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Record W4282838605 · doi:10.1016/j.psj.2022.102003

Spent fowl as a source of unintentional egg proteins exposure in Canadian food products

2022· article· en· W4282838605 on OpenAlexaffabout
Jérémie Théolier, Gabrielle Vatin, Virginie Barrère, Silvia Domínguez, Samuel Benrejeb Godefroy

Bibliographic record

VenuePoultry Science · 2022
Typearticle
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFowlContaminationFood scienceEggshellBiologyChemistry

Abstract

fetched live from OpenAlex

The occurrence of egg proteins in products containing spent fowl manufactured under current practices was studied to assess the risk these food products may pose to egg-allergic consumers and to determine if Precautionary Allergen Labelling (PAL) was recommended. Spent fowl slaughtering and processing operations in 2 Canadian facilities were observed. Raw hen pieces (n = 134), coming from 2 facilities, and intermediate and processed products containing spent fowl (n = 57), coming from one facility, were analyzed using ELISA. All samples tested positive for egg proteins. Raw pieces were tested using a qualitative method (i.e., swabbing); estimated egg proteins concentrations suggest the presence of highly contaminated samples (>600 mg/kg in 2 hen wing samples). Swabbing was found to be efficient for rapid detection of eggs in raw hen pieces, but not for quantification. A comparison between swab and grind results showed that egg proteins concentration is underestimated by at least a factor 2 for whole carcasses and a factor 10 for breast, wings and drumsticks, when using the swab protocol. For intermediate and processed products, quantitative measurements indicate that egg protein levels were below 16 mg/kg. Additionally, 88 water samples from chiller tanks were analyzed and indicate that this step could be the cause of the global contamination observed with an increase in egg protein concentrations overtime during the production schedule. As egg contamination is not adequately controlled under the current good production practices, the use of PAL would be recommended for raw spent fowl products.

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)0.001
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 score0.160
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.286
Teacher spread0.260 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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