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Record W2789076055 · doi:10.3390/su10020517

The Sustainability of Concrete in Sewer Tunnel—A Narrative Review of Acid Corrosion in the City of Edmonton, Canada

2018· article· en· W2789076055 on OpenAlex
Linping Wu, Chaoshi Hu, Wei Victor Liu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSustainability · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversity of Alberta
FundersCity of EdmontonNatural Sciences and Engineering Research Council of Canada
KeywordsSustainabilityCivil engineeringCorrosionDrainageEngineeringPervious concreteDesign elements and principlesNarrative reviewEnvironmental scienceGeotechnical engineeringEnvironmental engineeringCementMaterials scienceMetallurgyEcology

Abstract

fetched live from OpenAlex

This paper is intended to conduct a narrative review on the acid corrosion of sewer tunnel concrete in the City of Edmonton—an investigation on the MIC (microbially induced corrosion) mechanism and the potential control methods to improve the sustainability of concrete. Firstly, three categories of main influencing factors were identified for the rate of MIC: hydraulic parameters, environmental factors, and concrete mixture design. Secondly, it is found that the sewer tunnel design plays an essential role in the control of the MIC. Building on that, a review was conducted on eight municipal drainage design standards in consideration of the MIC, indicating a lack of design standards of the flow velocity and pipe material. Finally, an investigation was done for cement-based rehabilitating techniques and materials.

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.

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)0.003
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.265
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