Macro-micro mechanics of Fujian River sand under triaxial shear using X-ray micro-tomography
Bibliographic record
Abstract
Fujian River sand (FJS) is a complex mixture of minerals and rock fragments shaped by the dynamic geological history of Fujian province, China. The macro–micro mechanical responses of FJS under triaxial shear were carefully investigated through the X-ray tomography-based in situ triaxial test. By utilising the particle tracking strategy with the signature of histograms of orientation, both intact and crushed FJS particles can be successfully recognised and tracked at different stages of axial strain. It is found that (a) smaller particles are more likely to crush than larger ones, and the crushed particles have more irregular particle shapes than the original set of particles; (b) the coordination number, fabric anisotropy, 3D rose map, and particle displacement are found to highly correlate to the phase transition point from volumetric contraction to dilation; (c) the sample deformation is found to be uniform at the early stage, and then it starts to spread from the boundaries to the inner part and finally develops into an inclined shear band; (d) locations of particle breakage within the granular assemblage show an overall sporadic and irregular pattern throughout the shearing process, which is not strongly correlated with the shear band that has developed, even at large strains.
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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 | 0.001 | 0.001 |
| 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".