The assessment of population exposure to chlorination by-products: a study on the influence of the water distribution system
Bibliographic record
Abstract
BACKGROUND: The relationship between chlorination by-products (CBPs) in drinking water and human health outcomes has been investigated in many epidemiological studies. In these studies, population exposure assessment to CBPs in drinking water is generally based on available CBP data (e.g., from regulatory monitoring, sampling campaigns specific to study area). Since trihalomethanes (THMs) and haloacetic acids (HAAs) are the most documented CBP classes in drinking water, they are generally used as indicators of CBP exposure. METHODS: In this paper, different approaches to spatially assign available THM and HAA concentrations in drinking water for population exposure assessment purposes are investigated. Six approaches integrating different considerations for spatial variability of CBP occurrence within different distribution systems are compared. For this purpose, a robust CBP database (i.e., high number of sampling locations selected according to system characteristics) corresponding to nine distribution systems was generated. RESULTS AND CONCLUSION: The results demonstrate the high impact of the structure of the distribution system (e.g., presence of intermediary water infrastructures such as re-chlorination stations or reservoirs) and the spatial variability of CBPs in the assigned levels for exposure assessment. Recommendations for improving the exposure assessment to CBPs in epidemiological studies using available CBP data from water utilities are also presented.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".