Optimization of Essential Fatty Acids Via Esterification of the Native North Sumatera’s Freshwater Fish
Bibliographic record
Abstract
Nutritionally balanced diets required animal proteins which are obtained in both marine fish and freshwater fish.Chemical constituents obtained in freshwater fish are especially high in protein and rich in healthy lipids.Polyunsaturated fatty acids (PUFA), the essential fatty acids, for example, are responsible for central nervous system function, play important roles in inflammatory responses and immune system, significant for structural components of cell membranes, and heredity.Indonesia is known as one of Asia's greatest freshwater fish producers, and North Sumatera, a part of Indonesia's mainland, is one of the biggest in the country.Cyprinus carpio and Indonesian snakehead fish (Channa striata) are common freshwater products consumed in daily life and in the traditional ceremonies of the biggest population called Bataknese.The results showed that for saturated fatty acid (SFA), palmitic acid (C16:0) was dominant for goldfish and snakehead fish, which are about 31.8% and 42.7%, respectively.In addition, oleic acid (C18:1) was the largest monounsaturated fatty acid (MUFA), more than 45% for goldfish and around 26% for snakehead fish.In contrast, docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) of PUFA are found to be higher in snakehead fish oil than in goldfish, which indicates a rich amount of nutrients.Furthermore, the fatty acid distributions are more in the sn-2 position in both goldfish and snakehead fish.The fatty acids content and distribution in this study were determined by enzymatic hydrolysis of extracted fish oil followed by esterification.The individual percentage of fatty acid was quantified using Gas Chromatography-Flame Ionization Detector (GC-FID).
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 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 | 0.000 | 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) | 0.001 | 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".