Structure and composition of Nycteribiidae and Streblidae flies on bats along an environmental gradient in northeastern Brazil
Bibliographic record
Abstract
Bats can be parasitized by several arthropod groups, including ectoparasitic flies. The high host specificity is a common phenomenon between flies and bats. In recent years, more efforts have been employed to understand how environmental variables can influence richness and parasitic load (PL). However, many gaps still need to be filled to better understand this issue. We analyzed the PL of flies on bats sampled in three environments with different rain volume and vegetation types to verify if PL is correlated with rainfall and if there are differences in the PL on bats within and between environments. Overall, there was no correlation between rainfall and PL in the same environment, nor a difference between the three environments. When tested separately, Seba’s short-tailed bats (Carollia perspicillata (Linnaeus, 1758)) had a difference in prevalence of flies between environments and flat-faced fruit-eating bats (Artibeus planirostris (Spix, 1823)) had a greater abundance of flies in the rainy season in a semiarid area. There was no difference in PL between male and female bats. Our results suggest that bat–fly interactions are driven by several factors, not only by the amount of rainfall or vegetation, and that different host species may respond differently with no obvious general pattern.
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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 | 0.001 | 0.001 |
| 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".