Effects of a stepwise exercise regimen and dietary tryptophan supplementation on the behaviour, metabolism, and faecal characteristics in mid-distance training sled dogs
Bibliographic record
Abstract
Exercise improves the health status of dogs; however, extreme exertion may lead to injuries, variable metabolic and faecal characteristics, and reduced welfare. The objective was to investigate the effects of supplemental dietary tryptophan and an exercise regimen with stepwise increases in duration and intensity on outcomes of behaviour, faecal quality, heart-rate, and metabolism of 16 Siberian Huskies. Dogs were randomly allocated into 2 groups with 8 dogs fed a control diet, and 8 fed the control diet supplemented with tryptophan to reach a tryptophan to large-neutral-amino-acid ratio of 0.075:1. The dogs were projected to run 8 km, 4 days a week at baseline, and reach 86 km, 4 days a week by week 12; however, due to inclement weather this schedule was altered. Activity monitors were worn on rest and run-days throughout the trial. Stool scoring (5-point scale: 1=hard/dry, 5=watery) occurred weekly. Every 3 weeks, dogs trained while wearing external telemetry jackets to non-invasively record heart-rate, then received a meal followed by postprandial blood collections. Activity on rest-days decreased weekly, and on run-days was negatively correlated with distance ran. Treatment did not affect rest or run-day activity. Treatment dogs had proportionately more evacuations scored between 2-3.5 compared to control dogs. Conditioning decreased mean and maximal working heat-rate, but resting heart-rate was unchanged. Treatment dogs had increased fasted and postprandial serum tryptophan compared to baseline, increased postprandial tryptophan versus fasted, and increased postprandial tryptophan compared to controls. Tryptophan supplementation improved tryptophan status and may have improved faecal characteristics compared to control fed dogs.
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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".