The effect of different treatments on the accumulation of histamine in herring and fesikh
Bibliographic record
Abstract
In Egypt, the request for salt fish products has been increasing during many feasts because it is one of Egypt's favorite foods. It has been reported that in certain seasons, these products cause toxicity and even death. Most fish poisonings around the world are known to be caused by elevated histamine levels. Thus, the study assessed the histamine levels of herring and fesikh samples available on the market and established the safety of these products with recommendations for various treatments that may inhibit the production of histamine in herring and fesikh through bacteria and enzyme production. Before manufacturing herring and fesikh, the fresh fish is soaked for one hour in a modified pH solution of 4 by vinegar with the addition of natural substances individually or in combination (such as garlic, onion, hot pepper, or aloe vera) or some chemicals singly (such as edta, nisin, h2o2, formic acid, and so2). The levels of histamine in herring (111 to 138 mg/kg) and fesikh (214 to 279 mg/kg) were unsafe in marketable samples. The histamine levels of herring and fesikh in proposed treatments were safe since they did not exceed 26 mg/kg after 30 days of cold storage for herring or 45 mg/kg after maturity of fesikh. The proposed treatments enhanced greatly herring and fesikh organoleptic qualities, especially those containing natural ingredients, such as garlic, hot pepper, or their mixture beside onion, which are more accepted treatments.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".