The Relationships between Behavioural Categories and Social Influences in the Gregarious Big Brown Bat (<i>Eptesicus fuscus</i>)
Bibliographic record
Abstract
Abstract Behavioural plasticity is a critical component of natural selection leading to evolution. However, a surge of studies in the last two decades has discovered a distinct limit to behavioural plasticity, commonly referred to as behaviour types and behavioural syndromes. We set out to understand the relationships across behavioural categories in wild‐caught adult, female big brown bats and how they compare between social and solitary behaviours. Using bats sampled from four different maternity colonies, we ran a series of behavioural assays to create a behavioural profile for each individual. The behavioural profile encompassed exploratory, learning, competitive and aggressive categories. We found that Big brown bats exhibit a mean profile relatively unique to other well‐documented species, where aggression was linked to increased competitive ability but not to boldness. Our results indicate that the solitary and socially directed behaviours of individuals are not necessarily related and that behaviours pertaining to social interactions are linked most closely to learning abilities. Furthermore, we found evidence that poor body condition may be a predictor of increased social interactions and that behaviours exhibited in the presence of conspecifics are unrelated to those exhibited in solitude. These findings indicate importance of social affiliations on individual behaviours in this species and their uniqueness relative to other well‐studied taxa.
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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".