Echolocation calls produced by Kuhl's pipistrelles in different flight situations
Bibliographic record
Abstract
Abstract Flexibility in the echolocation call structure of bats can improve their performances, because, in some situations, some signal designs are better than others. Hence, at least some bats should adjust their echolocation calls according to the setting in which they are operating but also to the specific task at hand, that is their behavioral intention. We studied variation in the echolocation calls of Pipistrellus kuhlii emitted during four flight situations that were similar in setting but differed in behavioral context: emergence from a roost, commuting to and from foraging sites, foraging and returning to a roost. Echolocation calls produced by P. kuhlii differed significantly according to the flight situation. Call types differed most distinctly between foraging and commuting. We also found a high variance in the emergence calls we recorded, perhaps reflecting pre‐ and post‐takeoff calls. Discriminant function analysis on calls emitted while foraging, commuting or returning to the roost classified the calls to the correct group 73.3% of the time. The differences between bats' echolocation calls in different flight situations might indicate an intrinsic change in the bat's behavior. Recognizing these differences could be crucial when using call variables to identify bat species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".