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Record W1996915385 · doi:10.1080/09603123.2013.800961

The cooling profile of hot-cooked mussels stored in domestic insulated coolers amongst food vendors in Prince Edward Island, Canada

2013· article· en· W1996915385 on OpenAlexaffabout
Richard Meldrum, Peter R Millar, Peter Strahlendorf

Bibliographic record

VenueInternational Journal of Environmental Health Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEnvironmental scienceAnimal scienceFisheryToxicologyBiology

Abstract

fetched live from OpenAlex

It is common during outdoor events on Prince Edward Island, Canada for vendors to store hot-cooked mussels in domestic coolers. Provincial legislation states that hot product should be maintained at a minimum of 60 °C. A study was conducted to ascertain how long mussels could be stored before the temperature decreased to less than 60 °C. Hot, cooked mussels were placed into coolers and the temperature measured every 10 min for 4 h. It was found that when the cooler was unopened, the mean temperature dropped to less than 60 °C in 56 min. For coolers opened every 10 min, the mean temperature decreased to less than 60 °C in 38 min. For coolers opened every 10 min with mussels removed, the mean temperature decreased to less than 60 °C in 52 min. It was concluded that mussels should not be stored for more than 30 min and temperature should be regularly monitored.

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)0.002
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 score0.391
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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