Bibliographic record
Abstract
Abstract Oil sands are dense granular materials with interlocked structure and clay shales are heavily overconsolidated clays. They are classified as structured soil or weak rock, exhibiting high peak strength with severe softening and dilation, particularly at low confining stress. The triaxial compression test results indicate that both materials yield linear Mohr–Coulomb envelopes with an apparent cohesion for peak and residual strengths. However, the strength components mobilized from these two materials are very different. This paper investigates if these strength parameters are intrinsic properties or responses derived in triaxial compression conditions. Computer tomography scanning technique is used to aid in examining the micro‐structural features of the sheared specimens such as shear banding pattern, shear band thickness, spatial porosity distributions inside and outside shear bands. These micro‐structural features are used to explain the macro‐deformation response observed in the triaxial compression tests. Mobilization of strength components derived from interlocked structure, cementation, dilation, rolling and critical state are analysed for pre‐, post‐peak softening and residual stages. It is found that the empirical correlation such as Mohr–Coulomb failure criterion based on triaxial compression test results does not necessarily reflect the intrinsic properties of the test materials. Testing conditions are embedded in the empirical correlation. Copyright © 2001 John Wiley & Sons, Ltd.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".