Differences in laboratory versus field treatment performance of point-of-use drinking water treatment methods: research gaps and ways forward
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
Abstract In this Perspective, we present evidence that indicates a discrepancy between laboratory and field performance of point of use water treatment (POUWT) techniques, identified via a narrative review process to investigate the origin of the LRV comparison estimates reported by the WHO. We considered only peer-reviewed articles that reported laboratory and field log reduction values (LRVs) for the same POU technology. We will present a summary of explanations that have been offered by the literature regarding such discrepancies; the potential implications of the “laboratory versus field” data discrepancy; and potential risks posed by conflating the two. Finally, in view of this discussion, we propose a strategy to help mitigate the research gap and explore the potential to improve current health risk assessments and ultimately, recommendations by public health entities and manufacturers of POUWT products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it