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Record W1991905673 · doi:10.1021/es901988y

Pressure Monitoring and Characterization of External Sources of Contamination at the Site of the Payment Drinking Water Epidemiological Studies

2009· article· en· W1991905673 on OpenAlexafffund
M. Besner, Romain Broséus, Jean Lavoie, George di Giovanni, Pierre Payment, Michèle Prévost

Bibliographic record

VenueEnvironmental Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsPolytechnique MontréalInstitut National de la Recherche ScientifiqueNatural Sciences and Engineering Research Council of Canada
FundersPolytechnique MontréalNatural Sciences and Engineering Research Council of CanadaTexas AgriLife Research
KeywordsContaminationEnvironmental scienceWater qualityEnvironmental engineeringIntrusionPopulationFecal coliformEnvironmental healthGeologyMedicineEcologyBiology

Abstract

fetched live from OpenAlex

The 1990s epidemiological studies by Payment and colleagues suggested that an increase in gastrointestinal illnesses observed in the population consuming tap water from a system meeting all water quality regulations might be associated with distribution system deficiencies. In the current study, the vulnerability of this distribution system to microbial intrusion was assessed by characterizing potential sources of contamination near pipelines and monitoring the frequency and magnitude of negative pressures. Bacterial indicators of fecal contamination were recovered more frequently in the water from flooded air-valve vaults than in the soil or water from pipe trenches. The level of fecal contamination in these various sources was more similar to levels from river water rather than wastewater. Because of its configuration, this distribution system is vulnerable to negative pressures when pressure values out of the treatment plant reach or drop below 172 kPa (25 psi), which occurred nine times during a monitoring period of 17 months. The results from this investigation suggest that this distribution system is vulnerable to contamination by intrusion. Comparison of the frequency of occurrence of negative pressure events and repair rates with data from other distribution systems suggests that the system studied by Payment and colleagues is not atypical.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.016
GPT teacher head0.253
Teacher spread0.238 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2009
Admission routes2
Has abstractyes

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