Tailings mobilization estimates for dam breach studies
Bibliographic record
Abstract
Quantitative assessment of potential consequences caused by a flood from a dam breach of a tailings facility requires an estimate of the volume of water and tailings released during the breach. A methodology for estimating the volume of tailings mobilized by the free water stored in the pond and the resulting initial flood wave following a dam breach is presented. Tailings mobilization can be estimated as a function of the stored water volume and the physical characteristics of the tailings deposit. The result is an estimate of the total outflow consisting of volumes of free water, and tailings and interstitial water that could be potentially mobilized. This approach indicates that a larger operating pond would mobilize more tailings than a smaller pond. Similarly, a tailings deposit that is more consolidated or only partially saturated would result in a smaller volume of tailings being released in a breach. These are the primary attributes of stored tailings affecting the potential consequences of a breach. An understanding of these attributes allows the practitioner to use the results of the analysis as a decision making tool for decreasing the consequences of failure.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".