Bibliographic record
Abstract
The focus of this work has been to investigate the status of backfill technology, in particular paste backfill, a relatively new technology. A rationale specifically for paste backfill system design has been developed. To date, a limited number of mines have implemented paste backfill systems. An extensive survey of backfill literature and a review of paste backfill operations in practice was undertaken. This has been used to identify target paste backfill design criteria and the critical success factors for paste backfill system design and implementation. Material characterisation for paste backfill has been identified as one of the key elements of paste backfill design. The criticality of determining the physical, chemical, and mechanical characteristics of tailings, which will affect the paste backfill quality and performance, has been illustrated in a case study of paste characterisation test work conducted by the author at a Canadian base metal mine. A number of outstanding issues, primarily technical, related to the reliability of paste backfill systems design have been identified. The future advancement of paste backfill technology will depend on the resolution of these key issues.
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 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) | 0.000 | 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 teacher head, 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".