Development of an oil sands tailings management simulation model
Bibliographic record
Abstract
Mine tailings management systems (TMSs) consist of a web of interrelated subsystems across multiple processes and disciplines. Conventional predictive models simulate individual physical processes but lack integration with the overall TMS. A dynamic system-modelling approach was adopted to develop a model capable of simulating a TMS to facilitate the evaluation of operating strategies, design alternatives and dewatering technologies. Using a multitude of process-based, empirical and qualitative formulations, the model incorporates the major components of a TMS, including tailings production, dewatering, deposition and impoundment water balance. Individual model processes (e.g. consolidation and deposition) were verified using experimental, analytical or numerical data sets. A tailings plan from a hard-rock mine was then simulated to evaluate the model. The simulated tailings deposit and water cap elevations as well as total impoundment volume were found to be within 5% deviation of the mine data, indicating that the model is capable of simulating a TMS.
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".