Iron ore supplies to the United Kingdom iron and steel industry
Why this work is in the frame
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Bibliographic record
Abstract
The pattern of iron ore sources for the United Kingdom iron and steel industry has evolved in response to both national and worldwide technical developments and discoveries. In the earliest times ores came from numerous locations and supported small, local industries. Production grew rapidly from the mid-eighteenth century, especially after coke replaced charcoal as a reductant. Output became focused increasingly on the large resources of bedded phosphoric ironstones of central and eastern England; this was accelerated by the improved transport offered by the canal and railway networks. The low-phosphorus replacement hematite ores of Cumbria and South Wales were also exploited, especially to meet the requirements of the acid Bessemer process. Imports began in the mid-nineteenth century, initially from Europe and North Africa, and both domestic and imported ores were used on a substantial scale for many years. Dependence on imports became complete with the adoption of the Linz-Donawitz steelmaking process in the 1960s and 1970s. At about the same time mining and ocean freight developments enabled the use of ores from worldwide sources. In recent years ore supplies have come mainly from Australia, Brazil, Canada and South Africa. Most of the supply is sintering fines, with considerable quantities of lump ore and some pellets.Major technological changes in the short to medium term are not expected. There may be less lump ore available, but changes in blast-furnace practice, such as coal injection, may make it less desirable. In the longer term ores may have to be accepted with slightly higher phosphorus levels. Eventually, alternative processes to the blast-furnace may come to have a greater impact.
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 | 0.002 | 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