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Record W2123327110 · doi:10.1017/s0950268813001714

International outbreak investigation of Salmonella Heidelberg associated with in-flight catering

2013· article· en· W2123327110 on OpenAlexafffundabout
Javiera Rebolledo, Patricia Garvey, Anthony W. Ryan, Joan O’Donnell, Martin Cormican, Sarah Jackson, Fiona Cloak, Lucy Cullen, Corien Swaan, Barbara Schimmer, Rolf Appels, Karin Nygård, Rita Finley, Nandini Sreenivasan, Annick Lenglet, Céline M Gossner, P McKeown

Bibliographic record

VenueEpidemiology and Infection · 2013
Typearticle
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsPublic Health Agency of Canada
FundersFraser Health AuthorityGovernment of AlbertaPublic Health AgencyPublic Health Agency of CanadaAlberta Health Services
KeywordsOutbreakTanzaniaEnvironmental healthIdentification (biology)SalmonellaGeographyMedicineBiologyVirologyEnvironmental planning

Abstract

fetched live from OpenAlex

Rapid and wide dispersal of passengers after flights makes investigation of flight-related outbreaks challenging. An outbreak of Salmonella Heidelberg was identified in a group of Irish travellers returning from Tanzania. Additional international cases sharing the same flight were identified. Our aim was to determine the source and potential vehicles of infection. Case-finding utilized information exchange using experts' communication networks and national surveillance systems. Demographic, clinical and food history information was collected. Twenty-five additional cases were identified from Ireland, The Netherlands, Norway, USA and Canada. We conducted a case-control study which indicated a significant association between illness and consumption of milk tart (OR 10.2) and an egg dish (OR 6) served on-board the flight. No food consumed before the flight was associated with illness. Cases from countries other than Ireland provided supplementary information that facilitated the identification of likely vehicles of infection. Timely, committed international collaboration is vital in such investigations.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.314
Teacher spread0.274 · 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 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

Citations27
Published2013
Admission routes3
Has abstractyes

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