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Record W3185080465 · doi:10.1139/cgj-2020-0758

Low-strain dynamic characterization of undisturbed Leda clay

2021· article· en· W3185080465 on OpenAlexaffvenue
Muhammad Irfan, Giovanni Cascante, Dipanjan Basu, Denis LeBœuf

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversité LavalUniversity of Waterloo
Fundersnot available
KeywordsPlasticitySoil waterGeotechnical engineeringGeologyShear (geology)Shear modulusDamping ratioMaterials scienceMineralogyComposite materialSoil scienceAcousticsPetrologyPhysics

Abstract

fetched live from OpenAlex

The low-strain dynamic behavior of Leda clays is investigated using resonant column (RC) and bender element (BE) tests. Four undisturbed, lightly overconsolidated Leda clay samples, collected from two sites near the St. Lawrence River valley, are tested at different strains, confining stresses, and frequencies. To evaluate the effect of excitation frequency, simultaneous measurements of shear wave velocity using RC and BE tests are performed. The results show that the samples from the different sites behave differently. The high sensitivity of the Leda clays does not have a significant effect on the modulus degradation curves. However, the measured degradation curves are similar to those of soft clays with high plasticity, which is contrary to the expected behavior of these low plasticity (Ip = 6.2–20) specimens. Likewise, the measured damping ratios are on the lower end of the typical values reported for soils of high plasticity. Low values of damping ratio make the amplification of small seismic events more likely in Leda clay deposits. The difference in the shear wave velocity measurements from RC and BE tests ranges from 17% to 26% depending on the confinement, likely because of the strong influence of P-waves observed in the BE tests for these soils.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

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)0.0010.000

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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 designObservational
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

Citations4
Published2021
Admission routes2
Has abstractyes

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