PSXI-34 Evaluating the lysine requirements of adult and senior Labrador Retrievers using low and high crude protein inclusion levels
Bibliographic record
Abstract
Abstract Despite consumer interest in senior pet care, little is known about the effect of changing crude protein (CP) levels on the lysine (Lys) requirements in young and senior dogs. Feeding crude protein in excess can lead to long-term health problems. Moreover, changing the CP content of the diet can lead differences in Lys requirements. Two experiments were conducted to determine the Lys requirements in adult and senior Labrador Retrievers through the indicator amino acid oxidation technique. Six young (< 1.5 yrs) and six old (>8 yrs) dogs were allocated to two trials (6 dogs/exp) to determine the effects of feeding 13 and 18% CP on the Lys requirement. All dogs were supplied with constant dietary Phe across diets. The control diet was fed for two days, followed by a day in which the test diet was fed, a tracer amino acid was supplied, and breath samples were collected. On test day, a priming dose of L-[1-13C]phenylalanine (Cambridge Isotope Laboratories, Inc.) based on the subject’s body weight was supplied, followed by [1-13C]Phe doses every 30 minutes, spanning a four hour period. A respiration mask was placed on each subject every 30 minutes (Oxymax, Columbus Instruments), 13CO2 was collected, and enrichment was determined by isotope ratio mass spectrometry (IRMS). Results for IRMS were converted to atom percent excess (APE) and analyzed using a broken-line model of best fit (JMP® Pro 15). Oxidation results showed that for a 13% CP diet, the Lys mean and population safe requirements (mean±2SD) were 1.56±0.25 and 0.81±0.37 g/1000kcal for adult and senior dogs, respectively. For the 18% CP diet, adult and senior dog mean and population safe requirements were 1.36±0.18 and 0.86±0.07 g/1000kcal accordingly. The results suggest that as dogs age, the lowered lean mass requires less AA nitrogen and Lys to maintain body tissues.
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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) | 0.002 | 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".