Assessment of price and nutritional quality of gluten-free products <i>versus</i> their analogues with gluten through the algorithm of the nutri-score front-of-package labeling system
Bibliographic record
Abstract
Evidence has shown that the nutritional quality of gluten-free products (GFPs) is lower than that of non-GFPs. Our main objective was to compare the nutritional quality through nutritional profiles of foods underlying the Nutri-Score front-of-pack and the price of GFPs with respect to non-GFPs, and to evaluate whether there is a correlation between both parameters. Nutritional information of all products was obtained from the CELIACBASE database and the price through Spanish supermarkets websites. Global quality using the Nutri-Score algorithm and the price were compared between both types of products. GFPs do not always have poorer quality than their counterparts. A better quality of gluten-free pasta was correlated with the higher price but also a worse quality of gluten-free muesli was correlated with the higher price. The price of GFPs compared to non-GFPs was higher up to 391.5%. However, for ham and cheese pizza, ham pizza, Marie biscuits, and baby biscuits, the difference was not statistically significant. Generally, the price of GFPs did not correlate with better nutritional quality. Nutri-Score would ease the nutritional quality identification, empowering consumers and could also influence manufacturers to improve the nutritional quality of GFPs. Nowadays, given that many GFPs have poor nutritional quality, they should be included only occasionally in a balanced gluten-free diet.
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.
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 | 0.000 | 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 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".