Effects of dietary supplementation of alga<i>Haematococcus pluvialis</i>(Flotow), synthetic astaxanthin and β-carotene on survival, growth, and pigment distribution of red devil,<i>Cichlasoma citrinellum</i>(Günther)
Bibliographic record
Abstract
Dietary carotenoids of various types and concentration can affect the pigmentation efficiency in an ornamental fish red devil, Cichlasoma citrinellum. Astaxanthin (AX) containing alga Haematococcus pluvialis, a synthetic AX, and a synthetic β-carotene (BC) were supplemented in formulated diets at two concentrations, 80 and 160 mg kg−1, resulting in six pigmented diets. Formulated diet without carotenoids supplementation served as a control. These diets were fed to the fish, for 8 weeks. Astaxanthin dominated in body carotenoids deposition. Dietary BC hardly had contribution to body AX. Control fish had much lower AX content in skin, fin and muscle than fish fed pigmented diets, but had equal AX content in liver, intestine and gonad as those fish. Dietary synthetic AX had equal efficiency in depositing AX in skin and fin as natural AX but higher efficiency in gonad than natural AX. Fish fed AX supplemented at 160 mg kg−1, either natural or synthetic AX, had higher AX content in skin than fish at 80 mg kg−1 but had equal AX content in fin as fish at 80 mg kg−1. Disregarding the treatment effects, the overall average AX content in tissue in descending order was gonad>fin≧(intestine=skin)>liver>muscle.
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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) | 0.000 | 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".