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Record W4320031990 · doi:10.22424/jdsb.2022.40.4.151

Survival Behavior of Escherichia coli O157:H7 during over 60-Day Aging of Camembert Cheeses Manufactured from Unpasteurized Raw Milk

2022· article· en· W4320031990 on OpenAlexaboutno aff
Jung‐Whan Chon, Kun‐Ho Seo, Jong-Soo Lim, Hye‐Young Youn, Dongkwan Jeong, Kwang‐Young Song

Bibliographic record

VenueJournal of Dairy Science and Biotechnology · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsnot available
FundersKonkuk University
KeywordsRaw milkPasteurizationFood scienceInoculationEscherichia coliRaw materialChemistryAgarBiologyBacteriaHorticulture

Abstract

fetched live from OpenAlex

Although many developed countries (USA, Canada, and several EU countries) allow raw milk cheese to be aged more than 60 days, these countries have strict standards for the aging conditions, such as temperature, of raw milk cheese. Spiking experiments were conducted with Camembert cheese made from raw milk, to assess the microbiological safety of raw milk cheese aged for more than 60 days. We spiked Escherichia coli O157:H7 into raw milk with different inoculation levels (high, medium, and low). Camembert cheese was prepared from the inoculated raw milk, then aged in an incubator for up to 9 weeks (63 days). There were no significant differences in pH and water activity (aW) between uninoculated cheese and cheese samples inoculated with E. coli O157:H7 (p<0.05). The pH and aW of the Camembert cheese decreased throughout the storage period. In conclusion, E. coli O157:H7 did not affect the pH and aW of the cheese samples. Cell counts were conducted every week using the agar-plating method. Inoculated cells were completely eliminated, especially in Camembert cheese, after 60 days, and the reduction rate of cells was much faster in Camembert cheese.

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)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.023
GPT teacher head0.282
Teacher spread0.259 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Dairy Science and Biotechnology→Same topicListeria monocytogenes in Food Safety→French-language works237,207→