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Record W3189509551 · doi:10.1061/9780784483626.049

Structural Renewal of a 60 in. Potable Water Transmission Main Using CFRP for New Jersey American Water

2021· article· en· W3189509551 on OpenAlexaff
R. Conklin, Edward P. Gajek, Dave Caughlin, Michael Wolan, Rasko P. Ojdrovic, Jeff Molesko

Bibliographic record

VenuePipelines 2021 · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsAmerican Water (Canada)
Fundersnot available
KeywordsPotable waterPipeline transportPipeline (software)RehabilitationWater pipeEnvironmental scienceCivil engineeringReliability (semiconductor)Forensic engineeringEngineeringEnvironmental engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The South Plainfield 60-in. water transmission main is owned and operated by New Jersey American Water. This 60-in. prestressed concrete cylinder pipe (PCCP) water transmission main is a critical New Jersey American Water asset that provides service to nearly one million residential, commercial, and industrial customers. The line had a history of issues and replacement or renewal was required in order to reestablish the structural integrity of the line and provide for continued assurance of its future operational reliability. Various replacement and rehabilitation options were considered, with pipeline renewal using carbon fiber reinforced polymer (CFRP) ultimately being selected. The rehabilitation project began in the fall of 2019 and was completed in the spring of 2020. It consisted of the stand-alone rehabilitation of approximately 3,410 linear feet of 60-in. PCCP and ductile iron pipe (DIP). Currently, the project is the longest run of large-diameter potable water pipe renewal utilizing CFRP lining in the country.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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