Comparison of gastrointestinal parasite communities in vervet monkeys
Bibliographic record
Abstract
Globally, habitat degradation is accelerating, especially in the tropics. Changes to interface habitats can increase environmental overlap among nonhuman primates, people, and domestic animals and change stress levels in wildlife, leading to changes in their risk of parasite infections. However, the direction and consequences of these changes are unclear, since animals may benefit by exploiting human resources (e.g., improving nutritional health by eating nutritious crops) and decreasing susceptibility to infection, or interactions with humans may lead to chronic stress and increased susceptibility to infection. Vervet monkeys are an excellent model to understand parasitic disease transmission because of their tolerance to anthropogenic disturbance. Here we quantify the gastrointestinal parasites of a group of vervet monkeys (Chlorocebus aethiops) near Lake Nabugabo, Uganda, that frequently overlaps with people in their use of a highly modified environment. We compare the parasites found in this population to seven other sites where vervet monkey gastrointestinal parasites have been identified. The vervets of Lake Nabugabo have the greatest richness of parasites documented to date. We discuss how this may reflect differences in sampling intensity or differences in the types of habitat where vervet parasites have been sampled.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".