Yellow-bellied marmot hiding time is sensitive to variation in costs
Bibliographic record
Abstract
Many species use refugia to avoid predators, but remaining in a refuge is costly because foraging and engaging in other beneficial activities are curtailed while in a refuge. Thus, we expect that the duration of refuge use will be optimized. We tested a key prediction of this optimization hypothesis in yellow-bellied marmots, Marmota flaviventris (Audubon and Bachman, 1841), by providing supplemental food next to their burrows to manipulate the costs of remaining in a refuge. We then systematically walked towards a subject that was foraging on supplementary food or a subject that was not foraging on supplementary food until the individual disappeared into its burrow. We found a significant effect of our feeding treatment; subjects with supplementary food emerged from their burrows sooner than those without it. We also found a complex interaction between our feeding treatment and immergence distance (i.e., the distance subjects were at when they disappeared into their burrows). Individuals that tolerated close approaches emerged sooner when food was present, while those that were intolerant of approaching humans took longer to emerge and emerged sooner when food was not present. Juveniles emerged significantly sooner than adults, while there was no detectable difference between emergence times for adults and yearlings. This is the first demonstration in a mammal that hiding time is sensitive to the cost of remaining in the burrow. A number of previous studies on hiding times have focused on ectothermic species. More generally, our results suggest that endotherms are also likely to optimize the time that they remain in a refuge.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".