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Record W2156388478 · doi:10.1139/cgj-2013-0169

The undrained strength – liquidity index relationship

2014· article· en· W2156388478 on OpenAlexvenueno aff
Paul J. Vardanega, Stuart K. Haigh

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsLogarithmAtterberg limitsGeotechnical engineeringShear strength (soil)Power functionMathematicsMarket liquiditySoil waterMaterials scienceStatisticsGeologyMathematical analysisSoil scienceEconomicsWater content

Abstract

fetched live from OpenAlex

A database of 641 fall cone tests on 101 soil samples from 12 countries has been analysed to determine the best mathematical relationship linking undrained shear strength with liquidity index. From the database, it is shown that the use of a linear relationship linking liquidity index and the logarithm of undrained shear strength that uses the commonly assumed 100-fold factor increase in strength from the liquid to plastic limit overpredicts the measured data of soil strength. The use of a factor of about 35 for the ratio between the strength at liquid limit and that extrapolated to the plastic limit is shown to be more realistic. Logarithmic liquidity index is examined and found to also correlate strongly with the logarithm of undrained shear strength; however, it is shown that no great statistical improvement is present compared with the semi-logarithmic formulation. When considering data of individual soils a power law fitting is statistically shown to be the preferred mathematical function.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.186
Teacher spread0.177 · 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 designBench or experimental
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

Citations116
Published2014
Admission routes1
Has abstractyes

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