Estimation of fill strength requirements using bonded particle modelling for mining under cemented rockfill
Bibliographic record
Abstract
Recovery of sill pillars is often associated with mining under existing backfill. The backfill stability in such cases is of primary concern due to risks associated with personnel safety, equipment loss, and ore dilution. Two key aspects that control the stability of exposed backfill are the fill strength and the size of the fill exposure. Use of stronger fill will allow for increased excavation size but will come at a higher cost because of higher binder content requirements. A mine operator, therefore, must decide what combination of excavation size and fill strength is appropriate. In this paper we present the results of a study for a base metal mine in Canada aimed at estimating the strength requirements for cemented rockfill (CRF) being undercut. Numerical simulations utilising bonded particle models were used to relate the size of the undercut to the CRF strength requirements. The results were expressed as the depth of fill failure and as ore dilution, allowing the operator to select appropriate fill strength.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".