Spent fowl as a source of unintentional egg proteins exposure in Canadian food products
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".