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Record W2999088157 · doi:10.1061/9780784481646.038

New Deep Burial Testing Facility at Queen’s University

2018· article· en· W2999088157 on OpenAlexaff
Van Thien, Ian Moore, Neil A. Hoult

Bibliographic record

VenuePipelines 2018 · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsCulvertGeotechnical engineeringSoil waterGroundwaterErosionWater pipeGeologyEnvironmental scienceEngineeringMining engineering

Abstract

fetched live from OpenAlex

Laboratory testing to evaluate buried pipe systems under deep burial is needed to evaluate the response of a variety of culvert and sewer pipe products for a range of deterioration conditions and backfill soils. The cost and the time associated with experiments on highway and sewer structures in the field are significant. Until recently no facilities have existed to evaluate larger diameter pipes, to test pipes in saturated ground, or to allow the behavior of pipe joints at deep burial to be investigated. A new deep burial testing facility that is 3 m wide, 5 m long, and 4.6 m deep has been constructed at Queen's University to permit deep burial testing on pipes with diameters up to 3.05 m. The test pit is sealed, so that deep burial experiments can be conducted in saturated ground, permitting seminal studies of soil erosion caused by groundwater flow into the leaking joints of sewer pipes or perforations in deteriorated culverts. Selected results from a commissioning test on a 3.05 m diameter steel reinforced polyethylene pipe are provided.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.008

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 head0.012
GPT teacher head0.193
Teacher spread0.180 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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