Estimation of live food consumption for Hippocampus barbouri and Hippocampus kuda
Bibliographic record
Abstract
Seahorse is found worldwide in marine habitats such as the seagrass beds, coral reefs, mangroves and estuaries. Hippocampus barbouri and Hippocampus kuda are among the most traded seahorse species. In recent year, worldwide attention strongly support the establishment of seahorse aquaculture as to provide an alternative source of seahorse. However, the main bottleneck in succeeding seahorse aquaculture were problems faced in the culture of early stage juvenile, specifically the diet. The selection of suitable diet will contribute to the breeding success and larval rearing of seahorse. In this study the consumption of live food by new born, juvenile and adult seahorse were being investigated. H. barbouri and H. kuda commenced feeding at birth. The used of live food, namely the newly hatched Artemia nauplii was able support the growth and survival of new born and juvenile seahorses in specific tank systems. The results shows an increasing trend in which the increased of seahorse age and size (height), increases the average numbers of Artemia nauplii consumed. The minimum numbers of nauplii consumed by H. barbouri and H. kuda at 3 DAB with height 14.24±0.14 mm and 10.71±0.13 mm, were only 7 and 5 nauplii per feeding respectively. This study showed that Artemia nauplii can be used as live food for H. barbouri newborn stage to 28 DAB, while from newborn to 42 DAB for H. kuda. As for late juvenile stage of H. barbouri, at 90 DAB onwards, the used of adult Artemia instead of nauplii is highly recommended.
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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 | 0.001 | 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".