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Potential for pathogen intrusion during pressure transients

2003· article· en· W1537153355 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Water Works Association · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsAmerican Water (Canada)
FundersAmerican Water Works Association Research Foundation
KeywordsColiphageEnvironmental scienceMicroorganismIntrusionClostridium perfringensPotable waterEnvironmental engineeringMicrobiologyBiologyGeologyBacteria

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.207
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it