Filtered dry stacked tailings : the fundamentals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Filtered tailings are becoming an increasingly common consideration for tailings management at many mines. There are more filtered dry stack tailings storage facilities than there are surface paste facilities yet the amount of guidance documentation on filtered tailings is virtually non-existent in compare to those same paste tailings facilities. The reason for this lack of guidance materials is uncertain but it has led to some unfortunate tailings management decisions based on misinformation about dry stacked tailings facilities in general. This paper provides practical guidelines for the design and development of filtered dry stack tailings facilities. These guidelines are based upon the successful conceptualization, design, and operating experience at a number of these facilities. Issues related to target moisture content, appropriate testing methods and criterion, geotechnical conditions and placement considerations are included. The guidelines include specific reference to “lessons learned” from existing operations that will benefit designers and owners alike. [All papers were considered for technical and language appropriateness by the organizing committee.]
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 it