MétaCan
Menu
Back to cohort
Record W2144909104 · doi:10.1139/t03-005

Strain-induced anisotropy in fabric and hydraulic parameters of oil sand in triaxial compression

2003· article· en· W2144909104 on OpenAlexvenueno aff
Ron CK Wong

Bibliographic record

VenueCanadian Geotechnical Journal · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsTortuosityDilatantGeotechnical engineeringAnisotropyPermeability (electromagnetism)GeologyMaterials scienceTriaxial shear testOil sandsShear (geology)Composite materialPorosityAsphaltOptics

Abstract

fetched live from OpenAlex

Dense locked Athabasca oil sand specimens were tested in drained triaxial compression with lubricated ends at confining pressures of 5–750 kPa. Computer tomography and scanning electron microscopy imaging techniques were used to examine the microstructural features (interlocked structure, grain fabric, and rearrangement inside and outside shear bands) of the intact and sheared specimens. The average hydraulic radii and tortuosity along three principal directions were also measured using thin section imaging and electrical resistivity measurement methods. It was found that changes in fabric and hydraulic parameters of oil sand in triaxial compression are highly inter-related. Intrinsic and induced anisotropies in permeability were observed.Key words: oil sand, fabric, strain induced anisotropy, permeability, tortuosity, dilatancy.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.899

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 integrity0.0000.001
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 head0.020
GPT teacher head0.221
Teacher spread0.201 · 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 designOther design
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

Citations24
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207