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Record W3108075540 · doi:10.47339/ephj.2020.22

Changes in processing and labelling of frozen chicken products available to consumers in Vancouver

2020· article· en· W3108075540 on OpenAlexfundvenueaboutno aff
Kelsey Lutz, Environmental Health BCIT School of Health Sciences, Dale Chen, Lorraine McIntyre

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
FundersBritish Columbia Centre for Disease ControlBritish Columbia Institute of Technology
KeywordsBusinessFood safetySalmonellaProduct (mathematics)Convenience foodAgency (philosophy)Food productsAgricultural scienceFood scienceBiologyMathematics

Abstract

fetched live from OpenAlex

Background: Between May 2017 and May 2019, 18 Salmonella outbreaks in Canada were linked to raw chicken, resulting in the recall of 13 chicken products. Most of these products contained frozen raw breaded chicken, such as chicken nuggets, chicken fries, and breaded chicken burgers. (Public Health Agency of Canada, 2019) These products are especially risky for consumers because they may appear precooked, resulting in inadequate food safety measures being taken. (Catford, Ganz, & Tamber, 2017). Due to this concern, as of April 1, 2019, all frozen raw breaded chicken product manufacturers are required to follow one of four Salmonella control measures set out by the Canadian Food Inspection Agency (CFIA). The simplest option for processors is to precook their products to destroy Salmonella bacteria and produce a ready-to-eat product. (Government of Canada, Canadian Food Inspection Agency, & Food Safety and Consumer Protection Directorate, 2019a) Methods: Data was collected from all frozen chicken products available at 14 retail locations in Metro Vancouver that were randomly selected in previous studies carried out in 2018 and 2019 by the British Columbia Centre for Disease Control (BCCDC) and British Columbia Institute of Technology (BCIT) students. The processing status of the products surveyed in this study (n=466) was compared to those collected in the previous studies done in 2018 and 2019, respectively (n=383; n=415). Other information collected included whether product packaging contained statements of internal temperature, requirements for thermometer use, and additional food safety instructions. Data on these parameters collected in the current study (n=466) were compared to similar data collected in 2008 (n=24) and in 2018 (n=67). Photos were taken of all product labels and relevant data from the photos was compiled in Microsoft Excel. Statistical analyses were done using chi-square tests performed using NCSS 2019 software. Results: The proportion of surveyed frozen chicken products that were cooked as opposed to raw increased from 38% in 2018 to 41% in 2019 to 69% in 2020. The proportion of products containing statements regarding required internal temperatures increased from 58% in 2008 to 96% in 2018 and then decreased to 86% in 2020. 0%, 4.5%, and 1.7% of products surveyed in 2008, 2018, and 2020, respectively, included an indication to use a food thermometer. 79%, 57%, and 25% of products surveyed in the same years included additional food safety statements. Conclusions: This study showed that the ratio of cooked to uncooked frozen chicken products available to consumers in the Metro Vancouver area has increased since the CFIA’s Salmonella control measure requirements for frozen breaded chicken manufacturers were implemented in 2019. The 28% and 26% increase since 2018 and 2019, respectively, suggests that many frozen chicken product manufacturers are complying with the CFIA requirements by using a validated cook process to reduce Salmonella in their products. This study also showed that, since 2019, there has been a significant decline in the proportion of frozen chicken products that contain information about internal cooking temperatures and additional food safety information on their packaging.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.718
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

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

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 head0.057
GPT teacher head0.228
Teacher spread0.171 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

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