Conspecifics influence call design in the Brazilian free-tailed bat,<i>Tadarida brasiliensis</i>
Bibliographic record
Abstract
The Brazilian free-tailed bat, Tadarida brasiliensis (Saint-Hilaire, 1824), uses calls that represent a broad continuum of design variation which is dependent upon habitat and situation, and exhibits characteristic changes in call design as bats close in on airborne targets. Here we demonstrate the influence of conspecifics on call design. We found that the peak frequency used in calls varies more as the number of bats flying in the same space increases (measured from single bats and pairs of bats). We investigated this phenomenon through comparing call-parameter differences found between two bats recorded flying together (actual pairs) with call-parameter differences between two bats each recorded flying alone at different locations that were randomly assigned to one another (virtual pairs). We found that actual pairs of bats used calls which differed in peak frequency more so than did virtual pairs. This result is particularly striking given that these frequency differences were greater between bats in the same space than between bats in two different habitats. We argue that these differences indicate that this species is practicing jamming avoidance, air traffic control, or both.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".