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Foodborne botulism outbreak involving different nationalities during the Rugby World Cup: critical role of credit card data and rapid international cooperation, France, September 2023

2023· article· en· W4388973515 on OpenAlex
Laure Meurice, Laurent Filleul, Aurélie Fischer, Annie Burbaud, Gauthier Delvallez, Laure Diancourt, Sophie Bélichon, Benjamin Clouzeau, Denis Malvy, Magali Labadie, Coralie Bragança, Hendrik Wilking, Rafaela Franca, Greg Martin, Gauri Godbole, Mathieu Tourdjman, Nathalie Jourdan‐Da Silva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEurosurveillance · 2023
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionAgence Nationale de Sécurité Sanitaire de l’Alimentation, de l’Environnement et du TravailPublic Health AgencyPublic Health Agency of Canada
KeywordsOutbreakBotulismEnvironmental healthCoronavirus disease 2019 (COVID-19)MedicineGeographyConsumption (sociology)Medical emergencySocioeconomicsVirologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

In September 2023, a severe outbreak of type B botulism with fifteen cases was linked to consumption of canned sardines at a restaurant in Bordeaux, France, during the Rugby World Cup. The cases were from seven countries. One death was recorded. Outbreak investigation using credit card data, rapid communication between health authorities of the affected countries and broad media communication allowed identification of cases and exposed persons and prevented further severe outcomes.

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.

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 score0.051
Threshold uncertainty score0.462

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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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