Impact of source waters, disinfectants, seasons and treatment approaches on trihalomethanes in drinking water: a comparison based on the size of municipal systems
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 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.
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 | 0.000 | 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