Do Consumers Want Seaweed in Their Food? A Study Evaluating Emotional Responses to Foods Containing Seaweed
Bibliographic record
Abstract
Seaweeds are nutrient-dense marine organisms that have been proposed as a key ingredient to produce new functional foods. This study’s first objective was to identify consumers’ emotional responses and purchase intent towards a variety of food products containing seaweed. The secondary objective was to evaluate how hunger status and lifestyle affect consumers’ emotional responses. Participants (n = 108) were asked to evaluate pictures of different food items containing seaweed (beef burger, cheddar cheese, fettuccine, fish filet, sausage, bread, yogurt, and dried seaweed) using the CATA variant of EsSense25 Profile® and a purchase-intent scale. The consumers also answered questions about their hunger status, food neophobia, food-related lifestyle, as well as open-ended comment questions about seaweed. Participants’ purchase-intent scores were highest for bread and dried seaweed, which they associated with positive emotions. The participants disliked yogurt and sausage, indicating that they were disgusted with them. Participants believed seaweed could be added to fish, savoury, and cereal grains-based foods. The participants’ hunger status as well as their food neophobia and lifestyle impacted their emotional responses. Future research should continue to investigate how emotions affect purchase intent, how participant’s hunger status affects their emotions, and how participants’ lifestyle changes how they perceive new food products.
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How this classification was reachedexpand
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 | 0.002 | 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) | 0.001 | 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 teacher head, 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".