A Food Poisoning Outbreak in Al-Khazir U2 Camp of Internally Displaced Persons - Iraq, Summer 2017
Bibliographic record
Abstract
Background Globally, about 600 million fall ill and 420,000 die every year after eating contaminated food. On June 12, 2017, Iraq CDC informed about a food poisoning outbreak among internally displaced persons (IDPs) in Al-Khazir camp, Northern Iraq after consuming “Iftar” (Ramadan breakfast) provided by an NGO. “Iftar” was composed of rice, white bean broth, chicken, yogurt, date and bread. Objective The objective was to describe the outbreak, identify the causative agent and recommend preventive measures. Methods A team of FETP residents dispatched to investigate the outbreak. The case patient was defined as any person in the camp who ate “Iftar” and developed nausea/vomiting or diarrhea or abdominal pain. A retrospective cohort study was initiated. Results Conclusions The large number of ordered meals from a single restaurant led to suboptimal food preparation and storage. We recommended rigorous implementation of food handing instructions and health education of the food handlers.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".