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Record W2197342951 · doi:10.3148/64.2.2003.59

<i>Consumer Food Handling Recommendations:</i> Is thawing of turkey a food safety issue?

2003· article· en· W2197342951 on OpenAlexaffvenue
Bonnie J. Lacroix, Kelly Wing Man Li, Douglas Powell

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFood safetyFood spoilageEnvironmental healthBusinessWork (physics)Health professionalsScientific evidencePublic healthConsumer safetyMedicineFood packagingMarketingRisk analysis (engineering)Food scienceHealth careNursingEngineeringPolitical science

Abstract

fetched live from OpenAlex

While it is important that dietitians and other health or food professionals provide consistent messages to the public about food safety, it is equally important that the information be evidence-based. Conflicting recommendations are evident when reviewing consumer publications from food safety advisory groups and the scientific literature. In addition, caveats are attached to the various food-handling methods. Pathogens, spoilage microorganisms, and contamination of the work area are the major concerns in thawing turkey. While several methods, including thawing on the counter at ambient temperatures, can be employed for thawing turkey, cooking to an adequate internal temperature, validated with a meat thermometer, is the more critical step. The findings indicate that providing clients or consumers with clear, consistent, evidence-based messages is difficult for food and health professionals. Further research is required to corroborate best practices in a kitchen setting. This paper is of interest to professionals who counsel clients at high risk for foodborne illness, or who counsel consumers about safe preparation of foods such as turkey.

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)0.005
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.025
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0240.011

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 head0.092
GPT teacher head0.331
Teacher spread0.240 · 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 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

Citations4
Published2003
Admission routes2
Has abstractyes

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