Models of the turning and fast‐start swimming dynamics of aquatic vertebrates
Bibliographic record
Abstract
Two models for unpowered and powered turns and C‐type fast‐starts were developed and applied to four different manoeuvres: unpowered turns by a streamlined fish (yellowfin tuna Thunnus albacares ), powered turns by an unstreamlined fish (boxfish Ostracion meleagris ), fast‐starts (sticklebacks Gasterosteus spp.) and a manoeuvre by a steller sea lion Eumetopias jubatus deploying control surfaces (flippers). The velocity at the end of manoeuvres (terminal velocity) was employed as the ‘benchmark variable’ for comparisons of predicted and actual performance. Good agreement was found in all cases. A log–log plot of available experimental data for turning radius v. mass shows that turning radius scales to the 0·37 power of mass ( r 2 = 0·73), close to the predicted value of 0·33. Recent interests in highly manoeuvrable aquatic vertebrates as biomimetic models for automated underwater vehicles adds to the practical utility of the models presented here.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".