A novel cognitive palatability assessment protocol for dogs1
Bibliographic record
Abstract
Assessment of canine palatability is important for both the pet food and pharmaceutical industries; however, the current palatability assessment protocols are limited in their utility. The most common technique, the two-pan test, does not control for the satiating effects of food and may not be useful for long-term palatability analysis because nutritional or caloric characteristics of the diets may interfere with the results. Furthermore, the large quantities of foods consumed may be detrimental to the health of animals that do not self-limit their food intake. The purpose of this study was to determine whether a cognitive protocol could be used to determine food palatability in dogs. Five beagle dogs were trained on a three-choice object-discrimination learning task. After establishing object preferences, the preferred object was associated with no reward, a second object was associated with the dog's normal laboratory diet (Purina Agribrands Canine Lab Chow No. 5006; Agribrands Purina Canada, Inc., Woodstock, ON, Canada), and the third object was associated with a commercial (Hill's P/D; Hill's Pet Nutrition Inc., Topeka, KS) diet. In the discrimination-training phase, dogs were trained until they learned to avoid the no-reward object. They were subsequently given an additional 20 test sessions, which were used to determine food preference. In the reversal phase, which involved reversal learning, the object-food associations were modified, such that the object that was previously associated with Hill's P/D diet was now associated with the normal laboratory diet and vice versa. Once the dogs learned to avoid the no-reward object, they were tested for an additional 20 sessions. All subjects learned to avoid the no-reward object during the initial learning, and the number of choices to the object associated with the Hill's P/D diet was greater than the number of choices to the objects associated with the dry laboratory diet (P < 0.05) and no reward (P < 0.05), indicating a strong preference for the Hill's P/D diet. The object preferences were reversed in only three of five dogs when the food-choice associations were reversed, although the two phases did not differ significantly from one another. The protocol in the present study provides a robust measure of food palatability and circumvents many of the limitations associated with other palatability assessment techniques. The present protocol should be useful as a replacement or adjunct to other tests of palatability, but requires further validation by comparing the assessment of more similar and novel foods directly with other palatability tests.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".