Stretchy nerves withstand deformation associated with lunge feeding in rorqual whales (918.21)
Bibliographic record
Abstract
Rorqual whales have evolved a remarkable feeding strategy that involves rapidly gulping enormous quantities of prey‐laden water and then more slowly separating the prey from the water by filtering the material through baleen plates suspended from the roof of the oral cavity. During the initial engulfment, the tongue inverts into a ventral pouch and balloons backwards as far as the umbilicus. Simultaneously muscles in the floor of the oral cavity, and the overlying ventral groove blubber, dramatically expand to accommodate the engulfed water that can reach a volume exceeding that of the whale itself. We have found that large nerves in the tongue and in the floor of the oral cavity of adult fin whales can stretch or extend up to twice their initial lengths. This contrasts with intercostal nerves that are virtually inextensible. Histological analysis demonstrates that nerves in the tongue and floor of the oral cavity are surrounded by a very thick connective tissue coating consisting of elastin and collagen, and that the central nerve bundle itself is folded or coiled into a small central core ‐ not unlike a coiled string inside a much thicker bunge‐cord. Intercostal nerves are not folded and have much thinner surrounding walls. Stretchy nerves are yet another extreme morphological adaptation to lunge feeding in rorqual whales. Grant Funding Source : Supported by NSERC Discovery Grants
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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 | 0.000 | 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".