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Record W2921136807 · doi:10.1017/s0950268818003370

Comparison of 3-day and 7-day recall periods for food consumption reference values in foodborne disease outbreak investigations

2019· article· en· W2921136807 on OpenAlexafffundabout
Vanessa Morton, M. Kate Thomas, Nadia Ciampa, J Cutler, Matt Hurst, Andrea Currie

Bibliographic record

VenueEpidemiology and Infection · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsPublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsOutbreakRecallConsumption (sociology)PopulationFood consumptionEnvironmental healthMedicineFood scienceDemographyBiologyPsychologyVirology

Abstract

fetched live from OpenAlex

Investigations into an outbreak of foodborne disease attempt to identify the source of illness as quickly as possible. Population-based reference values for food consumption can assist in investigation by providing comparison data for hypothesis generation and also strengthening the evidence associated with a food product through hypothesis testing. In 2014-2015 a national phone survey was conducted in Canada to collect data on food consumption patterns using a 3- or 7-day recall period. The resulting food consumption values over the two recall periods were compared. The majority of food products did not show a significant difference in the consumption over 3 days and 7 days. However, comparison of reference values from the 3-day recall period to data from an investigation into a Salmonella Infantis outbreak was shown to support the conclusion that chicken was the source of the outbreak whereas the reference values from a 7-day recall did not support this finding. Reference values from multiple recall periods can assist in the hypothesis generation and hypothesis testing phase of foodborne outbreak 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)0.002
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 score0.015
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.125
GPT teacher head0.345
Teacher spread0.221 · 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

Citations4
Published2019
Admission routes3
Has abstractyes

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