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Record W2028745449 · doi:10.1139/t08-035

Cone penetration test (CPT) methods for end-bearing assessment of open- and closed-ended driven piles in siliceous sand

2008· article· en· W2028745449 on OpenAlexvenueno aff
Xiangtao Xu, James A. Schneider, Barry Lehane

Bibliographic record

VenueCanadian Geotechnical Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsCone penetration testPileGeotechnical engineeringPenetration testPenetration (warfare)Submarine pipelineBearing capacityBearing (navigation)Reliability (semiconductor)EngineeringStructural engineeringGeologyMarine engineeringComputer scienceOperations researchSubgrade

Abstract

fetched live from OpenAlex

The cone penetration test (CPT) has been used as a means of assessing the end bearing of driven piles in sand for many decades. This paper examines the predictive performance of four new such CPT-based methods recently included in the commentary of the 22nd edition of the American Petroleum Institute’s recommended practice for fixed offshore structures. It is demonstrated that the formulations given by one of these methods, referred to as UWA-05, provides better predictions than the three other CPT methods when tested against (i) an existing database of base-capacity measurements, (ii) results from a new series of load tests on small-diameter piles, and (iii) base capacities measured in two recently conducted load tests on 1.5 m diameter pipe piles. It is shown that the UWA-05 has better predictive performance (and hence reliability) as it accounts explicitly for the effects of partial plugging during pipe–pile installation and for variations in CPT resistance in the vicinity of the pile tip.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.548
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.025
GPT teacher head0.299
Teacher spread0.273 · 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 designSimulation or modeling
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

Citations49
Published2008
Admission routes1
Has abstractyes

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