Radiographic analysis of vocal tract length and its relation to overall body size in two canid species
Bibliographic record
Abstract
Abstract Body size is an important determinant of resource and mate competition in many species. Competition is often mediated by conspicuous vocal displays, which may help to intimidate rivals and attract mates by providing honest cues to signaler size. Fitch proposed that vocal tract resonances (or formants) should provide particularly good, or honest, acoustic cues to signaler size because they are determined by the length of the vocal tract, which in turn, is hypothesized to scale reliably with overall body size. There is some empirical support for this hypothesis, but to date, many of the effects have been either mixed for males compared with females, weaker than expected in one or the other sex, or complicated by sampling issues. In this paper, we undertake a direct test of Fitch's hypothesis in two canid species using large samples that control for age‐ and sex‐related variation. The samples involved radiographic images of 120 Portuguese water dogs Canis lupus familiaris and 121 Russian silver foxes Vulpes vulpes. Direct measurements were made of vocal tract length from X‐ray images and compared against independent measures of body size. In adults of both species, and within both sexes, overall vocal tract length was strongly and significantly correlated with body size. Effects were strongest for the oral component of the vocal tract. By contrast, the length of the pharyngeal component was not as consistently related to body size. These outcomes are some of the clearest evidence to date in support of Fitch's hypothesis. At the same time, they highlight the potential for elements of both honest and deceptive body signaling to occur simultaneously via differential acoustic cues provided by the oral versus pharyngeal components of the vocal tract.
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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 | 0.003 | 0.001 |
| 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) | 0.002 | 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".