PSLBI-16 Arginine requirements of young adult and senior Labrador retrievers
Bibliographic record
Abstract
Abstract Consumer demand for diets that meet the age-appropriate nutritional needs of their pets has steadily risen in recent years as senior dogs represent an increasing proportion of the pet population. However, few studies have targeted the specific amino acid requirements of the aging canine. In this study, the indicator amino acid oxidation (IAAO) technique was used to compare the arginine (Arg) requirements of young adult and senior Labrador retrievers. After 2-d adaptation to Arg-adequate basal diet (Arg = 0.82% dry matter), dogs underwent individual IAOO studies. In brief, all dogs were randomly fed one of six test diets with varying levels of arginine ranging from deficient to sufficient (final Arg content in experimental diets was 0.25, 0.29, 0.33, 0.71, 0.77 and 0.82% dry matter. Test diet was divided into 13 equal meals; at the 5th meal, a tracer amino acid was supplied (a bolus L-[1-13C] phenylalanine based on body weight was first given, followed by [1-13C] Phe doses every 30 min spanning a 4-h period), and breath samples were collected via respiration mask every 30 min. Total production of 13CO2 during isotopic steady state was determined by enrichment of 13CO2 in breath samples and total CO2 production was measured via indirect calorimetry and isotope ratio mass spectrometry (IRMS). Results for IRMS data were converted to atom percent excess (APE) and analyzed using segmented linear regression. The Four Rivers mean and population requirements for arginine were 1,004 ± 90.5 mg/1,000 kcal ME (mean ± 2 SD) in young adults and 919 ± 69.9 mg/1,000 kcal ME for senior dogs, which are slightly greater than the currently recommended amounts by NRC. As the pet food industry offers more specialized diets for aging canines, updating the amino acid requirements for such animals is increasingly important.
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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 | 0.001 | 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".