Evaluation of Geotextile Performance for the Filtration of Fine-Grained Tailings
Bibliographic record
Abstract
Geotextile filters are an interesting solution to dewater tailings as they can be installed on existing ponds or be deployed during operation. However, filtration of the fine-grained tailings that are encountered in the oil sands and other mining industries raises several issues: blinding or clogging of the geotextile by the fine particles, or piping. Since the hydraulic conductivity of fine-grained tailings is generally too low for the ASTM D5101 standard test method for soil/geotextile system filtration compatibility, a test setup has been specifically developed and used to study the filtration behavior of needle-punched and heat-bonded nonwovens with various types of oil sands tailings. The permittivity of the geotextile/tailings systems was always several orders of magnitude lower than the water permittivity of the geotextile. On the other hand, no clogging or blinding was observed over more than 100 days. These results show that geotextiles offer great promise for the filtration of fine-grained tailings.
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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 | 0.001 |
| 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 | 0.001 |
| 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".