Influence of fines content on the undrained flow instability of loess
Bibliographic record
Abstract
The influence of fines content (FC) on flow instability of intact and reconstituted Chinese loess is studied under undrained monotonic loading using conventional triaxial tests. The undrained behaviour of a mixed loess system indicates that the increasing plastic fines reduce the peak strength with little effect on the critical state friction angle. The changing FC can result in parallel translation and rotation of the critical state lines (CSLs) of reconstituted loess in the volumetric plane. A coarse-grain- to fine-grain-dominant transition is found as FC attains 55·5%, with a convergence of CSL for FC ranging from 55·5 to 87·9% using the equivalent interfine void ratio. A similar trend is found for intact specimens, suggesting that fines may act as void fillers at low-stress levels, which indicates a competing effect of structure and interfine contacts. The modified state parameter is robust in characterising the flow behaviour of the Chinese loess with revised range and corresponding descriptors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".