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Record W1984137522 · doi:10.1139/t06-023

Equivalent granular void ratio for characterization of Singapore's Old Alluvium

2006· article· en· W1984137522 on OpenAlexvenueno aff
Qing Ni, G. R. Dasari, T. S. Tan

Bibliographic record

VenueCanadian Geotechnical Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsVoid ratioSiltAlluviumGeotechnical engineeringGranular materialGeologyVoid (composites)StiffnessMineralogyMaterials scienceComposite materialGeomorphology

Abstract

fetched live from OpenAlex

Characterization of the Old Alluvium (OA) Formation in Singapore is difficult due to its natural heterogeneity. The OA formation was deposited by a braided river system, and it exhibits a wide range of engineering properties. Its strength and stiffness at a given depth, within a few metres distance horizontally, may differ by an order of magnitude, and this cannot be explained by differences in void ratio alone. The formation consists of sand, silt, and clay particles in varying proportions with no consistent relation with depth. Since the majority of OA is sand mixed with fines (silt and clay), the concept of granular void ratio, which treats silt and clay particles as void, was first introduced to try to characterize the formation. Though the concept of the granular void ratio was more useful than that of the void ratio, it could not take into consideration the different contributions that nonplastic silt fines and plastic clay fines make to the shear strength and thus was found to be inappropriate for a natural soil such as OA. To deal with this problem, the relative contribution of different kinds of fines is incorporated through the concept of equivalent granular void ratio. The merit of equivalent granular void ratio for the characterization of mixed soil formations is demonstrated in this paper through the analysis of results from triaxial tests on in situ OA samples.Key words: natural soil, clayey sand, Singapore Old Alluvium, heterogeneity, granular void ratio.

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)0.000
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 score0.816
Threshold uncertainty score0.801

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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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

Citations27
Published2006
Admission routes1
Has abstractyes

Explore more

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