Traditional Fermented Foods of North African Countries: Technology and Food Safety Challenges With Regard to Microbiological Risks
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.
Bibliographic record
Abstract
Abstract North African countries have a rich tradition in food technology, and many traditional foods of animal or plant origin are still widely consumed and highly appreciated. In fact, these foods play an important role in the economy and food security in these countries. Yet, they are still mainly prepared at the household level under poor sanitary conditions and marketed through informal routes. They thus remain beyond any official control for their compliance to national regulatory standards. Therefore, their consumption is anticipated to put the public health at risk, although such risk has never been estimated on a scientific basis due to the lack of consumption patterns, epidemiological data, and appropriate surveillance programs. The scarcity of scientific studies on the incidence of hazards in this specific category of foods adds to the difficulties in conducting scientifically sound risk assessment or profiling studies. This review provides a brief description of technologies of the most popular traditional foods of animal and plant origin in North Africa and discusses the potential microbiological risks associated with their consumption and the food safety challenges that they raise. The review also aims to draw the attention of stakeholders including decision makers in North African countries to the imperious need to assess or profile the health risks associated with their consumption, and consequently, take the necessary measures to reduce such risks. A tentative risk profiling of selected traditional North African foods is presented using as a template the “risk categorization model for food retail/food service establishments” developed by Health Canada.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it