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Record W2168997797 · doi:10.1061/9780784413692.025

Predicting the Remaining Life of Asbestos Cement Pipe with Acoustic Wall Thickness Testing

2014· article· en· W2168997797 on OpenAlex
Gregory K. Robbins, Dave Johnston, Kevin Laven

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

VenuePipelines 2014 · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsHydrogenics (Canada)
Fundersnot available
KeywordsAsbestos cementCementService lifePrioritizationMains electricityForensic engineeringWater pipeService (business)EngineeringEnvironmental scienceAsbestosMaterials scienceReliability engineeringComposite materialMechanical engineering

Abstract

fetched live from OpenAlex

Introduced as a building material in the mid-1900s, asbestos cement pipe makes up approximately 18% of all water mains in North America. Although its use declined in the 1980s after health concerns began to arise, a large amount of asbestos cement water pipe remains in service in many municipalities. While many have chosen to remove all asbestos cement mains from service, the combination of budget constraints and the complexity of its removal means the remaining pipes must be systematically prioritized. Remaining service life calculations based on the physical condition of the pipe are of significant value in this prioritization process. Prediction of pipe failure involves three core components: assessing the main's current physical condition, predicting how the condition will change, and determining the condition in which it will fail. This paper presents a simple yet effective method specific to asbestos cement pipe, with a focus on structural failure of the pipe wall.

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)0.000
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 score0.687
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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