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Record W4409360411 · doi:10.1139/cgj-2024-0405

Evaluation of cementation effects on swelling properties of bentonite buffer material using natural analogue

2025· article· en· W4409360411 on OpenAlexvenueno aff
Daichi Ito, Hailong Wang, Hideo Komine

Bibliographic record

VenueCanadian Geotechnical Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsBentoniteCementation (geology)Geotechnical engineeringSwellingBuffer (optical fiber)Natural (archaeology)GeologyMaterials scienceForensic engineeringComposite materialEngineeringCement

Abstract

fetched live from OpenAlex

Bentonite buffer material designed for the geological disposal of high-level radioactive waste must maintain its swelling capacity for tens of thousands of years in a disposal environment. During such a long period, a salient concern is that the designed functions might degrade because of cementation in the buffer. For this study, to estimate cementation effects on buffer swelling properties, bentonite ore was tested as a simulant: a natural analogue of the cemented buffer. This natural system resembling a geologic repository provides evidence of some inaccessible features such as long-term and structural complexity. Swelling pressure and swelling deformation tests conducted under different confining conditions were used to assess ore blocks (i.e., undisturbed specimens) and crushed ore (i.e., reconstituted specimens). The test results indicate a unique relation between the specimens’ confining pressure and their dry density conditions for undisturbed and reconstituted specimens. These unique relations elucidated the extent of cementation effects on the designed functions of the buffer material.

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: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.272
Teacher spread0.241 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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