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Record W2794143326 · doi:10.1111/zph.12442

Outbreak of <i>Salmonella</i> Typhimurium associated with feeder rodents

2018· article· en· W2794143326 on OpenAlexafffundabout
Linda Vrbova, Sujani Sivanantharajah, R. Walton, Yvonne Whitfield, Calvin Yee Fen Lee, Isabelle Picard, N. Chapinal, Colette Gaulin, Lorelee Tschetter, Joanne Tataryn

Bibliographic record

VenueZoonoses and Public Health · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsMinistère de l'Agriculture, des Pêcheries et de l'AlimentationBC Centre for Disease ControlPublic Health OntarioMinistère de la Santé et des Services Sociaux (Québec)Public Health Agency of Canada
FundersPublic Health Agency of Canada
KeywordsOutbreakSalmonellaVeterinary medicineEnvironmental healthRodentBiologyMedicineVirologyEcology

Abstract

fetched live from OpenAlex

In December 2012, an increase in human Salmonella Typhimurium cases was identified in the province of Ontario, Canada launching an outbreak investigation. The outbreak spanned 3 years (2012-2014), with 134 cases reported from five Canadian provinces. There was a substantial burden of illness among children: 45% of cases were children 12 years old or under, and 23% of cases were under 5 years old. Epidemiologic, traceback and laboratory findings linked this outbreak to feeder rodents (used to feed snakes) supplied by a network of rodent breeders in Ontario. Cases likely acquired their illness through either direct or indirect contact with feeder rodents. This investigation not only contributes to the weight of evidence on the risk that feeder rodents pose, but also underscores the importance of investigating indirect animal contact and associated risks, especially for high-risk individuals.

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)0.000
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 score0.099
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.258
Teacher spread0.209 · 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

Citations22
Published2018
Admission routes3
Has abstractyes

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