Seal blubber oil and its long-chain polyunsaturated fatty acids: processing technologies and applications
Bibliographic record
Abstract
Marine oils originate from the body of fatty fish such as herring and menhaden and the liver of white lean fish such as cod and halibut as well as blubber of marine mammals such as seal and whale. The blubber of harp seal (Phoca groeniandica) is a rich source of polyunsaturated fatty acids (PUFA). In addition to eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) that are found in fish oils, seal blubber oil (SBO) also contains approximately 5% docosapentaenoic acid (DPA). The dominance of PUFA in the triacyiglycerols (TAG) of SBO is in the sn-1 and sn-3 positions as opposed to the sn-2 position in fish oils. These differences would undoubtedly affect the properties of SBO and influence its assimilation into the body. Concentrates of SBO PUFA with dominance of different fatty acids were prepared and their application in production of structured lipids attempted. The oxidative stability of TAG was superior to that of their simple alkyl esters. Nutraceutical and food application of SBO has also been accomplished with special consideration of oxidative stability of 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.
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 | 0.001 |
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".