Adaptive policies for short-term material flow optimization in a mining complex
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the advent of inexpensive sensors and digital storage, increasing amounts of data about a mining complex can be collected. This data can, in turn, be used to continuously adapt stochastic optimization models and short-term mining decision making, thus reducing and managing local uncertainty. Taking advantage of this uncertainty reduction requires new decision-making approaches, mechanisms, and optimization methods. This paper proposes the use of state-dependent policies, which encode recipes for responding to new information as it comes along. Focusing on short-term planning shows how to represent and optimize state-dependent policies for making adaptive destination decisions for materials mined and processed. Resulting policies can be applied across different short-term time scales, marking an important step towards simultaneously optimizing different time scales. An implementation of the proposed method at a copper-gold deposit shows that it can improve the utilization of processing streams, production and financial performance over simple heuristic approaches and practices.
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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 | 0.001 |
| 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 it