The Effects of Forest Fragment Age, Isolation, Size, Habitat Type, and Water Availability on Monkey Density in a Tropical Dry Forest
Bibliographic record
Abstract
In summary, forest fragment age is an important explanatory variable for capuchin and howler density (higher densities were found in older areas of forest), whereas it makes no contribution to explaining the density of spider monkeys. The presence of evergreen forests in ACG is also important for explaining the absolute density of all three species, as there were higher densities in fragments containing evergreen forest. Transects where water was available in the dry season had higher capuchin densities; water availability appears to be more important for this species than for the spider monkeys and howlers. Forest fragment isolation and size made little contribution to explaining the density of any primate in ACG, probably due to the large size of forest fragments surveyed. Based on these findings, we conclude that older fragments of forest with dryseason standing water, and a substantial amount of evergreen forest should be preferentially protected to enhance the conservation of white-faced capuchins, black-handed spider monkeys, and mantled howlers in Costa Rica.
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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) | 0.003 | 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".