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Record W2279156972 · doi:10.1093/jaoac/87.6.1408

Regulatory and Compliance Activities to Protect Food-Allergic Consumers in Canada: Research in Support of Standard Setting and Consumer Protection

2004· article· en· W2279156972 on OpenAlexafffundabout
Samuel Ben Rejeb, Bruce Lauer, John Salminen, Irene Roberts, Ashwani Wadhera, Michael Abbott, David Davies, Chantal Cléroux, Dorcas Weber, Benjamin Lau, Stan Bacler, Daniel K. Langlois, Karl Kurz

Bibliographic record

VenueJournal of AOAC International · 2004
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsCanadian Food Inspection AgencyHealth Canada
FundersHealth CanadaCanadian Food Inspection AgencyH2020 European Research CouncilU.S. Department of Agriculture
KeywordsGovernment (linguistics)BusinessFood allergensEnvironmental healthConsumer protectionFood safetyAllergenMarketingMedicineAllergyImmunology

Abstract

fetched live from OpenAlex

An overview is presented of the activities of Health Canada and the Canadian Food Inspection Agency (CFIA) in the area of food allergens. Since the 1990s, changes were made in the Food and Drug Regulations in order to better protect allergic consumers by imposing labeling requirements to clearly identify sources of priority food allergens in prepackaged foods. Policies of application as well as risk management strategies are discussed with some statistics on allergen-related food recalls in Canada for the years 1997--2001. Health Canada's allergen method development program is a pioneering research initiative that was developed in the early 1990s in support of the changing Canadian regulatory environment. The objectives and some of the accomplishments of this program are presented. The development of the Canadian Compendium of Allergen Methodologies under a Web-based application to compile data on evaluated allergen detection methods will provide further support to compliance activities nationally, as well as to the international analytical community in both government and the food industry. Some emerging techniques for the confirmation of results generated by enzyme-linked immunosorbent assays are also discussed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.070
GPT teacher head0.352
Teacher spread0.282 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2004
Admission routes3
Has abstractyes

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