The use of sugar kelp (Saccharina latissima) as a seasoning for popcorn: An investigation of consumer acceptance, sensory perception and emotional response
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
Increasing consumer demand for health-promoting sustainable food products has led to interest in seaweed. Sugar kelp, Saccharina latissimi, is a rich source of vitamins, minerals, fibre, antioxidants, and protein, but it is underutilized as a food ingredient. Seaweed has been identified as a possible seasoning and could be used in snack foods. As such, the purpose of this study was to evaluate how consumers would use sugar kelp as a seasoning on popcorn. The consumers (n = 95) evaluated popcorn and then were asked to add sugar kelp seasoning and to reevaluate the popcorn. The amount of popcorn consumed, and the amount of seasoning used were recorded. Furthermore, the consumers evaluated the popcorn with and without sugar kelp using hedonic scales, free comment, generalized Labelled Magnitude Scales, as well as emotional response (using the EsSense25 profile). The consumers, on average, used 2.5 g of seasoning and consumed the same amount of both samples (with and without sugar kelp). The addition of sugar kelp decreased the liking scores, increased the intensity of umami and bitterness in the samples, and led to fishy, seaweed, and pepper flavours being perceived. It also led to the reduction of positive emotions and an increased selection of negative emotions. The consumers identified that they are interested in foods containing seaweed, but based on the results of the study, the addition of sugar kelp seasoning needs to be further explored.
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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