Maternal and social status affect hair cortisol concentrations in brown bears
Bibliographic record
Abstract
Hair cortisol concentration is affected by different biological factors, including age, sex, and reproductive status, and can provide important insights into fitness. Using cortisol concentrations of wild Scandinavian brown bears, Ursus arctos , the purpose of this study was to investigate cortisol variations among individuals in relation to age, sex, and reproductive status (solitary individuals vs individuals in a family group). Cortisol concentrations were measured in 448 hair samples of 303 brown bears (162 males and 141 females, from one to nine years of age) captured from 1990 to 2016. We found that members of family groups, i.e., mothers as well as their dependent offspring, had significantly higher cortisol concentrations compared to solitary individuals (males or females). Higher energetic costs in family groups are likely linked to growth of the offspring as well as maternal costs incurred by the rearing of offspring. Our findings provide valuable insights into the physiological effects of maternal care and reproductive status in mammals. • Hair cortisol is a measure of the long–term physiological response of individuals. • Higher hair cortisol concentrations in brown bear offspring and mothers. • Costs of cub rearing, growth and environmental adaptation offer explanations. • These findings enrich the still scanty information available on the Ursidae Family.
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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 | 0.000 |
| 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".