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Record W2312320697 · doi:10.1139/cjce-2014-0037

Assessing the impact of renewal scenarios on the global structural state of sewer pipe networks

2014· article· en· W2312320697 on OpenAlexaffvenueabout
Sophie Duchesne, Kassandra Bouchard, Babacar Toumbou, Jean‐Pierre Villeneuve

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsState (computer science)Civil engineeringComputer scienceEngineeringEnvironmental scienceTransport engineering

Abstract

fetched live from OpenAlex

The first objective of this paper is to demonstrate how mathematical models simulating the structural state of sewer pipes can help to assess the financial resources required for the preservation of sewer networks. The second objective is to assess and compare the annual replacement rate that should be applied to four different Canadian sewer networks to stabilize their global structural state for the long term. The required annual replacement rates are similar for the four studied networks, even if their global structural states were different prior to replacement. Results also show that the required annual replacement rate is three times less if the deterioration states of all pipes in the network are known, as opposed to the case where the structural states are unknown. This demonstrates the importance of sewer pipe inspection for the planning of sewer pipe renewal.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.357

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.202
Teacher spread0.195 · 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 designSimulation or modeling
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

Citations4
Published2014
Admission routes3
Has abstractyes

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