Drinking water quality for peri-urban residents in Phnom Penh, Cambodia
Bibliographic record
Abstract
Piped distribution systems are limited to major urban centres in Cambodia, leaving the residents of peri-urban communities to rely on a variety of surface, rain and groundwater sources for their drinking water supplies. This paper examines microbial water quality results from two of Phnom Penh's peri-urban communities, and describes relationships between water source and treatment type, study site and storage vessel, relative to water quality guidelines. Treating water by boiling was a common practice, although the majority of residents indicated using boiling times far greater than required, which may impact adoption rates. A statistical difference is described between boiled water by source type, with boiled shallow well water having elevated E. coli levels. The only household drinking water type that met WHO guidelines most of the time was boiled rain or tank (vendor) water (56%); boiled rain or tank (vendor) water stored in a kettle, bucket/cooler or bucket with spigot met guideline values 69, 43 and 60% of the time, respectively. The highest quality water is from boiled rain or tank (vendor) water taken directly from a kettle. The findings described provide some insight on how to prioritize water options for various uses.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".