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Record W3189838737 · doi:10.1061/9780784483626.009

Challenging Rehabilitation of a Trunk Sewer Using Sprayed Geopolymer Lining in Ontario

2021· article· en· W3189838737 on OpenAlexaffabout
Paul Headland, Joseph R. Royer, Glenn MacIntosh, Vin Servera

Bibliographic record

VenuePipelines 2021 · 2021
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsRegional Municipality of Durham
Fundersnot available
KeywordsSanitary sewerRehabilitationWaterproofingEnvironmental scienceCivil engineeringEngineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

The 16th Avenue Sanitary Trunk Sewer Rehabilitation project comprises rehabilitation of a partially deteriorated sewer located in Markham, Ontario. This 3.0-km section of 2.6-m inner diameter trunk sewer tunnel is located at depths ranging between 35 and 47 m below ground surface. Based upon the results of a Pilot Study, the Regional Municipality of York (York Region) proceeded with the full rehabilitation using sprayed geopolymer as the permanent structural sewer lining. Numerous challenges were anticipated and encountered during construction including installing key bypass system components at depths of 47 m, sewer waterproofing with groundwater heads of 45 m, and considerations for optimal geopolymer spray application. An important lesson learned was that it is essential for infiltration to be adequately controlled for the geopolymer to be applied to a substrate free of flowing water to achieve sewer lining rehabilitation with adequate long-term performance. The first 1.5 km of the planned 3.0 km of sewer rehabilitation on 16th Avenue was completed in October 2019 and an inspection was conducted after 6 months in-service (March 2020) showing that the lining was performing as designed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.266
Teacher spread0.239 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

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