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Record W7015034250

Risk Assessment of Shell Eggs Internally Contaminated with Salmonella Enteritidis

2011· other· en· W7015034250 on OpenAlexaboutno aff

Bibliographic record

VenueContact-less Assessment of In-vivo Body Signals Using Microwave Doppler Radar (InTech) · 2011
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFlockSalmonella enteritidisRisk assessmentContaminationSalmonellaInfection riskFood contaminantFood microbiology
DOInot available

Abstract

fetched live from OpenAlex

A risk assessment was performed to determine the health risks associated with the consumption of Canadian grade A eggs internally contaminated with Salmonella Enteritidis. The distribution of the prevalence of contaminated eggs yielded an average of 1.7 per million from regulated laying flocks. The poorest storage and handling conditions for eggs represent 0.6% of exposures but result in 46% of illnesses; eggs handled under ideal storage and handling conditions account for 96% of exposures and represent 49% of illnesses. These findings suggest that risk management options targeting contaminated egg prevalence and the number of illnesses from a contaminated egg would be appropriate. Simulated risk management strategies included i) vaccination of flocks moving into houses previously occupied by positive flocks, ii) test and divert flock management strategy with environmental testing for S. Enteritidis, iii) eliminating the use of pooled shell eggs in foodservice and institutional settings, and iv) eliminating S. Enteritidis growth by improving egg storage and handling conditions. Strategies aimed at flock management yielded simulated reductions in contaminated egg prevalence between 2 and 29% of baseline, with smaller simulated gains from strategies aimed at reducing the number of illnesses per contaminated egg.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0040.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.022
GPT teacher head0.300
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations21
Published2011
Admission routes1
Has abstractyes

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