Impact of source waters, disinfectants, seasons and treatment approaches on trihalomethanes in drinking water: a comparison based on the size of municipal systems
Bibliographic record
Abstract
Abstract This study compares concentrations of trihalomethanes ( THM s) in municipal water for 2001–2007 from the small and large systems in two provinces in C anada ( N ewfoundland and Q uebec) based on source waters, disinfectants, seasons and treatment approaches. Approximately 71 and 94%, respectively, of the municipal systems in Quebec and Newfoundland are small systems (serving fewer than 3000 people). The small systems serve approximately 8.6% (0.57 million) and 44.1% (0.18 million) of the populations in Quebec and Newfoundland, respectively. Concentrations of THM s and its variability are much higher in the small systems (Quebec: 0–941 μg/L; Newfoundland: 0–875 μg/L) than in the systems with populations 10 000 or more (Quebec: 0–364 μg/L; Newfoundland: 2.3–205 μg/L). The study reveals that the differences in THM s between the small and medium/large systems are because of different types of source waters, treatments, disinfection strategies and seasons. The results emphasize that regulatory agencies must focus more on the occurrence of DBP s in small systems and identify strategies to reduce their levels in drinking water.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".