Discovery, supply and demand: From Metals of Antiquity to critical metals <sup/>
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
Transformational growth amongst the various critical metals’ markets would reduce supply concerns for industrial consumers and governments, whilst also providing commercial opportunities for the upstream industry. However, despite rapid market growth amongst some critical metal markets over the last decade, as a group they have lagged the market growth rates of the non-ferrous industrial and precious metals sectors. Research into the growth prospects of the critical metal markets is clearly required; however, their limited economic history and a paucity of data make this difficult. The economic history of the metals and mining industry as a whole, however, is better documented, and thus may provide insights into the potential for market growth amongst the critical metals. This paper therefore reviews the economic history of metals and mining, and in particular, that of the aluminium, nickel and uranium industries in an attempt to understand the key drivers behind transformational growth within the metals’ markets. This historical review suggests that a combination of breakthroughs in discovery, supply and demand are required to catalyse transformational market growth; and thus that parties seeking to benefit from the transformational growth of the critical metals’ markets must approach these markets in an integrated manner, considering each of the discovery, supply and demand issues in turn, rather than focusing on one specific constraint.
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.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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