Estimating maximal force output of cetaceans using axial locomotor muscle morphology
Bibliographic record
Abstract
Abstract Cetaceans span a large range of body sizes and include species with the largest known locomotor muscles. To date, force output and thrust production have only been directly measured in the common bottlenose dolphin (Tursiops truncatus), although thrust forces have been hydrodynamically modeled for some whales. In this study, two metrics of epaxial muscle size—cross‐sectional area (CSA) and mass—were used to estimate force output for 22 species (n = 83 specimens) ranging in size from bottlenose dolphins to blue whales (Balaenoptera musculus). Relative to total body length (TL), maximum force output estimated based upon both muscle CSA (TL1.56 ± 0.05) and mass (TL2.64 ± 0.07) scaled at rates lower than those predicted by geometric scaling, suggesting relative force output decreases with increasing body size in cetaceans. Estimated maximal force outputs were compared to both published drag forces and to the breaking strengths of commercial fishing lines known to entangle whales. The breaking strengths of these lines are within the same order of magnitude, and in some cases, exceed the estimated maximal force output of whales. These results suggest that while powerful animals, large whales may be unable to break the extremely strong fishing line used today.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".