Estimated Levels of Gluten Incidentally Present in a Canadian Gluten-Free Diet
Bibliographic record
Abstract
Avoiding exposure to gluten is currently the only effective treatment for celiac disease. However, the evidence suggests that for most affected individuals, exposure to less than 10 mg/day is unlikely to cause histological changes to the intestinal mucosa. The daily diet of people with celiac disease does not rely solely on gluten-free pre-packaged foods, but also on naturally gluten-free grains (e.g., rice, buckwheat, ...) and foods with grain-derived ingredients (i.e., flour and starches) used for cooking and baking at home. The objective of this study was to estimate the level of incidental gluten potentially present in gluten-free diets from a Canadian perspective. We have conducted gluten exposure estimations from grain-containing foods and foods with grain-derived ingredients, taking into consideration the various rates of food consumption by different sex and age groups. These estimates have concluded that if gluten was present at levels not exceeding 20 ppm, exposure to gluten would remain below 10 mg per day for all age groups studied. However, in reality the level of gluten found in naturally gluten-free ingredients is not static and there may be some concerns related to the flours made from naturally gluten-free cereal grains. It was found that those containing a higher level of fiber and that are frequently used to prepare daily foods by individuals with celiac disease could be a concern. For this category of products, only the flours and starches labelled "gluten-free" should be used for home-made preparations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".