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Record W1972371109 · doi:10.1139/t04-035

Performance evaluation of a buried steel pipe in a moving slope: a case study

2004· article· en· W1972371109 on OpenAlexvenueno aff
Pei-Chun Chan, Ron CK Wong

Bibliographic record

VenueCanadian Geotechnical Journal · 2004
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringTransverse planeLateral movementGeologyPerpendicularMovement (music)Soil structure interactionBendingSubgradePipeline (software)Structural engineeringEngineeringFinite element methodGeometry

Abstract

fetched live from OpenAlex

Shallow and deep-seated soil movements were observed in a slope in which a steel pipe was laid for transport of oil emulsion. In the past, solutions have been developed mainly for analysis of buried pipes subjected to longitudinal or transverse soil movement at a shallow depth. Based on simplified soil–pipe interaction relationships and ground movement patterns, this paper presents methods for analysis of pipes subjected to the measured soil movements at varying depths in slopes. These methods decompose the resultant soil movement into its components parallel and perpendicular to the pipeline, i.e., the pipeline is subjected to a combined longitudinal and transverse soil movement. In the transverse movement analysis, the effect of pipe stretching due to large deformation is included. These methods were used in the case study to assess the potential of yielding in the pipe with the given soil movements that occurred in the slope.Key words: pipeline, soil subgrade, soil movement, bending, axial stretching.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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 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

Citations30
Published2004
Admission routes1
Has abstractyes

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