Comparative Evaluation of Moringa Oleifera, Vicia Faba, and Abelmoschus Esculentus as Natural Coagulants for Turbidity Removal in Water Treatment
Bibliographic record
Abstract
This study researched the use of plant-based coagulants instead of chemical coagulants.The research methodology relies on removing turbidity with natural additives.The results of the current study showed the possibility of replacing chemical coagulants with natural ones.The benefit of that in removing turbidity is that they are safer ad lower in cost, water sample was taken from river, the jar test was used to show the percentage of removal.The results showed the possibility of removing turbidity by up to 80% using the Moringa oleifera and Vicia faba plants, at a dose of 100 mg/L, and the sedimentation time was studied, which showed that 50% of the turbidity was removed within the first 5 minutes using natural coagulation.However, the Vicia faba showed better results than Moringa oleifera in the initial sedimentation of turbidity removed, these results could be due to the high percentage of protein found in Vicia faba.The results of treatment using Abelmoschus esculentus plant were promising, where 78% of the turbidity was removed at a dose of 100 mg/L, however it requires a longer sedimentation time.The results of this study are promising results that gives hope to using natural coagulation instead of chemical coagulation which reduces the negative side effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".