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Record W4413135294 · doi:10.1061/9780784486375.017

From Inception to Completion—Rehabilitation of Large Non-Circular Combined Sewers in Winnipeg, Manitoba

2025· article· en· W4413135294 on OpenAlexaffabout
Adam Braun, Nathan Kehler, Stacy Cournoyer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsUniversity of WinnipegStantec (Canada)
Fundersnot available
KeywordsSanitary sewerRehabilitationComputer scienceEngineeringMedicinePhysical therapyEnvironmental engineering

Abstract

fetched live from OpenAlex

This paper details the rehabilitation of five large non-circular combined sewers in Winnipeg, Manitoba, Canada. The project is part of the City of Winnipeg’s annual sewer rehabilitation program and includes egg-shaped sewers ranging in size from 2,060 × 1,625 to 2,950 × 1,950 mm. With multiple rehabilitation technologies on the market, the preliminary design process focused on evaluating applicable rehabilitation methods. Considerations included the existing sewer geometry, liner constructability, construction risk, liner structural performance, and an evolving approach to liner design in the market. The project faced many obstacles during design and construction, including construction on leased City and railway property, construction on busy regional streets, and COVID-19-related shipping delays. This paper takes readers through the entirety of the project from preliminary design to the completion of construction. There is a focus on technology selection, risk reduction, tendering rehabilitation work utilizing the new ASCE MOP 145, and construction. The latter will focus on lessons learned, stakeholder engagement, ongoing risk reduction efforts, and dealing with a volatile post-pandemic global market. The intent is to demonstrate a holistic approach to large-diameter sewer rehabilitation, which is employed from inception to completion.

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)0.000
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 score0.151
Threshold uncertainty score0.454

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 head0.003
GPT teacher head0.220
Teacher spread0.217 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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