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Record W4244060618 · doi:10.1680/geot.2005.55.2.109

Towards reliable and effective site investigations

2005· article· en· W4244060618 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGéotechnique · 2005
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsScope (computer science)Settlement (finance)Reliability (semiconductor)Geotechnical engineeringCivil engineeringEngineeringFinite element methodMonte Carlo methodConstruction engineeringStructural engineeringComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

It is widely appreciated that, in civil engineering and building projects, the largest element of financial and technical risk usually lies in the ground. Almost exclusively, the scope of geotechnical investigations is governed not by what is needed to characterise the subsurface conditions appropriately but, rather, by how much the client and project manager are willing to spend. There is often little correlation between the variability of the ground and the scope of the investigation. This paper presents the results of a Monte Carlo simulation incorporating many 3D single-layer soil profiles with different statistical characteristics. A three-storey building founded on nine pad footings is used to assess the reliability of various site investigation scopes and test methods. The pad footings are designed on the basis of settlement, and are examined using 3D finite element analysis and Schmertmann's method. It is observed, as expected, that the likelihood of underdesigning or overdesigning a footing decreases as the scope of the investigation increases. The relationship between these likelihoods and the variability of the ground is presented.

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.

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)0.000
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 score0.775
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.003
GPT teacher head0.187
Teacher spread0.184 · 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