Comparison of All-in Sustaining Costs, Gold Grade, and Gold Prices in North American Gold Mining Companies
Bibliographic record
Abstract
Mining has evolved into an equilibrium of ore deposit management, environmental stewardship, and economic profitability that necessitates a proper understanding of economics and production efficiency. The All-In Sustaining Cost (AISC) was introduced in 2013 to better capture the cost of producing one ounce of gold and, when compared with the gold price and grade, could describe a company’s gold production efficiency. In this paper, this novel analysis focuses on US and Canadian operations under Barrick and Newmont, the two largest gold mining companies in North America, from 2019-2022. Published data for Coeur and Kinross were also secondarily analyzed. Under Newmont Corporation, Cripple Creek & Victor (CC&V) consistently demonstrated higher AISC than Éléonore (except in 2020), hinting at potential challenges in profitability for CC&V. Overall, Éléonore boasted a higher gold grade, potentially mitigating certain production costs and bolstering profitability relative to CC&V. Under Barrick Corporation, Hemlo consistently demonstrated higher AISC compared to Nevada Gold Mines, suggesting potential profitability challenges. Despite boasting a higher gold grade overall, Hemlo encountered reduced cost efficiency due to its higher production costs relative to the prevailing gold price. In terms of sustainability, all operations must continue to address efficient resource management, adherence to regulatory standards, and community engagement efforts. Areas for future research include comparisons of AISC, gold cost, and gold grade between surface and underground mine operations, as well as intercontinental comparisons among settings with varying labor costs and degrees of sustainability efforts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".