Determining Feeding State and Rate of Mass Change in Insectivorous Bats Using Plasma Metabolite Analysis
Bibliographic record
Abstract
Insectivorous bats regularly experience dramatic and sometimes rapid changes in nutrient stores, yet our ability to study these changes has been limited by available techniques. Plasma metabolite analysis has proven effective for studying individual rates of mass change in birds but has not been validated for other taxa. We tested the effectiveness of plasma metabolite analysis by conducting a study with captive big brown bats (Eptesicus fuscus) and little brown bats (Myotis lucifugus) in the field. In the lab, we varied food availability to induce various rates of mass change. As predicted, individual rate of mass change was positively correlated with plasma triglyceride concentration, but there was no relationship with plasma beta-hydroxybutyrate concentration, whereas such a relationship has been found in birds. In the field, we collected blood samples from postlactating females as they emerged in the evening (fasted) and when they returned from feeding in the morning. Plasma triglyceride concentration was greater in fed bats than fasted bats, and the increase was less when rain limited foraging. Contrary to predictions, beta-hydroxybutyrate concentration was also greater in fed bats than fasted bats. Analysis of plasma triglyceride concentration provides a technique for assessing individual feeding state and rate of mass change of bats and will facilitate further study of bat nutritional ecology and energetics.
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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) | 0.000 | 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 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".