Resting energy expenditure and body composition of Labrador Retrievers fed high fat and low fat diets
Bibliographic record
Abstract
A high dietary fat intake may be an important environmental factor leading to obesity in some animals. The mechanism could be either an increase in caloric intake and/or a decrease in energy expenditure. To test the hypothesis that high fat diets result in decreased resting energy expenditure (REE), we measured REE using indirect calorimetry in 10-adult intact male Labrador Retrievers, eating weight-maintenance high-fat (HF, 41% energy, average daily intake: 8018 +/- 1247 kJ/day, mean +/- SD) and low-fat (LF, 14% energy, average daily intake: 7331 +/- 771 kJ/day) diets for a 30-day period. At the end of each dietary treatment, body composition measurements were performed using dual-energy X-ray absorptiometry. The mean +/- SD REE was not different between diets (4940 +/- 361 vs. 4861 +/- 413 kJ/day on HF and LF diets respectively). Measurements of fat-free mass (FFM) and fat mass (FM) also did not differ between diets (FFM: 26.8 +/- 2.3 kg vs. 26.3 +/- 2.5 kg; FM: 3.0 +/- 2.3 vs. 3.1 +/- 1.5 kg on HF and LF diets respectively). In summary, using a whole body calorimeter, we found no evidence of a decrease in REE or a change in body composition on a HF diet compared with LF diet.
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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) | 0.001 | 0.001 |
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".