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Record W2605646390 · doi:10.1089/fpd.2016.2259

The Epidemiology of Childhood <i>Salmonella</i> Infections in Alberta, Canada

2017· article· en· W2605646390 on OpenAlexafffundabout
Kate E. Faulder, Kimberley Simmonds, Joan Robinson

Bibliographic record

VenueFoodborne Pathogens and Disease · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of Alberta
FundersPublic Health Agency of CanadaAlberta Health Services
KeywordsTyphoid feverMedicineOutbreakSalmonellaEpidemiologyEnvironmental healthIncidence (geometry)Paratyphoid feverBacteremiaDemographicsPediatricsInternal medicineVirologyDemographyAntibioticsBiologyMicrobiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The objectives were to describe the incidence, demographics, laboratory findings, and suspected sources of childhood Salmonella infections in Alberta, Canada, with a focus on preventable cases. METHODS: Data from Notifiable Disease Reports for children with nontyphoidal salmonellosis (NTS) or typhoid/paratyphoid fever from 2007 through 2015 were analyzed. RESULTS: NTS was detected from 2285 children. Bacteremia was documented in 55 cases (2.4%), whereas a single infant had NTS meningitis. The suspected source was food (N = 577; 25.3%) followed by animal or animal manure contact (N = 426; 18.6%), of which a reptile was the suspected source in 264 cases (11.5%). There were 44 outbreaks with none sharing the same food source. Ninety-five children were diagnosed with typhoid/paratyphoid fever, of which 48 cases (51%) were typhoid cases in unimmunized children 2 years or older. CONCLUSIONS: There are still ∼275 pediatric cases of Salmonella infection in Alberta annually, the bulk of which are preventable. APPLICATION: Public education about reptile exposure, food safety, and pretravel immunizations could potentially prevent many cases of Salmonella infection.

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)0.002
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 score0.432
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.232
Teacher spread0.215 · 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

Citations9
Published2017
Admission routes3
Has abstractyes

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