Efficacy of Annual Bacteria Monitoring and Shock Chlorination in Wells Finished in a Floodplain Aquifer
Bibliographic record
Abstract
Abstract Public health authorities generally recommend annual water‐quality monitoring of rural water wells and shock chlorination if coliforms are detected. It is implicitly assumed that shock chlorination is effective in ridding most wells of bacteriological pathogens for months to years. Neither annual monitoring nor shock chlorination was effective in addressing coliform contamination of selected water wells in a small town developed on an alluvial aquifer where septic system effluents are impacting well water quality. Considerable temporal variation in total and fecal coliforms was observed in water wells monitored for a six‐month period. Individual wells intermittently met and exceeded the drinking water criteria, indicating annual sampling was insufficient. Shock chlorination of three contaminated wells and their associated distribution systems proved ineffective because colonies apparently originated from outside the wells and reappeared over relatively short time periods (ranging from less than one week up to 21 weeks). The relatively fast and similar rate of recovery of total heterotrophic bacteria suggested they are related to biofilm formation in the wells and not to ground water contamination.
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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 | 0.002 |
| 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 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".