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Record W4293240292 · doi:10.47339/ephj.2022.213

Food premises inspection violations and inspection frequency during COVID-19 in Vancouver Island Health Authority

2022· article· en· W4293240292 on OpenAlexvenueaboutno aff
Jessi L. Smith, Environmental Health BCIT School of Health Sciences, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessPandemicPublic healthCoronavirus disease 2019 (COVID-19)Environmental healthHazardCompliance (psychology)Food inspectionPublic relationsFood safetyMedicineNursingPolitical sciencePsychology

Abstract

fetched live from OpenAlex

Food service establishments, such as restaurants are subject to regulatory compliance, which acts to protect the health of the public from health risks and hazards that may arise in these settings. Ensuring compliance during inspections is carried out by public health professionals including Environmental Health Officers (EHOs). The COVID-19 Pandemic has impacted the public health sector, with many programs, services and professional involvement being enhanced to better support the COVID-19 response. This study investigated whether restaurant inspections on Vancouver Island, British Columbia, were impacted during COVID-19, including inspection frequency, inspection violations and hazard ratings.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score1.000

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 studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.252
Teacher spread0.214 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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