Processes affecting surface and chemical properties of chrysotile: Implications for reclamation of asbestos in the natural environment
Bibliographic record
Abstract
Holmes, E. P., Wilson, J., Schreier, H. and Lavkulich, L. M. 2012. Processes affecting surface and chemical properties of chrysotile: Implications for reclamation of asbestos in the natural environment. Can. J. Soil Sci. 92: 229–242. A landslide at the headwaters of the Sumas River in southwestern British Columbia, is a seasonal and episodic source of chrysotile asbestos to the floodplain soil. Fresh alluvial deposits of fibres have potential for aeolian movement, posing a health risk to the Sumas watershed population. To understand the effects aquatic and pedogenic processes have on the fibres, asbestos materials from the river and floodplain were subjected to organic acid treatments in the laboratory. Changes were monitored by X-ray diffraction, scanning electron microscopy and elemental analysis. Fibre surfaces modified by organic acid treatments were similar to those affected by natural processes in that they showed a high loss of elements from the brucite layer compared with the silica tetrahedral layer, and the surfaces became smoother due to the loss of a rough amorphous coating. To initiate sustainable reclamation practices, changes in fibre surfaces by natural processes need to be considered and enhanced by incorporation of organic amendments that produce complexing soil acids. Reclamation activities should focus on recently deposited sediment along the floodplain. Non-polluting organic material, such as peat, compost and sawdust could be applied to increase reaction potential and kinetics of the reaction of chrysotile with naturally occurring acids.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".