Hen egg yolk and skinned krill as possible foods for rearing leptocephalus larvae of<i>A</i><i>nguilla japonica</i>Temminck & Schlegel
Bibliographic record
Abstract
Usual diets for rearing leptocephalus larvae of Japanese eel Anguilla japonica include eggs of the endangered spiny dogfish Squalus acanthias (SE). We investigated the effects of alternative food materials, hen egg yolk (HEY) and exoskeleton-free (skinned) Antarctic krill (SAK), on the growth and survival of eel larvae. We found that feed comprising whole krill including exoskeleton (WAK) containing higher levels of fluoride (37.89 mg kg−1) was acutely toxic to eel larvae exposed to this alone. In contrast, extract from SAK containing lower concentrations of fluoride (4.25 mg kg−1) showed no apparent adverse effects. Growth of larvae fed a mixture of SE and SAK in a feed trial of 58 days [mean body weight (BW), 6.0 mg] was about twofold higher than that of larvae fed a mixture of SE and WAK (3.2 mg) (P < 0.01). A mixture of HEY and SAK also had some dietary benefits for eel larvae, enabling them to survive for up to 58 days and to grow significantly (mean BW, 2.4 mg), compared with their initial weight (mean BW, 0.2 mg) (P < 0.001). Although additional nutritional improvements are needed, the present results suggest that combination diet HEY and SAK may be a good alternative to SE as an effective diet for eel larvae.
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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) | 0.001 | 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".