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Record W1528603668 · doi:10.1111/1541-4337.12007

Control of <i>Salmonella</i> Contamination of Shell Eggs—Preharvest and Postharvest Methods: A Review

2013· review· en· W1528603668 on OpenAlexaboutno aff
Anca Maria Galis, Christopher Marcq, Didier Marlier, Daniel Portetelle, Ilie Van, Yves Beckers, André Théwis

Bibliographic record

VenueComprehensive Reviews in Food Science and Food Safety · 2013
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsPreharvestSalmonella enteritidisSalmonellaPostharvestOutbreakContaminationFood safetyBiologyBiotechnologyFood microbiologyEggshellToxicologyFood scienceHorticultureEcologyVirologyBacteria

Abstract

fetched live from OpenAlex

Abstract Salmonella Enteritidis is one of the most prevalent foodborne pathogen, its main reservoir being considered the shell egg. As the concerns related to the increasing human salmonellosis cases grow, the need for an application of preventive methods either at the farm level or during the processing steps is crucial for a better control of the foodborne outbreaks due to the consumption of this specific food product. This review focuses on the application of preventive methods at the farm level, on preharvest step, in order to reduce the risk of shell eggs contamination with Salmonella , especially S . Enteritidis, through a better control of the laying hens’ infection with this pathogen. As postharvest methods, a 1st approach is the egg storage conditions and the prevention of Salmonella spp. growth and multiplication. In addition, shell eggs may be subjected to eggshell decontamination, to reduce the risk of foodborne outbreaks. Several of these latter mentioned methods are already authorized to be put in place in different countries, as it is the case in the United States of America and Canada. Their efficacy has been proven and their use is regarded by some as mandatory for ensuring shell eggs safety for the consumers.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.106
GPT teacher head0.368
Teacher spread0.262 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations83
Published2013
Admission routes1
Has abstractyes

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