An investigation of bacteriological and chemical water quality and the barriers to private well water sampling in a Southwestern Ontario Community
Bibliographic record
Abstract
Private well owners in Canada are responsible for maintenance, including routine sampling, of their private drinking water supply. Sampling rates in a Southern Ontario community are well below the public health recommendation. A study with private well owners was conducted to improve private well water sampling rates through the removal of two significant barriers to private well water testing.During the pilot and extended study phases, 549 nitrate and 425 bacteriological water sampling bottles were delivered to private well owners and water samples were collected the following day. A follow-up telephone survey was conducted with both study participants and non-participants to identify barriers to private water sampling that were encountered by the study sample population.Participation rates in the pilot and extended study phases were less than 50% prompting the follow-up telephone survey. Inconvenience and lack of time [statistically significant, P < 0.01] were found to be the main barriers for participation in the study.The findings from this study illustrate the influence that certain barriers have on the frequency of private well water testing in a Southern Ontario community. The findings provide guidance for other health authorities to improve sampling rates.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".