Coumarin and Safrole Content in Cinnamon-Flavored Food Products on the Syrian Market
Bibliographic record
Abstract
Some plants that are processed into foods often contain natural substances that may be hazardous to human health. One example is coumarin, which is known to cause liver and kidney damage in rats, mice and probably humans. Coumarin is found in different Cinnamomum species such as Cinnamomum cassia, Cinnamomum loureiroi, and Cinnamomum burmannii; all commonly referred to as cassia. Another hazardous substance is Safrole. Safrole is reasonably anticipated to be a human carcinogen based on sufficient evidence of carcinogenicity from studies in experimental animals; and is mainly present in cinnamon leaf oil and could be a possible contaminant in cinnamon powder. European Council’s Directive on food flavourings 88/388/EEC limits safrole in foodstuffs to 1ppm. The content of coumarin is regulated in the European Regulation (EC) No 1334/2008. In the present study, coumarin and safrole levels were analyzed in locally bought cinnamon samples and cinnamon-flavored food products using a validated HPLC method with diode array detector (DAD). Appreciable amounts of coumarin were found in bakery products with concentrations up to 39.466 mg/kg in certain kinds of cookies, whereas safrole was undetectable. Our exposure data on coumarin in bakery products show that there is still a need for a continued regulation of coumarin in foods. A toxicological re-evaluation of coumarin with the aim to derive scientifically founded maximum limits should be conducted with priority.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".