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Record W2160066281 · doi:10.1139/cgj-2012-0215

Effects of pile extraction and refilling with cement slurry on ground settlements

2013· article· en· W2160066281 on OpenAlexvenueno aff
Yue Wu, Jian Liu, Charles W. W. Ng

Bibliographic record

VenueCanadian Geotechnical Journal · 2013
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSettlement (finance)PileSlurryGeotechnical engineeringExtraction (chemistry)CementBeam (structure)Human settlementMaterials scienceGeologyStructural engineeringComposite materialEngineeringWaste managementChemistry

Abstract

fetched live from OpenAlex

Secant pile walls reinforced with steel I-beams are widely used worldwide. Although ground surface settlement caused by the installation of secant pile walls has been investigated, there is minimal data available on ground surface settlement due to extraction of steel I-beams from secant pile walls. This note aims to investigate the effectiveness of cement slurry refilling on reducing ground settlements during extraction of steel I-beams. Measured ground surface settlements during the extraction of steel I-beams from secant pile walls with and without cement slurry refilling are reported, discussed, and explained. Two different influence zones due to steel I-beam extraction can be identified. Ground settlement due to steel I-beam extraction can be minimized with the refilling of cement slurry. By using such a refilling technique, measured maximum surface settlement was reduced by 70%. The average measured settlement rate was reduced by 61%.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.005
GPT teacher head0.176
Teacher spread0.171 · 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 designBench or experimental
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

Citations9
Published2013
Admission routes1
Has abstractyes

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