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Record W3142516488 · doi:10.2903/j.efsa.2021.6543

Guidance on the preparation and presentation of applications for exemption from mandatory labelling of food allergens and/or products thereof pursuant to Article 21 (2) of Regulation (EU) No 1169/20111

2021· article· en· W3142516488 on OpenAlexaff

Bibliographic record

VenueEFSA Journal · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural safety and regulations
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsEuropean commissionEuropean unionPresentation (obstetrics)BusinessLabellingCommissionMedicineRisk analysis (engineering)BiotechnologyMarketingPublic relationsPolitical sciencePsychologyBiologyFinanceSurgeryInternational trade

Abstract

fetched live from OpenAlex

[Table: see text] Following a request from the European Commission, the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA) was asked to deliver a scientific opinion on Scientific and technical guidance for the preparation and presentation of applications for exemption from mandatory labelling of food allergens and/or products thereof. This guidance applies to food ingredients or substances with known allergenic potential listed in Annex II of Regulation (EU) No 1169/2011 or products thereof, and aims to assist applicants in the preparation and presentation of well-structured applications for exemption from labelling. It presents a common format for the organisation of the information to be provided and outlines the information and scientific data which must be included in the application, the hierarchy of different types of data and study designs, reflecting the relative strength of evidence which may be obtained from different study types and the key issues which must be addressed in the application in order to assess the likelihood of a food allergen-derived preparation/foodstuff(s) triggering adverse reactions in sensitive individuals under the proposed conditions of use. This guidance document was adopted by the NDA Panel in 2013 and updated in 2017 to reflect the application of Regulation (EU) No 1169/2011. Upon request from the European Commission in 2020, it has been revised to inform applicants of new provisions in the pre-submission phase and submission application procedure set out in Regulation (EC) No 178/2002, as amended by Regulation (EU) 2019/1381 on the transparency and sustainability of the EU risk assessment in the food chain, that are applicable to all applications submitted as of 27 March 2021.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.082
metaresearch head score (Gemma)0.200
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.152
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0820.200
Meta-epidemiology (narrow)0.0020.004
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0060.004
Science and technology studies0.0050.004
Scholarly communication0.0110.007
Open science0.0090.005
Research integrity0.0310.012
Insufficient payload (model declined to judge)0.1520.183

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.

Opus teacher head0.033
GPT teacher head0.253
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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