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Record W989835227

Evaluating impacts of changing drinking water regulations on distribution infrastructure integrity - a conceptual framework

2006· article· en· W989835227 on OpenAlexfundvenueno aff
Syed Imran, Rehan Sadiq, Yehuda Kleiner

Bibliographic record

VenueNPARC · 2006
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAmerican Water Works Association Research Foundation
KeywordsBusinessDistribution (mathematics)Environmental planningEnvironmental resource managementWater infrastructureEnvironmental scienceWater resource managementWater supplyEnvironmental engineering
DOInot available

Abstract

fetched live from OpenAlex

The drinking water distribution infrastructure is a network of pipes composed of different materials, of different ages and states of repair and subject to varying environments and stresses. Often newer drinking water regulations may require a change in the water-sources, treatment processes and/or practices. The distribution system is at the receiving end of these changes. It is understood from general principles, that any change in the quality of the transported water can adversely affect the distribution system components.Relating changes in treatment practices to distribution infrastructure integrity is complicated by a number of inter-related processes taking place within the distribution system. This paper elaborates a conceptual framework for evaluating the impact of changes in treatment practices on the long-term structural and functional integrity of the distribution infrastructure. The proposed conceptual framework can be used to identify potential problems in the distribution infrastructure that are associated with the changing water treatment practices.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.011
Scholarly communication0.0100.009
Open science0.0020.006
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.038
GPT teacher head0.296
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2006
Admission routes2
Has abstractyes

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