Can we define a tolerable level of risk in food allergy? Report from a <scp>E</scp>uro<scp>P</scp>revall/<scp>UK F</scp>ood <scp>S</scp>tandards <scp>A</scp>gency workshop
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is an emerging consensus that, as with other risks in society, zero risk for food-allergic people is not a realistic or attainable option. Food allergy challenge data and new risk assessment methods offer the opportunity to develop quantitative limits for unintended allergenic ingredients which can be used in risk-based approaches. However, a prerequisite to their application is defining a tolerable level of risk. This requires a value judgement and is ultimately a 'societal' decision that has to involve all relevant stakeholders. OBJECTIVE: The aim of the workshop was to bring together key representatives from the stakeholders (regulators, food industry, clinical researchers and patients), and for the first time ever discuss the definition of a tolerable level of risk with regard to allergic reactions to food. RESULTS: The discussions revealed a consensus that zero risk was not a realistic option and that it is essential to address the current lack of agreed action levels for cross-contamination with allergens if food allergen management practice is to be improved. The discussions also indicated that it was difficult to define and quantify a tolerable level of risk, although both the clinical and the industry groups tried to do so. A consensus emerged that doing nothing was not a viable option, and there was a strong desire to take action to improve the current situation. CONCLUSIONS AND CLINICAL RELEVANCE: Two concrete actions were suggested: (1) Action levels should be derived from the data currently available. Different scenarios should be examined and further developed in an iterative process. On the basis of this work, a tolerable level of risk should be proposed. (2) 'One-dose' clinical trial with a low challenge dose should be performed in multiple centres to provide additional information about the general applicability of dose-distribution models and help validate the threshold levels derived.
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.
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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it