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Record W2092118002 · doi:10.1017/s0950268803001924

Risk factors for <i>Salmonella</i> Typhimurium DT104 and non-DT104 infection: a Canadian multi-provincial case-control study

2004· article· en· W2092118002 on OpenAlexaffabout
K. DOR, Jane A. Buxton, Brandon Henry, F. Pollari, Dean Middleton, Murray Fyfe, Rafiq Ahmed, Pascal Michel, Alejandra King, Carol Tinga, Jeffrey B. Wilson

Bibliographic record

VenueEpidemiology and Infection · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of GuelphCegep de Saint HyacintheBC Centre for Disease ControlToronto Public HealthMinistry of Health and Long Term CareHealth Canada
Fundersnot available
KeywordsSalmonellaEnvironmental healthMicrobiologyMedicineBiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

To identify risk factors for sporadic Salmonella Typhimurium definitive phage-type 104 (DT104) and non-DT104 diarrhoeal illness in Canada, we conducted a matched case-control study between 1999 and 2000. Cases were matched 1:1 on age and province of residence. Multivariate analysis suggested that recent antibiotic use [odds ratio (OR) 5.2, 95% confidence interval (CI) 1.8-15.3], living on a livestock farm (OR 4.9, 95% CI 1.9-18.9), and recent travel outside Canada (OR 4.1, 95% CI 1.2-13.8) are independent risk factors for DT104 illness. Similar analyses suggested that recent travel outside North America is a sizable risk factor for non-DT104 illness (OR 66.8, 95% CI 6.7-665.3). No food exposure was a risk factor in either analysis. Educating health-care providers and the public about appropriate antibiotic use and antimicrobial resistance is important. Appropriate administration of antibiotics to livestock, particularly cattle, and hygienic measures such as handwashing after contact with farm animals may reduce risk. Travel represents an important and probably underestimated risk factor for sporadic illness with S. Typhimurium. Improved national surveillance and detailed investigation of travel-related illness are required.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.104
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.034
GPT teacher head0.272
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 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

Citations52
Published2004
Admission routes2
Has abstractyes

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