Quantitative Computed Tomography of Humpback Whale (<i>Megaptera novaeangliae</i>) Mandibles: Mechanical Implications for Rorqual Lunge‐Feeding
Bibliographic record
Abstract
Rorqual whales (Balaenopteridae) lunge at high speed with mouth open to nearly 90 degrees to engulf large volumes of prey-laden water. This feeding process is enabled by extremely large skulls and mandibles that increase mouth area, thereby facilitating the flux of water into the mouth. When these mandibles are lowered during lunge-feeding, they are exposed to high drag, and therefore, may be subject to significant bending forces. We hypothesized that these mandibles exhibited a mechanical design (shape and density distribution) that enables these bones to accommodate high loads during lunge-feeding without exceeding their breaking strength. We used quantitative computed tomography (QCT) to determine the three-dimensional geometry and density distribution of a pair of subadult humpback whale (Megaptera novaeangliae) mandibles (length = 2.10 m). QCT data indicated highest bone density and cross-sectional area, and therefore, high resistance to bending and deflection, from the coronoid process to the middle of the dentary, which then decreased towards the anterior end of the mandible. These results differ from the caudorostral trends of increasing mandibular bone density in mammals, such as humans and the right whale, Eubalaena glacialis, indicating that adaptive bone remodeling is a significant contributing factor in establishing mandibular bone density distributions in rorquals.
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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 | 0.000 | 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 | 0.001 | 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 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".