Novel Glaucomys volans vocalizations in Indiana and evidence of geographic variation in high frequency communication
Bibliographic record
Abstract
Abstract The study of ultrasonic signaling has provided important insights into the ecology of bats and marine mammals, but it is poorly understood in other mammalian taxa. Recently, ultrasonic and high frequency vocalizations were described in southern flying squirrels (Glaucomys volans) in the southeastern United States and Ontario, Canada. Notable differences in many call characteristics suggest regional variation in G. volans communication. We evaluated this observation of regional variation by examining G. volans communication in a little studied portion of their range, the Central Hardwoods Region of the United States. We recorded calls of wild G. volans near West Point, Indiana, with Anabat II ultrasonic recorders. We described frequency and time characteristics of recorded calls, categorized call syllables into types, and used a canonical discriminant function analysis to refine our classification. Our analyses yielded 11 distinct types of G. volans syllables, 7 of which are unlike any calls described in other portions of the species range. This suggests G. volans either communicates in distinct regional dialects or has a much larger call repertoire than previously known. We recommend the creation of locally specific call libraries across the range of G. volans to ensure accuracy in the study of high frequency communication.
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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 | 0.001 | 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".