Wound Healing in the Flight Membranes of Big Brown Bats
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biologists routinely punch the flight membranes of bats to collect tissue for molecular analyses, or to mark animals in the field, or both. The current standard is to biopsy the wing membrane (chiropatagium) because it is easy to access and is less vascularized, and thus bleeds less, than the tail membrane (uropatagium). Although flight membrane biopsies are assumed not to affect the bat's ability to fly or capture prey, almost nothing is known about wound healing times and the optimal punch size or location for tissue excision. We measured wound healing in the wing and tail membrane of 32 big brown bats (Eptesicus fuscus) biopsied with 2 circular punch tool sizes, and quantified the concentration of DNA extracted from the excised tissue. Our results show that tail wounds healed significantly faster than wing wounds for both 4-mm- and 8-mm-diameter biopsy wounds. We also were able to extract significantly more DNA from tail biopsies than from wing biopsies of the same size. The newly healed tissue remains unpigmented for considerable time after wound closure, and this allows identification of individuals for an extended period. We hypothesize that the increased vasculature in the uropatagium contributes to faster healing times compared to the chiropatagium. Examination of our data indicates that tissue biopsy for molecular analyses in bats should be taken from the tail membrane, although biopsies of the wing membrane are useful for marking associated with recapture programs because the wound and scar will persist longer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it