Consumer Perception and Sensory Drivers of Liking of Fortified Oat Milks
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.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".