Nutritional therapies to improve health: lessons from companion animals
Bibliographic record
Abstract
Companion animals represent an under-utilised resource. The present paper is designed to encourage collaborative studies. Dogs and cats are out-bred animals that are willing to consume a consistent diet for long periods, so are ideal candidates for prospective studies of naturally-occurring disease. In some studies the effect of diet on survival has been substantial. Food restriction, for example, slows the development of osteoarthritis and increases the lifespan of Labrador retrievers by 2 years, protein and P restriction more than doubles the median survival time of dogs and cats with chronic kidney disease and adding n-3 fats and arginine to the diet of dogs with stage 3 lymphoma improves median survival time by one-quarter. Obesity is also very common in both dogs and cats and is also associated with disease as in human subjects. When interpreting these results, however, it is essential to take into account pathophysiological differences among species. Dogs and cats do not display all the characteristics of metabolic disease in human subjects, they metabolise fat well and atherosclerosis and cardiac infarction are uncommon. Such differences should not, however, preclude further study because differences among species often clarify knowledge. Monitoring of disease in companion animals may also provide a surveillance system for the safety of the food supply, as illustrated by recent outbreaks of acute renal failure and liver failure in cats and dogs in the USA caused respectively by melamine and mycotoxin contamination of pet foods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".