Flatbreads on the Rise, What about their Nutritional Quality? The Current State of the Mediterranean Market
Bibliographic record
Abstract
Flatbreads are increasingly attracting consumers, driving them to new eating ways. To define and evaluate the nutritional intake provided by these products, flatbreads market of seven Mediterranean countries (France, Spain, Italy, Croatia, Greece, Malta, and Lebanon) were considered. Flatbreads were available in both traditional and gluten-free versions, and in the single and doble layer variety. Wheat flour was the primary ingredient in both types, while sunflower and olive oil were the most used fats. Lebanese flatbread did not contain any fat. The Spanish market mostly featured one-layer flatbreads, such as tortillas and wraps, whereas pita appeared more frequently in Greece. Many Croatian flatbreads were not fermented. In comparison to gluten-containing flatbreads, the gluten-free version had a larger number of components listed on the labels. Blending flours with starches was the most common recipe. Hydrocolloids, emulsifiers, and fibers were added largely for technical reasons, but also to increase nutritional quality. Gluten-free flatbreads, on the other hand, were discovered to have lower fiber and protein content than their gluten-containing counterparts. Furthermore, their calorie value, as well as carbohydrate and salt content, were found to be lower.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".