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Record W2759058944 · doi:10.5864/d2017-019

Microbiological quality of Portuguese custard tarts in Toronto—a pilot study

2017· article· en· W2759058944 on OpenAlexaffvenueabout
Mike Park, Melissa Moos, Ian Young, Macdonald Chris, Richard Meldrum

Bibliographic record

VenueEnvironmental Health Review · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsChemistryFood science

Abstract

fetched live from OpenAlex

Custard poses a health risk as it can support microbial growth; however, few studies have investigated custard tarts as a potential hazard. Custard tarts were sampled from 14 Toronto bakeries for microbial quality, pH, and water activity. The custard tarts displayed the ability to support microbial growth, with a pH of between 6.3 and 6.5 and a water activity of between 0.94 and 0.96. No microbiological results exceeded the Ontario limits for post-production contamination levels of Staphylococcus aureus, Escherichia coli, and coliforms. It was concluded the heat used during the baking process likely kills any pathogens present and creates a surface too dry to support microbial growth. Therefore, custard tarts may not inherently pose the same risk as non-contained custard desserts.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.113
GPT teacher head0.365
Teacher spread0.253 · 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

Citations2
Published2017
Admission routes3
Has abstractyes

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