Personality Variation in Little Brown Bats
Bibliographic record
Abstract
Animal personality or temperament refers to individual differences in behaviour that are repeatable over time and across contexts. Personality has been linked to life-history traits, energetic traits and fitness, with implications for the evolution of behaviour. Personality has been quantified for a range of taxa (e.g., fish, songbirds, small mammals) but, so far, there has been little work on personality in bats, despite their diversity and potential as a model taxon for comparative studies. We used a novel environment test to quantify personality in little brown bats (Myotis lucifugus) and assess the short-term repeatability of a range of behaviours. We tested the hypothesis that development influences values of personality traits and predicted that trait values associated with activity would increase between newly volant, pre-weaning young-of-the-year (YOY) and more mature, self-sufficient YOY. We identified personality dimensions that were consistent with past studies of other taxa and found that these traits were repeatable over a 24-hour period. Consistent with our prediction, older YOY captured at a fall swarming site prior to hibernation had higher activity scores than younger YOY bats captured at a maternity colony, suggesting that personality traits vary as development progresses in YOY bats. Thus, we found evidence of short-term consistency of personality within individuals but with the potential for temporal flexibility of traits, depending on age.
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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".