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Record W2802940346 · doi:10.7939/r34953

Assessment of Pipeline Installation Using the Eliminator: a New Guided Boring Machine

2015· article· en· W2802940346 on OpenAlexaboutno aff
Mahmood Ranjbar

Bibliographic record

VenueUniversity of Alberta Library · 2015
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPipeline (software)Computer scienceEngineeringOperating system

Abstract

fetched live from OpenAlex

The Eliminator is a new guided boring machine developed to address the market need for Pilot Tube Microtunneling (PTMT) installations in non-displaceable soils. This study is part of a multi-phase research project sponsored by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the City of Edmonton. The main objectives of this research is to investigate the productivity of the Eliminator, risks associated with this machine, and methods to predict the required jacking force for installation of pipes. To achieve these goals, firstly a broad literature review was conducted on PTMT and the Eliminator as well as similar technologies such as microtunneling and pipe jacking. The study then introduces the first pipeline installation project performed with the Eliminator and assesses the technology’s economic performance using the project’s productivity and risk measures. The jacking force of the project was also monitored for analysis using hydraulic pressure transducers. Five existing jacking force prediction models used for technologies similar to the Eliminator were analyzed and compared with each force measured in the field. Based on the comparison, appropriate methods for estimating the jacking force of Eliminator projects are suggested.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.734
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.241
Teacher spread0.212 · 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 teacher head, 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

Citations0
Published2015
Admission routes1
Has abstractyes

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