Revaluing mine waste rock for carbon capture and storage
Bibliographic record
Abstract
Many mining wastes, especially those from the metal mining industry, have traditionally been treated as a matter of little or no value and in practice a cost burden. Some wastes, because of their reactivity characteristics, have emergent values that go beyond purely economic and into the environmentally beneficial realm. This article discusses the changing paradigm of mine waste management. Such fundamental parameters, such as cut-off grade and strip ratio, are positively impacted by the revaluation of waste rock material. Mine rock waste can now be seen as a commodity of value similar to the underlying ore being mined, which influences the economic performance of suitable projects. This valuable material can be used for industrial purposes including acid neutralisation as well as the capture and long-term disposal of anthropogenic carbon dioxide. The Turnagain Nickel project, located in Northern British Columbia, serves as an example of how waste rock material can become an important matrix for carbon capture and sequestration and how a project can benefit economically from it. By producing material that has emergent economic value as well as carbon capture and sequestration capabilities, the sequestration matrix producer is a beneficiary of new carbon credits that have a market value and is looked upon favourably by regulatory authorities and affected stakeholders.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".