Peat Water Treatment Using Combination of Cationic Surfactant Modified Zeolite, Granular Activated Carbon, and Limestone
Bibliographic record
Abstract
This research was conducted essentially to treat fresh peat water using a series of adsorbents. Initially, the characterization of peat water was determined and five parameters, including pH, colour, COD, turbidity, and iron ion exhibited values that exceeded the water standard limit. There were two factors influencing the adsorption capacity such as pH, and adsorbent dosages that were observed in the batch study. The results obtained indicated that the majority of the adsorbents were very efficient in removing colour, COD, turbidity at pH range 2-4 and Fe at pH range 6-8. The optimum dosage of cationic surfactant modified zeolite (CSMZ) was found around 2 g while granular activated carbon (GAC) was exhibited at 2.5 g. In column study, serial sequence of CSMZ, GAC, and limestone showed that the optimal reduction on the 48 hours treatment were found pH = 7.78, colour = 12 TCU, turbidity = 0.23 NTU, COD = 0 mg/L, and Fe= 0.11 mg/L. Freundlich isotherm model was obtained for the best description on the adsorption mechanisms of all adsorbents.
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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".