_score_gemma":0.001201983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008080127,"about_ca_topic_score_gemma":0.001157308,"domain_scores_codex":[0.9998565,0.00002838375,0.00001866235,0.00004473592,0.00003585374,0.0000157856],"domain_scores_gemma":[0.9996399,0.0001720349,0.0000512709,0.00001707604,0.00007727004,0.00004260327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009601183,0.00003231556,0.00065357,0.01326962,0.0001295361,0.0005532362,0.0003031549,0.000779337,0.004226616,0.03384223,0.03006076,0.9160536],"study_design_scores_gemma":[0.00001044156,0.00005784218,0.001823541,0.002861002,0.0001044757,0.001902326,0.0001631866,0.0001483714,0.0007340726,0.02394226,0.9682127,0.00003980017],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001869616,0.997256,0.0003814247,0.001149296,0.0002685858,0.000001775843,0.0000141898,0.000009696724,0.0007320931],"genre_scores_gemma":[0.001652247,0.9966158,0.0002790385,0.0006339298,0.0002890447,0.000003630165,0.00001954604,0.000002801715,0.0005038875],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002101825,"threshold_uncertainty_score":0.006483376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246501112792312,"score_gpt":0.2977563023754197,"score_spread":0.2652912912474966,"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."}}