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Record W4410592698 · doi:10.1139/cgj-2024-0747

Curing effects on strength, small strain stiffness, and microstructure of a lime-treated lean clay

2025· article· en· W4410592698 on OpenAlexvenueno aff
Huan Wang

Bibliographic record

VenueCanadian Geotechnical Journal · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsnot available
FundersChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsMicrostructureCuring (chemistry)StiffnessMaterials scienceGeotechnical engineeringComposite materialLimeGeologyMetallurgy

Abstract

fetched live from OpenAlex

This paper presents a multi-scale investigation of curing effect on the strength, stiffness, and microstructure of a lime-treated decomposed red mudstone (LDRM). Particular emphasis was assigned to develop a unified framework characterizing the development of the strength and small strain stiffness with curing period. Uniaxial compression tests and bender element tests were conducted on LDRM compacted at three void ratios and two lime contents up to 8640 h (360 days) of curing. Three-stage behavior, namely, initial curing, primary curing, and secondary curing was clearly identified, from which a power model was proposed to capture the S-shape evolution curve. The separation between three stages were clearly identified by examining the inflection point on the S-shape curve and the tangent at the inflection point. The proposed model applied well to not only LDRM, but also to a range of artificial soils. Changes in the pore size distribution and microfabric of LDRM during long-term curing were confirmed by mercury intrusion porosimetry and scanning electron microscope analyses. In detail, the progressive agglomeration and the transition in pore volume were considered as the structural interplay responsible for the increase in strength and small strain stiffness of LDRM.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.191
Teacher spread0.184 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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