Optimizing the solar water disinfection (SODIS) method by decreasing turbidity with NaCl
Bibliographic record
Abstract
Solar water disinfection (SODIS) has proven to be effective at reducing diarrheal incidence in epidemiological intervention studies. However, the SODIS method is limited to waters of low turbidity (<30 NTU). This study investigates the use of common table salt (NaCl) to reduce the turbidity of water containing suspended colloidal clay particles for use in the SODIS method. Three representative clays found in tropical soils (kaolinite, illite and bentonite) were tested at three levels of turbidity (50, 100 and 200 NTU) for their flocculating behavior with multiple NaCl concentrations to find the optimum. Supernatants were tested for sodium concentration for comparison against health and taste thresholds. Results show that unlike kaolinite and illite, pure bentonite solutions were shown to be very responsive to NaCl and produced supernatants with as low as 4 NTU (98% particle removal efficiency). This study has shown that NaCl, in combination with high-activity clay particles in solution, may effectively reduce turbidity to levels suitable for SODIS treatment, thereby expanding the number of people who can utilize the technology effectively.
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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 | 0.001 |
| 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 | 0.001 | 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".