Room without a view—Den excavation in relation to body size in brown bears
Bibliographic record
Abstract
) commonly use excavated dens for hibernation. Physical attributes of excavated dens are expected to impact the bear's heat retention and energy conservation. The objective of this study was to examine the determinants of cavity size of excavated dens and the impact of physical attributes of excavated dens on energy conservation in hibernating bears, hypothesizing that bears excavate dens in a way to minimize heat loss and optimize energy conservation during hibernation. We predicted that den cavity size would be determined by the bear's body size and that older bears would excavate better-fitting cavities to minimize heat loss, due to their previous experience. We further predicted that physical attributes of excavated dens would affect the bears' posthibernation body condition. Our results revealed that bears excavated a den cavity in relation to their body size, regardless of sex, and that older bears tended to excavate better-fitting den cavities compared to young bears, as we expected. Older bears excavated better-fitting den cavities, suggesting a potentially experience-based shift with age in den-excavation behavior and an optimum cavity size relative to a bear's body size. Our key finding is that insulation of excavated dens provided by wall/rood thickness and bedding materials had a significant positive effect on bears' posthibernation body condition. We believe that our study provides new insight into how not only the quality of denning habitat, but also the quality of dens may affect hibernating animals, by presenting a potential adaptive aspect of den preparation (age effect on efficiency in den excavation) and effect of den attributes on the posthibernation body condition of brown bears.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".