Stacked deposits of thickened and filtered fluid fine tailings using geotextile tubes – concepts/lessons learned updates
Bibliographic record
Abstract
The Global Industry Standard on Tailings Management has the aspirational goal of "zero harm to people and the environment" from tailings facilities and provides a framework for safe tailings facility management while affording operators flexibility on how best to achieve this goal. This paper aims to consider an alternative form of fluid fine tailings management using geotextile tubes, which combines the enhanced geotechnical stability of the fluid fine tailings by dewatering and densification while effectively maximising the reclaiming of process water. To ensure that the return water is suitable for reuse in the plant and that the fluid fine tailings can be dewatered and densified faster, a physicochemical treatment (recipe) should assist solids/water separation and ensure fines agglomeration during pipeline transport before discharge in the geotextile tubes. This paper also describes the recipe/geotextile tubes concept and some lessons learned from their use as a filtration technology process designed to enhance the physical stability of fluid fine tailings deposits.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".