MétaCan
Menu
Back to cohort
Record W4319594890 · doi:10.3390/foods12040723

Prevalence of Foodborne Viruses in Berries Harvested in Canada

2023· article· en· W4319594890 on OpenAlexafffundabout
Eva Chatonnat, Kim Manseau-Ferland, Éric Jubinville, Valérie Goulet-Beaulieu, Julie Jean

Bibliographic record

VenueFoods · 2023
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsNorovirusHepatitis a virusFecesBiologyFood scienceContaminated foodHepatitis AFood contaminantVirusHepatitis E virusVirologyMicrobiologyHepatitisGenotype

Abstract

fetched live from OpenAlex

It is known that the transmission of different foodborne viruses can occur either via discharge of contaminated water close to the production environment or via close contact with animal feces. Cranberries are intimately associated with water throughout their production cycle, and blueberries grow close to the ground which could lead to contact with wildlife. The aim of this study was to evaluate the prevalence of human norovirus (HuNoV GI and GII), hepatitis A virus (HAV) and hepatitis E virus (HEV) in two berries produced commercially in Canada. The detection of HuNoV and HAV on RTE cranberries and of HEV on wild blueberries was evaluated using the ISO method 15216-1:2017. Only 3 of 234 cranberry samples tested positive for HuNoV GI (3.6, 7.4, 5.3 genome copies/g, respectively) and all were negative for HuNoV GII and HAV. PMA pre-treatment and sequencing confirmed the absence of potential intact HuNoV GI particles on cranberries. None of the 150 blueberry samples tested positive for HEV. Overall, the prevalence of foodborne viruses in RTE cranberries and wild blueberries harvested in Canada is low, making these products relatively safe for consumers.

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)0.001
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 score0.289
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.054
GPT teacher head0.333
Teacher spread0.279 · 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

Citations12
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueFoodsSame topicViral gastroenteritis research and epidemiologyFrench-language works237,207