ACM Check Dams in Concrete Gutters for Recirculation Filters of Wastewater from Whiteleg Shrimp (Litopenaeus vannamei) Aquaculture in Southern Thailand
Bibliographic record
Abstract
Theresearch was aimed to recirculate the treated wastewater from Whiteleg shrimpfarms in following each other without interruptionby using concrete gutters containing ACM (Assembled ConstructedMaterials) check dams as the filters. Among the 2-inch diameter ofchipped-assembled-constructed materials, the ACM-Brick filterwas the most effective rather thanroof-tile, blocked cement, and rock, respectively. Three ACM-Brick check damswith 5-m space between them were indicated as 47.3 % treatment efficiencytogether with flow rates of 600 to 900 L/hr, and up to more 65 % and 85 % forfourth and fifth ACM-Brick checkdams while the first and second dams found13.0 % to 28.4 % efficiencies. Seemingly, irrespectiveof employing brick, roof-tile, blocked cement, or rock for constructing the ACM check dam was installedin concrete gutters with the size of 1-mwidth, 0.5-m depth, and more or less 20-m length that could be served needs inrecirculation aquaculture of Whitelegshrimps to gain satisfied benefits.Culturing Whiteleg shrimps in 3-sq.m. and 3-cu.m.concrete gutterscontaining only one of 0.5-sq.m. and 1-depth ACM-Brick filters by RCB design for 4 treatments (culturing shrimpdensities) and 3 replications found the density of 105 juveniles/3m2(6,606 kg/ha) with the most harvested-added weight 2,710 kg/ha (69.55 % of beginning weight), anddecreasing after increasing the density of 6,720, 8,371, and 11,382 kg/ha incorresponding to harvested-added weight 65.29 %, 46.36 %, and 42.33 %,respectively. The findings also informed that flow rate of 720 L/hr indicatedsomewhat high effective influences ondecreasing of water temperature, salinity, pH, DO, EC, alkalinity, TDS, BOD, NH4-N,NO2-N, and NO3-N which were conditioned for recirculationaquaculture of Whiteleg shrimps.
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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".