Wound healing in the flight membranes of wild big brown bats
Bibliographic record
Abstract
ABSTRACT The flight membranes of bats are susceptible to damage (e.g., holes and tears) from a number of sources, including impacts with natural and man‐made objects, fighting between conspecifics, and attacks by predators or pathogens. Biologists routinely biopsy bat wings as a method of tissue collection for molecular research, and sometimes for the temporary identification of animals in the field. A previous study reported that captive big brown bats (Eptesicus fuscus) rapidly and completely healed flight membrane wounds. Given that limited care is provided to animals following tissue biopsy in the field, we sought to determine whether healing times for wounds from bats in captivity were applicable to bats in the wild. We measured and compared healing times of wounds in the wing and tail membranes of 50 non‐reproductive female big brown bats from a wild population in Cuba following recapture. Tail wounds healed significantly faster than wing wounds of the same size, likely because of the increased thickness and vasculature of the tail membrane. Our data are concordant with a previous laboratory study in captive big brown bats, and confirm that tail membrane biopsies are better for obtaining tissue samples for molecular work because tail wounds heal faster than wing wounds. © 2015 The Wildlife Society.
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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 | 0.000 | 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".