Proteolytic processing of herring (<i>Clupea harengus</i>): biochemical and nutritional characterisation of hydrolysates
Bibliographic record
Abstract
Summary Food research on fish has demonstrated that they constitute excellent nutritional components. The aim of the present work, was to process herring ( Clupea harengus ) using Protamex ® and evaluate the distribution of nutrients in various fractions obtained following membrane filtration. The fish starting material was composed of approximately 88% water and the dry matter contained 59% crude proteins, 33% lipids and 5% minerals. The recovery of fish dry matter in the liquid hydrolysate was 67.8%. Most protein enriched fractions demonstrate a well‐balanced amino acid composition, notably the most essential amino acids. These protein fractions are characterised by biomolecules having a relatively low molecular weight (45 kDa and less) range. Even though the process could be optimised, the biochemical and nutritional analyses indicate that the herring may serve as high‐value products for future applications in the health and food sectors.
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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 | 0.001 |
| 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".