How social behaviour and life-history traits change with age and in the year prior to death in female yellow-bellied marmots
Bibliographic record
Abstract
Abstract Studies in natural populations are essential to understand the evolutionary ecology of senescence and terminal allocation. While there are an increasing number of studies investigating late-life variation in different life-history traits of wild populations, little is known about these patterns in social behaviour. We used long-term individual based data on yellow-bellied marmots (Marmota flaviventer) to quantify how affiliative social behaviours and different life-history traits vary with age and in the last year of life, and how patterns compare between the two. We found that some social behaviours and all life-history traits varied with age, whereas terminal last year of life effects were only observed in life-history traits. Our results imply that affiliative social behaviours do not act as a mechanism to adjust allocation among traits when close to death, and highlight the importance of adopting an integrative approach, studying late-life variation and senescence across multiple different traits, to allow the identification of potential trade-offs. This article is part of the theme issue ‘Ageing and sociality: why, when and how does sociality change ageing patterns?’
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".