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Record W4205446723 · doi:10.1139/cgj-2021-0440

The <i>ε</i><sub>v</sub>/<i>ε</i><sub>a</sub>–<i>p</i>′ method for the determination of instability of granular soils under constant shear drained stress path

2022· article· en· W4205446723 on OpenAlexvenueno aff
Jayan S. Vinod, M. Neaz Sheikh, Andy Fourie, David Reid

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersUniversity of South AustraliaUniversity of WollongongUniversity of New South WalesFreeport-McMoRan Foundation
KeywordsInstabilityStress pathGeotechnical engineeringShear (geology)Shear stressConstant (computer programming)Stress (linguistics)Soil waterEffective stressDrop (telecommunication)MechanicsPath (computing)MathematicsGeologyPhysicsEngineeringSoil scienceComputer science

Abstract

fetched live from OpenAlex

Past studies suggested various methods to determine the onset of instability of soil under constant shear drained (CSD) stress path using triaxial equipment. These methods were based on the characteristic features observed on the CSD stress path, axial and volumetric strains. However, the characteristic features are not similar for every soil leading to inconsistencies in predicting the onset of instability under the CSD stress path. This paper presents a strain ratio (εv/εa) – mean effective stress (p′) based method for determining the onset of instability of sand in the CSD stress path. The proposed method identifies the onset of instability at the drop of the εv/εa–p′ curve and features a distinctive value to mark the onset of instability. A series of CSD tests have been carried out on sand samples to verify the applicability of the proposed method. The proposed method captured the onset of instability similar to the other methods available in the literature.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.224
Teacher spread0.216 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

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