Development of Source and Treated Water Quality Indicators for drinking water in Canada from conceptual design to methodological development
Bibliographic record
Abstract
In September 2005, Health Canada took on the development of a Source Water Quality Indicator for Canada. The main objective was to develop a methodology by which source water quality could be linked to public health, the environment, society, and economy; and measured, tracked, and reported in the form of an indicator for decision making. A Treated Water Quality Indicator was also introduced to bridge the gap between source water quality and human health. With Federal/Provincial/Territorial and academic support, research into the approach and development of a conceptual design, parameter selection rationale, and two tools for the indicator calculations, along with recommendations for future work were completed. The tools developed included a modified Canadian Council of Ministers of the Environment water quality index calculator, and a Treatability Ranking tool (that determined the complexity of treatment required to achieve safe drinking water). The results of this project are described herein.
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.
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 | 0.175 | 0.159 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".