Assessment of water quality in distribution networks through the lens of disinfection by-product rules
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
Disinfection with chlorine is a common practice to ensure secured drinking water, but results in potentially harmful disinfection by-products (DBPs), when excess chlorination is done. The US Environmental Protection Agency (US EPA) has established Stage 1 and Stage 2 disinfection by-product Rules (DBP rules) to control DBP exposure. A modified version of the Canadian Council of Ministries of the Environment water quality index (CCME WQI) is used to assess water quality. CCME WQI is a globally accepted index to assess water quality, but is too generic to be used for DBP rules. The study developed a scheme to make the index suitable for DBP rules. A scoring method based on an analytic hierarchy process (AHP) is applied to assign weights based on DBP rules. A previously modified CCME WQI (Islam et al., 2014) is adapted along with the weights to perform the assessment at the distribution network (DN). A case study was performed on 7 sampling stations in a Québec City DN. The spatial water quality variations are presented using kriging – a geostatistical method, which identifies the regions with relatively poor water quality and highlights the potential locations for re-chlorination points. The proposed assessment formulation is flexible to handle situations with limited data, which makes it especially suited to smaller municipalities.Keywords: CCME water quality index, Stage 1 DBP Rule, Stage 2 DBP Rule, chlorination
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