Sources of Variation in Fecal Haptoglobin in a Population of Wild Capuchin Monkeys ( <i>Cebus imitator</i> )
Bibliographic record
Abstract
ABSTRACT The ongoing decline of non‐human primates places renewed emphasis on monitoring health in wild populations. Non‐invasive monitoring of reliable biomarkers of inflammation and immune activation allows researchers to assess individual health status without capturing or interfering with wild animals, but studies are limited by the availability of such biomarkers that are measurable from fecal and urine samples. In the present study, we aimed to validate the measurement of fecal haptoglobin, a biomarker primarily studied in relation to gut‐associated inflammation, in wild white‐faced capuchin monkeys ( Cebus imitator ), and to evaluate the relationship between fecal haptoglobin concentrations and age, sex, dominance rank, circadian effects and environmental factors including temperature and rainfall. We analytically validated the measurement of fecal haptoglobin in white‐faced capuchins. Our subsequent results did not demonstrate a relationship between haptoglobin concentrations and age, sex, dominance rank or circadian effects. However, we found significant influences of environmental conditions on fecal haptoglobin concentrations, with an increase and more variation observed during drier conditions in the early dry season, when the animals are typically under greater environmental stress. We conclude that haptoglobin measurement is feasible in wild white‐faced capuchin monkeys, and its concentrations vary in our study population, reflecting seasonal patterns of inflammation that are consistent with changes to environmental stressors associated with lower access to food and water.
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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 | 0.001 | 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".