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Record W4390043750 · doi:10.31223/x5tm36

Investigation of Liquefaction Potential in Sands Mixed with Gravel

2023· preprint· en· W4390043750 on OpenAlexaboutno aff
wenbo luo, Zhuoqiang Wen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsLiquefactionSiltGeotechnical engineeringGeologySoil liquefactionRelative densityEnvironmental scienceGeomorphologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Liquefaction is one of the significant hazards associated with earthquakes. It was previously believed to occur mostly in clean sands; however, recent research has shown that liquefaction can occur in specific conditions in sands mixed with fine or coarse particles. Numerous studies have been conducted on clean sand, while limited research has focused on sands mixed with silt. Nevertheless, the liquefaction resistance of sands mixed with coarse particles has received less attention in previous studies. This research investigates the liquefaction potential of sand mixed with gravel using cyclic triaxial testing. The experiments were performed on Ottawa sand mixed with various percentages of gravel. The study evaluates the influence of parameters such as relative density and gravel percentage on the liquefaction resistance of the mixed soil. The results indicate that the gravel percentage and relative density of the samples significantly affect the liquefaction potential.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.195
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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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