Mothers of disabled infants had higher cortisol levels in a free‐ranging group of Japanese macaques (<i>Macaca fuscata</i>)
Bibliographic record
Abstract
Glucocorticoids (GCs) are hormones released in response to stressors and can provide insight into an organism's physiological well-being. Experiencing chronic challenges to homeostasis is associated with significant deviations from baseline fecal GCs (fGCs) in many species, providing a noninvasive biomarker for assessing stress. In the group of free-ranging Japanese macaques (Macaca fuscata) at the Awajishima Monkey Center in Japan, ~17% have congenital limb malformations. We collected 646 fecal samples from 27 females over three consecutive birth seasons (May-August) and analyzed them using enzyme immunoassay to extract fGCs. We explored the relationship between fGC levels and individual (physical impairment and reproductive status), social (dominance rank and availability of kin for social support), and ecological variables (exposure to potential predators, rainfall, and wild fruit availability). A disabled infant was associated significantly with higher fGC in the mother; however, physical impairment in adult females was not significantly related to fGC levels. Females with higher dominance rank had significantly lower fGC levels than lower ranking females. Other factors did not relate significantly to fGC. These results suggest that providing care that meets the support needs of disabled infants poses a physiological challenge for mothers and suggests that physically impaired adults are able to effectively compensate for their disabilities with behavioral plasticity. Once an individual with congenital limb malformations survives infancy through their mother's care, physical impairment does not appear to influence fGC values, while social variables like dominance rank significantly influenced cortisol values in free-ranging female Japanese macaques.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".