Bibliographic record
Abstract
The void distribution of saturated specimens of Ottawa sand is presented. The presence of water inside the sand specimen is detected using the magnetic resonance imaging (MRI) technique. The void distribution of the sample was determined from the image. The specimen was prepared in a non-metallic triaxial cell and was put insie a MRI apparatus to obtain the image. Two sample preparation methods (wet tamping and dry pluviation) were used to illustrate the uniformity of the samples in the initial state. The void distribution along the height of the sample and the three-dimensional orientational void distribution at different locations inside the sample were analysed. The results indicate that the sample generated by the dry-pluviation method is more uniform than the sample generated by the wet-tamping method. When the wet-tamping sample preparation technique is used, the dense sample is more uniform than the loose sample. The development of voids was investigated by a sample loaded inside the MRI device under drained compression condition. The void distribution along the height of the sample at different stages was observed. This work has demonstrated the feasibility of using the MRI technique to examine void distribution in granular material.
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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 | 0.000 |
| 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".