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Record W4392520845 · doi:10.1061/9780784485323.048

New Case Studies to Validate the GT Direct CPT Method for Footings on Sand

2024· article· en· W4392520845 on OpenAlexaff
Paul W. Mayne, Jim Greig

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMRF Geosystems (Canada)Conetec Investigations
Fundersnot available
KeywordsGeotechnical engineeringComputer scienceStructural engineeringEngineering

Abstract

fetched live from OpenAlex

A direct cone penetration test (CPT) method for assessing the load-displacement-capacity response of shallow foundations on sands that was previously developed at Georgia Tech (GT) is applied to four new case studies that have become available. The algorithm relates the ratio of applied foundation stress normalized to cone tip resistance to the square root of normalized displacement, defined as settlement divided by footing width. The case studies include footing load tests conducted on large shallow concrete foundations and steel plates situated on both natural sands and sands densified by ground modification and compaction methods. The case studies involve circular and square foundations from projects located in Oman, Kuwait, UAE, and Texas, with reasonably good predictive agreement shown for all cases. A means to extend the approach to include footings bearing on silty sands to sandy silts for drained behavior is also discussed.

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)0.003
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.306
Teacher spread0.285 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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