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Shear Strength and Stiffness of Silty Sand

2000· article· en· W2142535963 on OpenAlexaboutno aff
Rodrigo Salgado, Paola Bandini, Ahmed M. Karim

Bibliographic record

VenueJournal of Geotechnical and Geoenvironmental Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringConsolidation (business)SiltStiffnessTriaxial shear testDilatantDirect shear testGeologyShear (geology)Shear strength (soil)Shear stressSoil testSoil waterMaterials scienceComposite materialSoil science

Abstract

fetched live from OpenAlex

The properties of clean sands pertaining to shear strength and stiffness have been studied extensively. However, natural sands generally contain significant amounts of silt and/or clay. The mechanical response of such soils is different from that of clean sands. This paper addresses the effects of nonplastic fines on the small-strain stiffness and shear strength of sands. A series of laboratory tests was performed on samples of Ottawa sand with fines content in the range of 5–20% by weight. The samples were prepared at different relative densities and were subjected to various levels of mean effective consolidation stress. Most of the triaxial tests were conducted to axial strains in excess of 30%. The stress-strain responses were recorded, and the shear strength and dilatancy parameters were obtained for each fines percentage. Bender element tests performed in triaxial test samples allowed assessment of the effect of fines content on small-strain mechanical stiffness.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.157
Teacher spread0.154 · 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

Citations557
Published2000
Admission routes1
Has abstractyes

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