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Record W4404458782 · doi:10.1016/j.jfp.2024.100404

Analysis of Outbreak Data Reveals Factors Contributing to Salmonellosis Outbreaks Linked to Cantaloupes

2024· article· en· W4404458782 on OpenAlexafffund
Megan Rose-Martel, Sandeep Tamber

Bibliographic record

VenueJournal of Food Protection · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsHealth CanadaCanadian Food Inspection Agency
FundersPublic Health Agency of Canada
KeywordsOutbreakFood poisoningBiologyEnvironmental healthMicrobiologyGeographyVirologyMedicine

Abstract

fetched live from OpenAlex

Over the last thirty years, the presence of Salmonella spp. on cantaloupes has been linked to multiple large and deadly foodborne outbreaks in multiple countries. To identify factors associated with the number of cases and risk of severe illness in these outbreaks, information from previous melon-associated salmonellosis outbreaks was analyzed. Data were collected from sixty outbreak investigations. Compared to other melon types, such as watermelon, honeydew, and Galia melon, cantaloupes had the highest public health burden. Cantaloupes were implicated in 43% of reported melon-related outbreaks, 51% of melon-related laboratory-confirmed cases, 54% of melon-related hospitalizations, and 76% of melon-related deaths. In the United States, imported cantaloupes were associated with higher rates of severe salmonellosis and a greater diversity of Salmonella spp. serovars compared to domestically grown cantaloupes. Cantaloupes implicated in outbreaks were equally likely to have been consumed in either private or public settings. Larger outbreaks were associated with the consumption of precut cantaloupe and/or the consumption of cantaloupes in public settings. With the identification of these contributing factors, a literature search was conducted to assess the state of knowledge concerning Salmonella and cantaloupes. Several gaps in the literature were noted and are discussed in the context of reducing the number of illnesses associated with the presence of Salmonella on cantaloupes.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.040
GPT teacher head0.278
Teacher spread0.238 · 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 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

Citations3
Published2024
Admission routes2
Has abstractyes

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