Why organisms age: Evolution of senescence under positive pleiotropy?
Why this work is in the frame
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Bibliographic record
Abstract
Two classic theories maintain that aging evolves either because of alleles whose deleterious effects are confined to late life or because of alleles with broad pleiotropic effects that increase early-life fitness at the expense of late-life fitness. However, empirical studies often reveal positive pleiotropy for fitness across age classes, and recent evidence suggests that selection on early-life fitness can decelerate aging and increase lifespan, thereby casting doubt on the current consensus. Here, we briefly review these data and promote the simple argument that aging can evolve under positive pleiotropy between early- and late-life fitness when the deleterious effect of mutations increases with age. We argue that this hypothesis makes testable predictions and is supported by existing evidence.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it