Spatial and temporal variations of manganese concentrations in drinking water
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.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".