Spatial and temporal variations of manganese concentrations in drinking water
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
The objective of this study was to assess the variability of manganese concentrations in drinking water (daily, seasonal, spatial) for eight communities who participated in an epidemiological study on neurotoxic effects associated with exposure to manganese in drinking water. We also assessed the performance of residential point-of-use and point-of-entry devices (POE) for reducing manganese concentrations in water. While the total Mn concentrations measured during this study were highly variable depending on the location (< 1-2,700 μg/L), daily or seasonal variations were minimal. Flushing the tap for 5 minutes did not significantly reduce total manganese concentration for 4 out of 5 sampling locations. The efficiency of reverse osmosis and ion exchange for total Mn removal was consistently high while activated carbon provided variable results. The four POE greensand filters investigated all increased (29 to 199%) manganese concentration, indicating deficient operation and/or maintenance practices. Manganese concentrations in the distribution system were equal or lower than at the inlet, indicating that sampling at the inlet of the distribution system is conservative. The decline in total Mn concentration was linked to higher water residence time in the distribution system.
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