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Record W2145006234 · doi:10.1017/s0950268813000770

Assessing multiple foodborne, waterborne and environmental exposures of healthy people to potential enteric pathogen sources: effect of age, gender, season, and recall period

2013· article· en· W2145006234 on OpenAlexafffundabout
Julie David, André Ravel, Andrea Nesbitt, Katarina Pintar, F. Pollari

Bibliographic record

VenueEpidemiology and Infection · 2013
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversité de MontréalPublic Health Agency of Canada
FundersUniversity of WaterlooPublic Health AgencyPublic Health Agency of Canada
KeywordsEnvironmental healthRecallRecall biasTelephone surveyMedicineExposure assessmentWinter seasonDemographyPsychology

Abstract

fetched live from OpenAlex

Information is lacking in Canada on the frequency of exposures of healthy people to enteric pathogen sources (i.e. water, food, animal contact) at the community level. This information is critical to develop more robust risk assessments and prioritize control measures. A 12-month-long cross-sectional telephone survey of 1200 healthy individuals in a sentinel community was performed. Survey respondents were divided into three recall period groups (3, 7, 14 days). The occurrence of 46 exposures (including water, animal contact, environmental contact and high-risk foods) was assessed per recall period. Effect of age, gender, and season on exposures was modelled and frequencies of exposure were extrapolated. Thirty-five exposures had similar occurrences across recall periods. Age was significant for 23 exposures, season for 18, and gender for three. Exposures that vary by age and season (i.e. bottled water, swimming, etc.) warrant consideration when investigating and analysing cases of enteric illness.

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 score0.094
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.314
Teacher spread0.285 · 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

Citations17
Published2013
Admission routes3
Has abstractyes

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