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Record W2797133209 · doi:10.1080/23311916.2018.1463594

Evaluation of testing methods for tracking CIPP liners’ life-cycle performance

2018· article· en· W2797133209 on OpenAlex

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.

Bibliographic record

VenueCogent Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsStantec (Canada)
FundersOffice of Research and DevelopmentU.S. Environmental Protection Agency
KeywordsQuality assuranceSuiteVisual inspectionEngineeringComputer scienceForensic engineeringConstruction engineeringOperations managementArtificial intelligence

Abstract

fetched live from OpenAlex

Despite the significant investments made in the use of cured-in-place pipe (CIPP) rehabilitation technologies, quality assurance (QA) and quality control (QC) practices can vary widely among municipalities, and CIPP liner evaluations are mostly restricted to periodic CCTV inspections. The information in this paper is derived from a multi-year project funded by the U.S. Environmental Protection Agency (US EPA). The study included a first of its kind retrospective evaluation of retrieved CIPP liners that were in service between 5 and 34 years at 18 different locations. This paper focuses on an assessment of the types of testing that were used during a pilot study to perform the CIPP retrospective evaluation. After performing the suite of tests, both visual inspection and flexural testing were found to be the key QA/QC assessment techniques. However, liners’ specific gravity was also found as a useful QA/QC tool and pursuing several other possibilities for non-destructive or minimally-invasive testing for measuring in situ physical properties of liners appeared feasible.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.567
Threshold uncertainty score0.870

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.056
GPT teacher head0.316
Teacher spread0.260 · 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