Determination of Carcinogenic Polycyclic Aromatic Hydrocarbons (PAHs), Aflatoxins, and Nitrosamines in Processed Fish from the Winam Gulf Area of Kenya and Estimated Potential Exposure in Human
Bibliographic record
Abstract
PAHs, aflatoxins and nitrosamines were analyzed in fish samples obtained from various markets and locations within the Winam Gulf area and processed by various methods often used in Kenya. The mean concentrations of total PAHs (TPAHs) in the smoked, charcoal-grilled and fresh tilapia muscle samples ranged from 22.27–44.58, 20.36–28.51, and 11.43–16.53 μg/kg wet weight, respectively. The concentrations of individual PAHs decreased in the order smoked>charcoal-grilled>fresh fish. Of the USEPA 16 PAHs, benzo(a)pyrene, dibenzo(a,h)anthracene, indeno(1,2,3-cd)pyrene, and benzo(g,h,i)perylene were not detected in all samples analyzed. Fluoranthene, acenaphthene, anthracene, phenanthrene, and acenaphthylene were not detected in fresh tilapia muscles but were generated in significant amounts on the samples during smoking and charcoal-grilling. The risk of exposure to human was estimated to be 0.67 μg/day through consumption of tilapia. The TPAHs levels in fresh fish, smoked and grilled tilapia were higher than the maximum allowable concentrations as per the WHO standards. Aflatoxins were found to be generated in sun-dried Dagaa during handling and storage with total mean concentrations ranging from 0.33–1.58 μg/kg wet weight but none were detected in the fresh samples. The daily intake of aflatoxins through consumption of Dagaa was estimated to be 0.0079 μg/day during the rainy season when the drying process is less efficient. None of the nitrosamines were detected in both fresh and the deep-fried tilapia muscle samples (frying temperatures ranging from 110–170°C) after exposure to nitrites and nitrates in water, in concentrations ranging up to 10 μg/L (NO2−) and up to 160 μg/L (NO3−).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".