EATING BEHAVIOUR OF INSECTIVOROUS BATS
Bibliographic record
Abstract
Eating behaviour in animals can vary with age, sex and foraging strategy and as a function of food hardness. Such variation may contribute to observed dietary differences within and among species and could indicate variation in the optimal foraging strategies of intra- and inter-specific groups. I tested the ability of Ontario insectivorous bats to consume hard and soft mealworm-based food items. I quantified feeding behaviour based on the bats’ ability to consume and manipulate the food item, consumption time, chew frequency and total chews to consume. Based on age-specific differences in these variables, adult Myotis lucifugus were superior to subadults at eating hard food items but not when eating soft food items. A similar, but less pronounced difference existed between adult and subadult Eptesicus fuscus. There was no effect of sex when Myotis lucifugus ate either food item. The gleaner, Myotis septentrionalis, was superior to the similarly-sized aerial hawker, Myotis lucifugus, at consuming hard food items.
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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".