Factors Influencing Formation of Trihalomethanes in Drinking Water: Results from Multivariate Statistical Investigation of the Ontario Drinking Water Surveillance Program Database
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 The presence of trihalomethanes (THMs) in drinking water is an important issue in the context of their potential health effects. Numerous studies have developed models in the past three decades relating THMs concentrations to different factors (e.g., dissolved organic carbon [DOC], chlorine dose, pH, etc.). Previous studies characterized the importance of specific factors through controlled studies using synthetic water or source waters from a small number of water treatment plants. Few studies have reported looking for factors related to THMs formation system-wide across many different water supply systems, and in environments where many factors vary simultaneously. This study presents the results of a multivariate statistical analysis for 162 water supply systems in Ontario, Canada for 2000 to 2004. Principal component analysis (PCA) was applied to determine important factors and possible clusters of variation. PCA identified DOC, chlorine dose, pH, temperature, and reaction time as significant factors for THMs formation. Separate clusters were observed for DOC-colour; chlorine dose-total/free residual chlorine; and hardness-alkalinity. Each cluster indicated factors varying together and representing significant variation. Temperature and pH were found significant and uncorrelated throughout the analysis. The multivariate analysis is the first phase of a continuing investigation into THMs formation with the ultimate goal of developing a predictive model, which can be used to perform human health risk-cost balance studies for drinking water quality management.
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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 | 0.005 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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