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The evolution of senescence through decelerating selection for system reliability

2009· article· en· W2101918864 on OpenAlexafffund
Robert A. Laird, Thomas N. Sherratt

Bibliographic record

VenueJournal of Evolutionary Biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsCarleton University
FundersOntario Innovation Trust
KeywordsBiologySenescenceEvolutionary biologyLongevityGenePopulationEcologyGeneticsDemography

Abstract

fetched live from OpenAlex

Senescence is a universal phenomenon in organisms, characterized by increasing mortality and decreasing fecundity with advancing chronological age. Most proximate agents of senescence, such as reactive oxygen species and UV radiation, are thought to operate by causing a gradual build-up of bodily damage. Yet most current evolutionary theories of senescence emphasize the deleterious effects of functioning genes in late life, leaving a gap between proximate and ultimate explanations. Here, we present an evolutionary model of senescence based on reliability theory, in which beneficial genes or gene products gradually get damaged and thereby fail, rather than actively cause harm. Specifically, the model allows organisms to evolve multiple redundant copies of a gene product (or gene) that performs a vital function, assuming that organisms can avoid condition-dependent death so long as at least one copy remains undamaged. We show that organisms with low levels of extrinsic mortality, and high levels of genetic damage, tend to evolve high levels of redundancy, and that mutation-selection balance results in a stable population distribution of the number of redundant elements. In contrast to previous evolutionary models of senescence, the mortality curves that emerge from such populations match empirical senescence patterns in three key respects: they exhibit: (1) an initially low, but rapidly increasing mortality rate at young ages, (2) a plateau in mortality at advanced ages and (3) 'mortality compensation', whereby the height of the mortality plateau is independent of the environmental conditions under which different populations evolved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.256
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2009
Admission routes2
Has abstractyes

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