Breaking the speed limit — comparative sprinting performance of brook trout (<i>Salvelinus fontinalis</i>) and brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Sprinting behavior of free-ranging fish has long been thought to exceed that of captive fish. Here we present data from wild-caught brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta), volitionally entering and sprinting against high-velocity flows in an open-channel flume. Performance of the two species was nearly identical, with the species attaining absolute speeds > 25 body lengths·s−1. These speeds far exceed previously published observations for any salmonid species and contribute to the mounting evidence that commonly accepted estimates of swimming performance are low. Brook trout demonstrated two distinct modes in the relationship between swim speed and fatigue time, similar to the shift from prolonged to sprint mode described by other authors, but in this case occurring at speeds > 19 body lengths·s−1. This is the first demonstration of multiple modes of sprint swimming at such high swim speeds. Neither species optimized for distance maximization, however, indicating that physiological limits alone are poor predictors of swimming performance. By combining distributions of volitional swim speeds with endurance, we were able to account for >80% of the variation in distance traversed by both species.
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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) | 0.000 | 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".