An automated production targeting goal programming framework for oil sands mine planning considering organic rich solids
Bibliographic record
Abstract
In oil sands mining, bitumen and fines contents are used to predict ore processability. However, experimental results show that certain solid fractions known as Organic Rich Solids (ORS) negatively affect the overall bitumen recovery. A conceptual mine planning framework based on a goal programming model for oil sands production scheduling and waste management is presented. Bitumen recovery is additionally adjusted based on the ORS content. The model features automated production targeting (APT) and limited duration stockpiling constraints that optimize the annual production capacities. The model is implemented with two scenarios. Scenario 1 uses processing recovery calculated based on Alberta Energy Regulatory requirements while Scenario 2 uses processing recovery additionally adjusted based on ORS content. Results for Scenario 1 show a 3.46% overestimation of net present value compared to Scenario 2. The APT constraints provide planners a robust and efficient technique for determining annual production tonnages with minimum periodic variations.
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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 | 0.001 |
| 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".