Using X-ray micro CT imaging data to obtain particle morphology and soil fabric parameters
Bibliographic record
Abstract
In addition to the well-understood effects of void ratio and effective confining stress on the mechanical behavior of finegrained soils, past experimental research at the University of British Columbia (UBC), Vancouver, Canada, has revealed a considerable effect of particle fabric on the monotonic and cyclic shear behavior of silts. With this background, an experimental research program was undertaken to further investigate the particulate nature and arrangement of silts. The fabric of soils has been traditionally associated with the matrix void ratio, but can be directly associated with fabric parameters like the coordination number. Furthermore, grain morphology has a significant impact on these characteristics. Advancements in acquiring digital images and associated processing have made it possible to obtain individual soil particle parameters such as length, width, breath, thickness, volume, etc., along with information on spatial location and orientation of a given particle - thus providing the data needed to determine contact fabric and morphology of a soil matrix. In order to calculate these parameters and look for any potential correlations, commercially available, precalibrated, standard-size silica having particles within the size range from 40 μm to 60 μm, were imaged and analyzed. This study establishes an approach for extracting void and morphological information from tomographic images using image analysis techniques and algorithms developed in-house. Initial observations related to particle morphology and preliminary fabric scalar parameters are discussed. This work contributes to the accounting for fabric in understanding the macroscopic shear behavior of silts from the Fraser River Delta, British Columbia, Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".