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Record W2987846387 · doi:10.1139/cgj-2019-0324

Axial capacity of bored piles in very stiff intermediate soils

2019· article· en· W2987846387 on OpenAlexvenueno aff
Le V. Doan, Barry Lehane

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersDepartment of Foreign Affairs and Trade, Australian Government
KeywordsGeotechnical engineeringPileSoil waterBearing capacityGeologyClay soilPenetration testEconomic shortageSoil science

Abstract

fetched live from OpenAlex

There is a major shortage of good-quality load test data for bored piles in stiff to hard intermediate soils such as silts and clayey sands. This paper presents the results and interpretation of an instrumented pile test in a very stiff overconsolidated fine-grained deposit. It is shown that, unlike typical fine-grained soils, dilation at the shaft of the pile makes an important contribution to the unit shaft friction. The relationship between shaft friction and the cone penetration test (CPT) end resistance is observed to differ appreciably from established empirical correlations for bored piles in less stiff, fine-grained soils. This is inferred to be largely because of the similarity between the drained and undrained CPT resistances in this soil type as well as the influence of dilation. Existing empirical methods to assess end bearing of bored piles are also seen to provide inconsistent estimations in this soil type.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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