Content Validation and Semantic Evaluation of a Check-List Elaborated for the Prevention of Gluten Cross-Contamination in Food Services
Bibliographic record
Abstract
Conditions associated to the consumption of gluten have emerged as a major health care concern and the treatment consists on a lifelong gluten-free diet. Providing safe food for these individuals includes adapting to safety procedures within the food chain and preventing gluten cross-contamination in gluten-free food. However, a gluten cross-contamination prevention protocol or check-list has not yet been validated. Therefore, the aim of this study was to perform the content validation and semantic evaluation of a check-list elaborated for the prevention of gluten cross-contamination in food services. The preliminary version of the check-list was elaborated based on the Brazilian resolution for food safety Collegiate Board Resolution 216 (RDC 216) and Collegiate Board Resolution 275 (RDC 275), the standard 22000 from the International Organization for Standardization (ISO 22000) and the Canadian Celiac Association Gluten-Free Certification Program documents. Seven experts with experience in the area participated in the check-list validation and semantic evaluation. The criteria used for the approval of the items, as to their importance for the prevention of gluten cross-contamination and clarity of the wording, was the achievement of a minimal of 80% of agreement between the experts (W-values ≥ 0.8). Moreover, items should have a mean ≥4 in the evaluation of importance (Likert scale from 1 to 5) and clarity (Likert scale from 0 to 5) in order to be maintained in the instrument. The final version of the check-list was composed of 84 items, divided into 12 sections. After being redesigned and re-evaluated, the items were considered important and comprehensive by the experts (both with W-values ≥ 0.89). The check-list developed was validated with respect to content and approved in the semantic evaluation.
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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 | 0.001 | 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".