Acceptance of oat‐based beverages tailored for patients with cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Oat-based beverages are a nutritious product with the potential to support increased nutrient intake of patients with cancer. The aim of this research was to evaluate the sensory acceptance of oat-based beverages and perceptions of oats among patients with cancer as future vehicles for nutrient delivery. In study 1, three flavors of oat-beverages were well accepted without significant difference in liking among flavors or serving temperature, or between patients with cancer and healthy participants. Patients with cancer more frequently rated the beverages as too sweet compared to healthy participants; flavor intensity was just about right for all participants. In the second study, one of two formulations fortified with protein and fish oil was not different in liking compared to the unfortified chocolate product. Patients associated oat food products with specific oat-based food products and oat health benefits in a free-word association task in the third study. Together, sensory acceptance and the perceived health benefits of oats indicate the potential for oats to be incorporated in fortified and unfortified products tailored for patients with cancer. PRACTICAL APPLICATION: The three studies presented here to assess the sensory acceptance of oat-based beverages and perceptions of oats among patients with cancer demonstrate that oats can be incorporated in fortified and unfortified products tailored for patients with cancer. Inadequate nutrition is highly prevalent among oncology patients and there is a lack of available products targeted to improve their nutritional intake. These findings can support product developers and sensory scientists in the development and evaluation of food products acceptable to this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it