The use of ventilation frequency as an accurate indicator of metabolic rate in juvenile Atlantic salmon (Salmo salar)
Bibliographic record
Abstract
Bioenergetics studies of free-living animals have long been hampered by limitations on our abilities to measure the energy costs of different activities. Here we evaluate whether it is possible to use the opercular ventilatory beat rate of a fish to estimate its rate of energy expenditure. Changes in metabolic rate (MR) and ventilation rate (VR) were recorded in yearling Atlantic salmon ( Salmo salar , weight range 1.8–12.64 g) engaged in different activities at different temperatures while within a respirometer. MR was found to correlate strongly with VR in all fish. The relationship was linear, and both the slope and corresponding intercept of the regression equation were strongly dependent on the fish’s body weight and the test temperature. From these relationships, a general equation was generated to predict MR at a range of temperatures from knowledge of a fish’s weight and its VR; this proved to be highly accurate (correlation between predicted and observed MRs: r = 0.95), although calibration of individual fish is recommended in studies that compare performance of individuals. Visual measurements of VR may therefore provide a highly accurate, cheap, and noninvasive method of measuring the energy consumption of fish engaged in natural behaviours in more natural settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".