Application of Quantitative Microbial Risk Assessment at 17 Canadian Water Treatment Facilities
Bibliographic record
Abstract
A quantitative microbial risk assessment model developed by Health Canada was applied at 17 water treatment plants (WTPs) located throughout Ontario and Quebec, Canada. Four source water characterization methods were compared that considered Escherichia coli , Giardia , and Cryptosporidium . In addition, three strategies to evaluate chemical disinfection performances were compared (median disinfectant exposure [CT 50 ], regulatory disinfectant exposure [CT 10 ], and continuous‐stirred tank reactors in‐series [N‐CSTR, where N is the number of CSTRs in the series]). The N‐CSTR approach provides more reliable risk estimates because it is less sensitive to high inactivation conditions (when compared with use of CT 10 or CT 50 ). Predicted risk estimates for the 17 WTPs revealed that only two did not comply with the 10 –6 disability‐adjusted life years (World Health Organization) and 10 –4 risk of infection (US Environmental Protection Agency) reference levels because of the poor performance of direct filtration without coagulation. This publically available quantitative microbial risk assessment model could help WTP managers assess overall treatment performance via a systematic evaluation process.
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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 | 0.001 |
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".