PSVI-32 The effects of varying amylose levels in different diets on digestibility and glycemic response in canines
Bibliographic record
Abstract
Abstract This study was conducted to compare the digestibility of pulse-based diets to grain-based diets based on varying levels of amylose and study how changes in digestibility impacts glycemic response in dogs. To establish glycemic response, six diets were formulated at an inclusion level of 20% available starch with varying amylose content. A grain-based diet was formulated using rice, while pulse-based diets consisted of smooth pea, wrinkled pea (4140–4 and Amigold varieties), faba bean, or lentil. Beagles (n = 8, 4 females, 4 males) were fed the 6 different test diets for 7 days in a randomized, cross-over, blinded design. At the end of each feeding period, fecal samples were collected and beagles were fasted overnight and subjected to a glycemic test (1g/kg of diet or glucose fed). Data collected were statistically analyzed using SigmaPlot 12.0 and significance was declared at P ≤ 0.05. Amylose levels of diets varied from 4.64% to 14.82% on a dry basis. The rice-based diet had the lowest amylose content, while the wrinkled pea (Amigold variety) diet had the highest amylose content. Following the collection of glycemic response and fecal data, repeated-measures, 1-way ANOVA’s were conducted. There were significant differences observed between diets based on peak glucose levels (mmol/L, P = 0.01). The rice diet had the highest peak in glucose, while the lentil-based diet had the lowest glucose peak. Significant differences were also seen between diets based on their digestibility (P < 0.001). Rice, lentil, faba bean and smooth pea-based diets had the highest levels of digestibility, while wrinkled pea varieties had decreased digestibility. Furthermore, varying amylose found in diets can be viewed as an impacting factor on glycemic response and digestibility. Incorporating pulses with higher amounts of amylose could be utilized in dog diets to promote a low glycemic response through decreased rates of digestibility.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".