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Record W4213218823 · doi:10.2196/36438

A Food Poisoning Outbreak Caused by Shigella in Al-Mafraq, Jordan, in 2019

2022· article· en· W4213218823 on OpenAlex
Mais Alkhalili

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.

venuePublished in a venue whose home country is Canada.
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

VenueIproceedings · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakFood poisoningEnvironmental healthChristian ministryMedicineShigellaContaminated foodGeographySalmonellaBiologyVirologyMicrobiology

Abstract

fetched live from OpenAlex

Background On October 6, 2019, 55 residents of Bala'ama town in Al-Mafraq, Jordan, were admitted to the local health care center with symptoms of food poisoning. Objective This study aimed to identify the cause of the food poisoning outbreak. Methods This descriptive study is a cross-sectional study. Data were obtained from the Directorate of Communicable Diseases in the Ministry of Health. A total of 25 stool samples from patients and an additional 2 samples from workers in the restaurant were collected and tested. An environmental survey of the food and water was also conducted. Results The period of the outbreak was from October 6 to 10, 2019. The highest proportion of patients were children under 5 years of age. More females than males were affected. Stool test results were positive for Shigella sonnei in 15 samples and rotavirus in 7 samples. Chloride concentration was 0 in the water samples. Conclusions The food poisoning outbreak was caused by consumption of hummus from a neighborhood restaurant, which was contaminated with S. sonnei.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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