Probabilistic Human Health Risk Assessment for Quarterly Exposure to High Chloroform Concentrations in Drinking-Water Distribution Network of the Province of Quebec, Canada
Bibliographic record
Abstract
Because quarterly concentrations of total trihalomethanes (THM) exceeding the 80 μg/L guideline are often tolerated by the public health authorities of the Province of Quebec (Canada), this study examined whether quarterly episodes of high concentrations of THM may pose a risk to the health of its population. Using Monte Carlo simulations, a probabilistic risk assessment was performed for infants (0-<6 mo), toddlers (6 mo-<5 yr) and adults (≥20 yr). Multiroute exposure including ingestion of drinking water as well as inhalation and dermal exposure while showering or bathing was considered. The resulting absorbed doses were compared to short-term reference values for chloroform, used as surrogate for THM, by calculating risk quotients (RQ). On the basis of THM concentrations values in Quebec's drinking water distribution systems during the months of July to October and exceeding the guideline value (>80 μg/L), the 95th percentile value of RQ were 0.65, 0.46, and 0.24 for infants, toddlers, and adults, respectively. Back-calculation allowed determining that a chloroform concentration of 330 μg/L would result in RQ ≤ 1 for 99% of infants, the subgroup considered the most susceptible among the general population. Overall, this study showed that episodes of high THM concentration encountered in Quebec drinking-water distribution network need not be considered as an immediate health concern for the general population. However, these results should not be interpreted as an authorization to exceed the 80 μg/L standard but rather as a risk management tool for public health authorities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".