General scientific guidance for stakeholders on health claim applications (Revision 1)1
Bibliographic record
Abstract
[Table: see text] The general guidance for stakeholders on the evaluation of Article 13(1), 13(5) and 14 health claims was first published in March 2011. Since then, the Panel on Dietetic Products Nutrition and Allergies (NDA) has completed the scientific assessment of Article 13(1) claims except for claims put on hold by the European Commission, and has assessedadditional health claim applications submitted pursuant to Articles 13(5), 14 and also 19. In addition, comments received from stakeholders indicate that general issues that are common to all health claims need to be further clarified and addressed. This guidance document aims to explain the general scientific principles applied by the NDA Panel for the scientific assessmentof all health claims and outlines a series of steps for the compilation of applications. The general guidance document represents the views of the NDA Panel based on the experience gained to date with the scientific assessment of health claims, and it may be further updated, as appropriate, when additional issues are addressed.The document also aims to inform applicants of newprovisionsin the pre-submission phase and in the application procedure set out in the General Food Law, as amended by the Transparency Regulation. These new provisions are applicable to all applications submitted as of 27 March 2021. The version of this guidance published in 2016 remains applicable for applications submitted before 27 March 2021.
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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 | 0.112 | 0.275 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.045 | 0.015 |
| Insufficient payload (model declined to judge) | 0.078 | 0.117 |
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".