Emerging Role of Phenolic Compounds as Natural Food Additives in Fish and Fish Products
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
Chemical and microbiological deteriorations are principal causes of quality loss of fish and fish products during handling, processing, and storage. Development of rancid odor and unpleasant flavor, changes of color and texture as well as lowering nutritional value in fish can be prevented by appropriate use of additives. Due to the potential health hazards of synthetic additives, natural products, especially antioxidants and antimicrobial agents, have been intensively examined as safe alternatives to synthetic compounds. Polyphenols (PP) are the natural antioxidants prevalent in fruits, vegetables, beverages (tea, wine, juices), plants, seaweeds, and some herbs and show antioxidative and antimicrobial activities in different fish and fish products. The use of phenolic compounds also appears to be a good alternative for sulphiting agent for retarding melanosis in crustaceans. Phenolic compounds have also been successfully employed as the processing aid for texture modification of fish mince and surimi. Thus, plant polyphenolic compounds can serve as potential additives for preventing quality deterioration or to retain the quality of fish and fish products.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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