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Record W2250124683

DEVELOPMENTS IN DEEP FOUNDATION HIGHWAY PRACTICE - THE LAST QUARTER CENTURY. IN: CURRENT PRACTICES AND FUTURE TRENDS IN DEEP FOUNDATIONS

2004· article· en· W2250124683 on OpenAlexaboutno aff
Jerry A. DiMaggio, G G Goble

Bibliographic record

VenueGeotechnical special publication · 2004
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFoundation (evidence)EngineeringQuarter (Canadian coin)Software deploymentSubgradeCivil engineeringConstruction engineeringForensic engineeringTransport engineeringPolitical scienceLawArchaeologyGeography
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the many significant changes in deep foundation design and construction, with the United States highway practice, during the last quarter century. The impressive listing of advancements has resulted in numerous benefits to the professional community, the deep foundation industry, and to United States taxpayers as well as private owners. The benefits have been tangible and intangible, and include reduced total project cost, accelerated speed of construction, development and deployment of improved materials and construction equipment, improved specifications and contracting procedures, and an overall improved appreciation of Geotechnical Engineering within the highway industry. Based on the author's more than 30 years of experience, in depth comparisons are made between current practice, national practice circa 1980, and 20 years in the future (2023). The information provided is partially obtained from the Federal Highway Administration's (FHWA) Geotechnical Program Review series that has been used by FHWA's National Geotechnical Team (NGT) to benchmark and assess Geotechnical Engineering highway practice since the early 1970s. Unfortunately, not all the developments have been positive nor have all the important and necessary changes that should have taken place occurred. This paper examines these topics by following an overall suggested development and delivery flowchart for deep foundation projects. An overall suggested design and construction process is presented with emphasis on several key steps that are sometimes omitted or misapplied on even major projects.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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 designOther design
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
Published2004
Admission routes1
Has abstractyes

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