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Record W2174199045 · doi:10.1139/cgj-2014-0433

Reply to the discussion by Mesri and Wang on “Large-strain elastic viscoplastic consolidation analysis of very soft clay layers with vertical drains under preloading”

2014· article· en· W2174199045 on OpenAlexvenueno aff
HU Ya-yuan, Wan‐Huan Zhou, Yuanqiang Cai

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)ViscoplasticityGeotechnical engineeringPore water pressureGeologyMaterials scienceConstitutive equationEngineeringFinite element methodStructural engineering

Abstract

fetched live from OpenAlex

The design of preloading involves loading schedule design and prediction of post-construction settlement. As the in situ measurement data are usually unavailable during the loading schedule design, it is difficult to estimate the preloading effects before construction. In this Reply, we first discuss the satisfied conditions of eq. (D4) in the Discussion (Mesri andWang 2015) based on Bjerrum’s creep diagram (Bjerrum 1967) and Yin–Graham’smodel (Yin and Graham 1989). Then the research objective and significance of the paper under discussion (Hu et al. 2014) are addressed. Based on Bjerrum’s creep diagram and Yin–Graham’s model, the void ratio at the end of service period for soft soil can be expressed as (Hu 2012)

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.192
Teacher spread0.188 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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