Turbidity tubes for drinking water quality assessments
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
Turbidity tubes have been considered to be the field method of choice for drinking water quality monitoring in resource-limited contexts because of their relative simplicity and low cost in comparison with conventional (nephelometric) turbidimeters. These tubes utilise the principle of visual extinction of a submerged target for turbidity determination and were therefore thought to be subject to user subjectivity, possibly affecting results. This study evaluated their performance under both field and controlled-laboratory conditions. Results from turbidity tubes can differ substantially from those obtained with conventional turbidimeters; this is of particular importance in the reporting of low turbidity (<10 NTU) measurements. These differences could be due to a combination of factors, such as: user variability, differences in calibration scales, and turbidity tube target shape and background colour. In view of their limitations, the usefulness of turbidity tubes for drinking water quality assessments and recommendations on the reporting of their results are also discussed.
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