Relating Intramuscular Fuel Use to Endurance in Juvenile Rainbow Trout
Bibliographic record
Abstract
This study examined fuel depletion in white muscle of juvenile rainbow trout sprinted to fatigue to determine whether the onset of fatigue is associated with a measurable metabolic change within the muscle and whether muscle glycogen levels influence endurance. In this study, "fuels" refer to any energy-supplying compounds and include glycogen, phosphocreatine (PCr), and ATP. Fuel depletion in white muscle was estimated by the calculation of the anaerobic energy expenditure (AEE; in micromol ATP equivalents g(-1)) from the reduction of PCr and ATP and the accumulation of lactate. Progression of fuel use during sprinting was examined by sampling fish before they showed signs of fatigue and following fatigue. Most of the AEE before fatigue was due to PCr depletion. However, at the first signs of fatigue, there was a 32% drop in ATP. Similarly, when fish were slowly accelerated to a fatiguing velocity, the only significant change at fatigue was a 30% drop in ATP levels. Muscle glycogen levels were manipulated by altering ration (1% vs. 4% body weight ration per day) combined with either daily or no exercise. Higher ration alone led to significantly greater muscle glycogen but had no effect on sprint performance, whereas sprint training led to higher glycogen and an average threefold improvement in sprint performance. In contrast, periodic chasing produced a similar increase in glycogen but had no effect on sprint performance. Taken together, these observations suggest that (i) a reduction in ATP in white muscle could act as a proximate signal for fatigue during prolonged exercise in fish and (ii) availability of muscle glycogen does not limit endurance.
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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 | 0.000 |
| 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".