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Record W4322623410 · doi:10.1139/cgj-2022-0188

Multiscale structural characterizations of anisotropic natural granite residual soil

2023· article· en· W4322623410 on OpenAlexvenueno aff
Xinyu Liu, Xianwei Zhang, Lingwei Kong, Gang Wang, Chengsheng Li

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsAnisotropyGeologySoil structureGeotechnical engineeringResidualCementation (geology)WeatheringShear (geology)Soil waterMaterials scienceComposite materialSoil sciencePetrologyGeomorphology

Abstract

fetched live from OpenAlex

While the anisotropy of sedimentary soil—particularly the underlying role of soil structure—is well understood, similar knowledge about granite residual soil formed by weathering is scarce. In particular, the evolution of soil structure during the hollow cylinder torsional shear tests (among the most appropriate for studying soil strength anisotropy) remains largely unknown. This study systematically investigates the multiscale structural properties of granite residual soil using stereo microscopy, scanning electron microscopy, energy-dispersive spectrometry, and computed tomography. Furthermore, the structural evolution during hollow cylinder torsional shear tests is traced. Results indicate the strength anisotropy of residual soil is associated with horizontal fissures which cause low shear strength when the soil is sheared with a principal stress direction of 45°. The cementation via Fe is characterized by a uniform distribution. Different evolutionary patterns are observed for soils within the shear band, inside the necking area, and in other regions. It is not always the case that particles are rearranged with their long axis perpendicular to the major principal stress. This study improves the understanding of natural residual soil structure and provides some insights into its anisotropic behavior.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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

Citations33
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Soil MechanicsFrench-language works237,207