Influence of body weight, swimming characteristics, and water temperature on the cost of swimming in brook trout (<i>Salvelinus fontinalis</i>)
Bibliographic record
Abstract
We performed respirometry experiments to estimate the spontaneous swimming costs of brook trout (Salvelinus fontinalis) for 24 combinations of fish weight (3.5, 17, and 32 g), water temperature (4, 12, and 18°C), and respirometer size (27, 54, and 108 L). Fish swimming characteristics were estimated for each experiment using videocamera recordings and image analysis. Under our experimental conditions, average swimming characteristics of fish, such as swimming speed and turning and acceleration rates, varied from 2.5- to 29-fold. Our data, alone or combined with similar published results on brook trout weighing 1 g, indicated that fish weight was the only variable that could explain a statistically significant proportion of the variations of spontaneous swimming costs for that species (r2 = 0.91). Our work confirms, with a wider range of experimental data, that spontaneous swimming costs of fish are 3- to 22-fold (8-fold average difference) more energy demanding than predicted by forced swimming models developed using fish swimming at constant speeds and directions in flumes.
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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) | 0.000 | 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".