Leaf-nosed bat species richness (Chiroptera: Phyllostomidae) across habitat types in a neotropical wet forest of the Osa Peninsula, Costa Rica
Bibliographic record
Abstract
Neotropical ecosystems are teeming with diversity but unfortunately, many areas are experiencing dramatic levels of degradation. In this study, I compared species richness of Phyllostomidae in secondary, riparian and old growth forest sites to test whether general patterns of diversity applied at the local scale. This study synthesizes data gathered as part of undergraduate field courses that took place between 2013 and 2018 in the Osa peninsula. Much of the study area is early successional secondary forest recovering from agricultural use with remnants of old growth vegetation. Overall, 21 species of Phyllostomidae were identified over 38 nights of sampling. While there were no significant differences in species richness between old growth and secondary forest sites, there were significant difference between these two forest types and riparian habitats. These results highlight the importance of considering surrounding areas when making decisions about the conservation value of specific habitats at the local level. Faculty Mentor: Dr. Doris Audet
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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".