Variability in food‐processing behavior among white‐faced capuchins (<i>Cebus capucinus</i>) in Santa Rosa National Park, Costa Rica
Bibliographic record
Abstract
Observed patterns of variability in the food-processing behavior of white-faced capuchins (Cebus capucinus) across populations may reflect foraging traditions. However, there has been relatively little attention given to intrapopulation variability in food processing among groups and age/sex classes, making recent cross-population comparisons difficult to interpret. In this paper, we provide data on patterns of object use in foraging that we observed at Santa Rosa National Park, Costa Rica, for comparison with published data from a neighboring research site, Palo Verde National Park. We also describe the techniques used to process two food items consumed by Cebus capucinus at Santa Rosa, and discuss the factors that may underlie observed variability. We conducted a 6-month study on two groups of capuchins in 2001, and collected data on general activity and feeding patterns, rates and forms of object use, and distinctive processing techniques employed for two specific foods (Sloanea terniflora and Luehea candida). Rates of object-use behavior at Santa Rosa were considerably higher than those reported for Palo Verde and showed significant variation between groups and age/sex classes, as did patterns of Sloanea and Luehea processing. Observed differences in feeding rates between groups may reflect food availability or relative profitability, whereas variation between age/sex classes seems to reflect differences in the physical capabilities, foraging strategies, and the relative experience of mature and immature animals. Further research is needed to identify how a social context may influence the acquisition of food-processing techniques in juveniles and the development of foraging traditions in social groups.
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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 | 0.001 | 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) | 0.000 | 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".