Exploring the relationships between small non-community drinking water system characteristics and water system performance in Ontario, Canada
Bibliographic record
Abstract
The objectives of this work were to investigate the relationships between characteristics of small non-community drinking water systems (SDWSs) and the performance of these systems with respect to Escherichia coli testing and risk ratings. Ontario-wide SDWS data were analysed using regression models with outcomes of (1) having an adverse E. coli test result in the 12 months prior to the last inspection and (2) the SDWS risk rating (high/medium vs. low risk) that is assigned by public health inspectors. Almost 34% (2,364/7,003) of SDWSs did not utilize treatment, more commonly for ground water than surface supplies (P < 0.001). The odds of having a positive E. coli test result were greater in systems using ground water with treatment (OR = 2.00; 95% CI 1.23-3.24) and surface water with treatment (OR = 1.97; 95% CI 1.05-3.71) compared to ground water with no treatment. The odds of having a water system rated high or medium compared to low risk was greater if the water system operated seasonally (OR = 1.36; 95% CI 1.17-1.59), had an adverse E. coli test result (OR = 1.66; 95% CI 1.09-2.53), and in specific facility types. This research helps to inform existing training opportunities available to SDWS operators in Ontario, and to better standardize the SDWS risk assessment 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 | 0.002 | 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 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".