The Application of Single-Cell Ingredients in Aquaculture Feeds—A Review
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
Single-cell ingredients (SCI) are a relatively broad class of materials that encompasses bacterial, fungal (yeast), microalgal-derived products or the combination of all three microbial groups into microbial bioflocs and aggregates. In this review we focus on those dried and processed single-cell organisms used as potential ingredients for aqua-feeds where the microorganisms are considered non-viable and are used primarily to provide protein, lipids or specific nutritional components. Among the SCI, there is a generalised dichotomy in terms of their use as either single-cell protein (SCP) resources or single-cell oil (SCO) resources, with SCO products being those oleaginous products containing 200 g/kg or more of lipids, whereas those products considered as SCP resources tend to contain more than 300 g/kg of protein (on a dry basis). Both SCP and SCO are now widely being used as protein/amino acid sources, omega-3 sources and sources of bioactive molecules in the diets of several species, with the current range of both these ingredient groups being considerable and growing. However, the different array of products becoming available in the market, how they are produced and processed has also resulted in different nutritional qualities in those products. In assessing this variation among the products and the application of the various types of SCI, we have taken the approach of evaluating their use against a set of standardised evaluation criteria based around key nutritional response parameters and how these criteria have been applied against salmonids, shrimp, tilapia and marine fish species.
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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 it