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Record W35902765

Food safety issues and information needs: an online survey of public health inspectors.

2012· article· en· W35902765 on OpenAlexaffabout
Mai Pham, Andria Q Jones, Catherine E. Dewey, Jan M. Sargeant, Barbara Marshall

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFood safetyEnvironmental healthPublic healthFood safety risk analysisResource (disambiguation)Information needsBusinessMedicineNursing
DOInot available

Abstract

fetched live from OpenAlex

In the study described in this article, the authors investigated the perceptions and needs of public health inspectors (PHIs) in the province of Ontario, Canada, with regard to food safety issues and information resources. A cross-sectional online survey of 239 Ontario PHIs was conducted between April and June 2009. Questions pertained to their perceptions of key food safety issues and foodborne pathogens, knowledge confidence, available resources, and resource needs. All respondents rated time-temperature abuse, inadequate hand washing, and cross contamination as important food safety issues. Salmonella, Campylobacter, and E. coli O157:H7 were pathogens reported to be of concern to 95% of respondents (221/233). Most respondents indicated that they were confident in their knowledge of food safety issues and foodborne pathogens, but wanted a central, online resource for food safety information and ongoing food safety education training for PHIs. The data from the authors' study can be used in the development of information resources targeted to the needs of PHIs involved in food safety.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.307

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 communication0.0000.001
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 head0.145
GPT teacher head0.257
Teacher spread0.112 · 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

Citations8
Published2012
Admission routes2
Has abstractyes

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