Preacutionary labelling of cross-reactive foods: The case of rapeseed
Bibliographic record
Abstract
Food allergic individuals are exposed to unnecessary dietary restrictions due to precautionary food allergy labelling (PFAL). Two forms of PFAL exist: type I identifies the possible presence of allergenic contaminaion in foods (‘may content…’), type II indicates as potentially dangerous ingredients or contaminants that do no belong to official list of food allergens. PFAL type II is based on the fear of cross-reactivity with foods belonging to that list. PFAL type II is less known, but may be tempting for the legal offices of food companies, for clinicians in a ‘defensive medicine’ key, and even for legislators. We identify here a case of PFAL type II, allergy to rapeseed (belonging to the family of Brassicaceae ). Increasingly used for their nutritional and nutraceutic value in asthma prevention, rapeseed has been indicated by regulatory authorities in Canada and Europe as potential cross-reactor with mustard. In this review, we provide the elements for a risk assessment of cross-reactivity of rapeseed/mustard allergy in the general population both clinically and from the point of view of the molecular allergy. Three findings emerge: 1. Allergic reactions to rapeseed are exceptional 2. The allergens identified in rapeseed and mustard are similar, but not identical 3. Reactions to rapeseed have never been described in mustard-allergic patients. On the ground of existing evidence, a precautionary labeling for rapeseed as potentially dangerous for patients allergic to mustard is not justified. In the interest of patients with multiple food allergy, PFAL type II must be avoided.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".