Implementing a low‐starch biscuit‐free diet in zoo gorillas: The impact on behavior
Bibliographic record
Abstract
In the wild, western lowland gorillas travel long distances while foraging and consume a diet high in fiber and low in caloric density. In contrast, gorillas in zoos typically consume a diet that is low in fiber and calorically dense. Some items commonly used in captive gorilla diets contain high levels of starch and sugars, which are present at low levels in the natural diet of gorillas. Diet items high in simple carbohydrates are associated with obesity and heart disease in humans. Typical captive gorilla diets may also encourage undesirable behaviors. In response to these issues, we tested the behavioral impact of a diet that was biscuit-free, had low caloric density, and which was higher in volume at five institutions. We hypothesized that this diet change would reduce abnormal behaviors such as regurgitation and reingestion (R/R), decrease time spent inactive, and increase time spent feeding. The biscuit-free diet significantly reduced (and in the case of one zoo eliminated) R/R and may have reduced hair-plucking behavior. However, an increase in coprophagy was observed in many individuals following the diet change. The experimental diet caused a general increase in time the gorillas spent feeding, but this increase did not occur across all institutions and varied by individual. Interestingly, the overall time gorillas spent inactive actually increased with this diet change. Future research will examine these behavioral changes in a greater number of individuals to determine if the results remain consistent with these preliminary findings. Additionally, future research will examine the physiological impact of this diet change.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".