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Record W4289522054 · doi:10.1139/cgj-2022-0009

Monotonic and cyclic properties of silty sand and sandy silt for foundation design of offshore windfarms

2022· article· en· W4289522054 on OpenAlexvenueno aff
Shaoli Yang, Ben He, Knut H. Andersen, Sarah Firouzianbandpey

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSiltGeotechnical engineeringMonotonic functionGeologySoil waterShear (geology)Submarine pipelineFoundation (evidence)Simple shearMathematicsSoil science

Abstract

fetched live from OpenAlex

This paper presents results of a series of monotonic and cyclic direct simple shear laboratory tests performed on reconstituted samples of two silty sands and one sandy silt. The laboratory program aimed to determine the cyclic shear strength and deformation characteristics of soils to be used in the offshore wind turbine foundation design. Various cyclic contour diagrams including cyclic shear strength and average and cyclic shear strains for different number of cycles were provided. The effect of strain rate for drained monotonic tests and overconsolidation ratio effect on both monotonic and cyclic properties were discussed. This study indicated that the fines content plays an important role in static and cyclic shear strength of silty soils, in addition to mineralogy and coefficient of uniformity.

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)0.001
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.019
GPT teacher head0.193
Teacher spread0.174 · 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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