76 Investigating the effects of increased soluble fiber and incremental exercise on the voluntary physical activity and behaviour of sled dogs
Bibliographic record
Abstract
Abstract Optimization of the insoluble:soluble fibers in the diets of dogs can improve gastrointestinal health by increasing commensal bacterial growth. A growing body of research suggests that improved gut health can influence behavior via the gut-brain axis. Therefore, the objectives of this study were to investigate the effects of an increased soluble fiber diet on the behavior and voluntary activity of actively training, client-owned Siberian huskies. Fourteen dogs were blocked for age, BW and sex and randomly allocated to either the control or treatment groups. The control group was fed a dry extruded diet that contained an insoluble:soluble fiber ratio of 4:1, and the treatment group was fed a dry extruded diet that contained an insoluble:soluble fiber ratio of 3:1. All dogs underwent eight weeks of incremental conditioning where they trained four days a week. Once a week, a 5-minute video recording was taken immediately pre- and post-exercise to evaluate behaviors. Activity monitors were used to record voluntary activity on two rest days and one active day during weeks -1, 1, 4, 5, and 7. All behavioral and physical activity count data were analyzed using a repeated measures mixed model to test for differences between dietary treatments and week. No differences were observed between treatment or control dogs for any behavior or voluntary physical activity levels (P > 0.05); however, all dogs experienced an exercise-induced reduction in locomotive behaviors prior to exercise throughout the 8-week conditioning period (P < 0.05). Additionally, all dogs were more active during the second consecutive day of rest relative to the first (P < 0.05). These data suggest that while increased soluble fiber in the diets of sled dogs may not affect their behavior, the exercise-related reduction in activity observed begins to recover within one rest day.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".