Laryngeal and soft palate valving in the harbour seal (<i>Phoca vitulina</i>)
Bibliographic record
Abstract
Effective ‘valving’ in the upper aerodigestive tract (UAT) is essential to temporarily separate the digestive and respiratory pathways. Marine mammals are largely dedicated to feeding underwater, and in many cases swallowing prey whole. In seals, little work has been done to explore the anatomy and function of the upper aerodigestive tract in the context of valving mechanisms that function to separate food and air pathways. Here we use videofluoroscopy, gross dissection, histology and CT renderings to explore the anatomy of the larynx and soft palate in the harbour seal (Phoca vitulina), and generate models for how valving mechanisms in the head and neck may function during breathing, phonating, diving and swallowing. Harbour seals have an elevated larynx and the epiglottis may rise above the level of the soft palate, particularly in pups when sucking. In addition, the corniculate and arytenoid cartilages with associated muscles form most of the lateral margins of the laryngeal inlet and vestibule, and move independently to facilitate airway closure. The corniculate cartilages flex over the laryngeal inlet beneath the epiglottis to completely close the laryngeal vestibule and inlet. The vocal folds are thick and muscular and the medial margin of the folds contains a small vocal ligament. The soft palate has well-defined levator veli palatini muscles that likely function to elevate the palate and close the pharyngeal isthmus during feeding. Our results support the conclusion that harbour seals have evolved UAT valving mechanisms as adaptations to a marine environment that are not seen in terrestrial carnivores.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".