Potential for pathogen intrusion during pressure transients
Bibliographic record
Abstract
Pressure transients in drinking water pipelines (i.e., surges) may cause hydraulic pressure gradients, resulting in the potential for intrusion of pathogens present in the external environment into the distribution system. The objectives of this study were to determine the occurrence of indicator microorganisms and pathogens in the vicinity of potable water pipelines and assess the potential for intrusion attributable to transient distribution system pressure changes. As part of an earlier study ( Kirmeyer et al, 2001 ), soil and water samples were collected at sites immediately exterior to drinking water pipelines at eight locations in six states. Samples were then tested for occurrence of total and fecal coliforms, Clostridium perfringens, Bacillus subtilis , coliphage, and enteric viruses. Indicator microorganisms and enteric viruses were detected in more than 50% of the samples examined. Monitoring of pressure transients at a large distribution system indicated that pressure transients occurred frequently, although negative pressures were detected on only one occasion. The results of this study suggest that during negative‐ or low‐pressure events, microorganisms may enter the treated drinking water through pipeline leaks.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".