Lead exposure and its relationship with fecal cortisol levels in black howler monkeys (<i>Alouatta pigra</i>)
Bibliographic record
Abstract
Efficiently detecting early environmental threats to wildlife is vital for conservation. Beyond obvious dangers like habitat loss or deforestation, our study focuses on one of the most hazardous toxic metals for wildlife: lead (Pb). Pb is a widespread, cumulative, and insidious environmental pollutant that can trigger a wide range of physiological, biochemical, and behavioral disorders. In fact, Pb can cause permanent dysfunction of the major stress system, the hypothalamic pituitary adrenal (HPA) axis. We analyzed Pb and cortisol concentrations in fecal samples from Alouatta pigra in southern Mexico. Fecal samples were collected across six sites categorized as free-ranging (n = 65; conserved and disturbed) and from captive animals (n = 58). Additionally, we collected soil samples (n = 35). We found that Pb was present in 28% of fecal samples and 83% of soil samples. There was a positive relation between fecal and soil Pb levels, and fecal Pb concentration was negatively associated with cortisol levels. However, the claim of Pb being a direct interference with HPA axis requires further investigation. Given our findings, assessing wildlife exposure can be a valuable tool for understanding potential Pb exposure levels in the environment and its possible implications for human health. It can also serve as an early warning system of these consequences.
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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".