Microbiological Effectiveness and Cost of Disinfecting Water by Boiling in Semi-urban India
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite shortcomings, boiling is the most common means of treating water at home and the benchmark against which emerging point-of-use water treatment approaches are measured. In a 5-month study, we assessed the microbiological effectiveness and cost of the practice among 218 self-reported boilers relying on unprotected water supplies. Boiling was associated with a 99% reduction in geometric mean fecal coliforms (FCs; P < 0.001). Despite high levels of fecal contamination in source water, 59.6% of stored drinking water samples from self-reported boilers met the World Health Organization standard for safe drinking water (0 FC/100 mL), and 5.7% were between 1 and 10 FC/100 mL. Nevertheless, 40.4% of stored drinking water samples were positive for FCs, with 25.1% exceeding 100 FC/100 mL. The estimated monthly fuel cost for boiling was INR 43.8 (US$0.88) for households using liquid petroleum gas and INR 34.7 (US$0.69) for households using wood.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it