Effect of Structure on the Geotechnical Properties of Bauxite Residue
Bibliographic record
Abstract
This paper describes a laboratory program to investigate the mechanical and physicochemical properties of bauxite residue (red mud) at a site in the United Kingdom. The red mud storage facility has been recently decommissioned and has been considered for future rehabilitation and construction activity. Based on a suite of laboratory tests conducted on the red mud, the material has compression behavior similar to clayey soils, but frictional behavior closer to sandy soils. The red mud appears to be “structured” and has features consistent with sensitive, cemented clay soils. Chemical testing suggests that the agent causing the aggregation of particles is hydroxysodalite and that the bonds are reasonably strong and stable during compressive loading. Exposure of the red mud to acidic conditions causes dissolution of the hydroxysodalite and a loss of particle cementation. Hydration of the hydroxysodalite unit cells is significant, but does not affect the mechanical performance of the material. The shape, size, and electrically charged properties of the hydroxysodalite, goethite, and hematite in the red mud appear to be causing mechanical behavior with features consistent with clay and sand, without the presence of either quartz or clay minerals.
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 | 0.000 |
| 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 | 0.001 | 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".