Consumer Perception and Sensory Drivers of Liking of Fortified Oat Milks
Why this work is in the frame
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Bibliographic record
Abstract
Oat milk was fortified with β-glucan at a level that attains health benefits and protein at a level equivalent to that of cow’s milk. This study aimed to identify consumer perceptions and evaluate the sensory attributes of fortified plain and chocolate oat milks. Oat milk consumers (n = 106) evaluated four samples: C (Control), 0Pro (6.25 g/L β-glucan), LPro (6.25 g/L β-glucan and 15.23 g/L oat protein), and HPro (6.25 g/L β-glucan and 30.45 g/L oat protein); and they completed free-word association (FWA), liking ratings, just-about-right (JAR), check-all-that-apply (CATA), and conjoint analysis (CA). Oat milk was associated with sensory descriptors, environmental sustainability, and health benefits. C and 0Pro products were liked significantly more than LPro and HPro. C and 0Pro oat flavors and thicknesses were rated ”just about right” by majority of the participants, while LPro and HPro were rated “too much”. Positive CATA attributes were “smooth”, “fresh”, and “oat-like” while negative attributes were “rancid”, “sandy”, and “grainy”. The CA results showed consumer interest in oat milk fortified with oat protein, containing β-glucan at a level recommended for health benefits, and with protein levels higher than cow’s milk. Based on the results, β-glucan-fortified oat milk is acceptable while oat protein fortification requires reformulation or substitution with another source.
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 | 0.000 |
| 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) | 0.000 | 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