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Record W2967302117 · doi:10.4315/0362-028x.jfp-19-005

Outbreak of Escherichia coli O157:H7 Infections Linked to Mechanically Tenderized Beef and the Largest Beef Recall in Canada, 2012

2019· article· en· W2967302117 on OpenAlexaffabout
Andrea Currie, Lance Honish, J Cutler, Annie Locas, Marie‐Claude Lavoie, Colette Gaulin, Eleni Galanis, Lorelee Tschetter, Linda Chui, Marsha Taylor, F. Jamieson, Matthew W. Gilmour, Constance Ng, Sarbjit Mutti, Victor Mah, Meghan Hamel, Amalia Martínez, Enrico Buenaventura, Linda Hoang, Ana Pacagnella, Danielle Ramsay, Sadjia Békal, Kelly Coetzee, Chrystal Berry, Jeff Farber, On Behalf Of The National Investigative Team

Bibliographic record

VenueJournal of Food Protection · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsUniversity of GuelphProvincial Laboratory of Public HealthBC Centre for Disease ControlAlberta HealthHealth CanadaGovernment of Newfoundland and LabradorAlberta Health ServicesSte. Anne's HospitalMinistry of Health and Social ServicesCanadian Food Inspection AgencyMinistère de l'Agriculture, des Pêcheries et de l'AlimentationPublic Health Agency of Canada
Fundersnot available
KeywordsOutbreakBeef cattleEscherichia coliFood contaminantBiologyVeterinary medicineFood scienceBiotechnologyMedicineAnimal scienceVirology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 score0.960
Threshold uncertainty score0.870

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 communication0.0000.000
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 head0.019
GPT teacher head0.213
Teacher spread0.193 · 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

Citations33
Published2019
Admission routes2
Has abstractno

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