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Record W2076784747 · doi:10.1139/t10-022

Long-term settlement of soft subsoil clay under rectangular or semi-sinusoidal repeated loading of low amplitude

2010· article· en· W2076784747 on OpenAlexvenueno aff
HU Ya-yuan

Bibliographic record

VenueCanadian Geotechnical Journal · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)SubsoilGeotechnical engineeringLeveeTerm (time)AmplitudeGeologyCoupling (piping)EngineeringSoil waterSoil sciencePhysicsComputer science

Abstract

fetched live from OpenAlex

By applying Yin and Graham’s one-dimensional (1-D) equivalent-time rheological model, which can predict both primary and secondary settlement, the expressions for calculating the long-term subsoil settlement under rectangular or semi-sinusoidal repeated loading of low amplitude are obtained without considering the fluid–solid coupling. A property has been proven that ultimate settlement of clay is independent of stress increasing history under 1-D conditions. According to this property, the expressions are derived considering the solid–fluid coupling to approximately calculate the long-term total settlement and the long-term settlement of soft subsoil clay after construction of the road embankment. Because the expressions of the long-term settlement are analytical solutions in the present paper, they can not only avoid cumulative calculation errors in the numerical analysis, but also have more solid theoretical foundations than empirical equations.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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

Citations14
Published2010
Admission routes1
Has abstractyes

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