CHẤT LƯỢNG NƯỚC TRONG HỆ THỐNG NUÔI CÁ SẶC RẰN (TRICHOGASTER PECTORLIS) THÂM CANH KẾT HỢP VỚI BÈO TAI TƯỢNG (PISTIA STRATIOTES)
Bibliographic record
Abstract
In the traditional earthern pond culture, water in intensive Trichogaster pectorlis Regan pond culture needs to be renewed by flushing out directly to the adjacent canals, leading to degradation of aquatic ecosystem. In order to reuse excessive nutrients, purify pond water and use surface water more effectively, the floating beds of water lettuce (Pistia stratiotes L.) at four coverage ratios of 0, 25, 50 and 75% pond surface area were applied. The concentration of NH4-N in the water body was low in all treatments while TP concentration was higher in the lower coverage ratios of 0 and 25%. Coverage ratios did not affect fish growth except the greatest feeding efficiency in the 25% coverage. During 60 days of experiment, water in the experimental tanks did not require changing, but water quality was remained within a suitable range for normal growth of Snakeskin gourami. Therefore, the study helps to maximize efficiency of water use and utilize nutrients that contributes to protect the environment and to sustainably manage water resource.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".