Best Practices in Underground Coal Gasification
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
Underground coal gasification (UCG) converts coal in-situ into a gaseous product, commonly known as synthesis gas or syngas through the same chemical reactions that occur in surface gasifiers. Gasification converts hydrocarbons into a synthesis gas (syngas) at elevated pressures and temperatures and can be used to create many products (electric power, chemical feedstock, liquid fuels, hydrogen, synthetic gas). Gasification provides numerous opportunities for pollution control, especially with respect to emissions of sulfur, nitrous oxides, and mercury. UCG could increase the coal resource available for utilization enormously by gasifying otherwise unmineable deep or thin coals under many different geological settings. A 300-400% increase in recoverable coal reserves in the U.S. is possible. For developing countries undergoing rapid economic expansion, including India and China, UCG also may be a particularly compelling technology. UCG has been tested in many different experimental tests in many countries. The U.S. carried out over 30 pilots between 1975 and 1996, testing bituminous, sub-bituminous, and lignite coals. Before that, the Former Soviet Union executed over 50 years of research on UCG, field tests and several commercial projects, including an electric power plant in Angren, Uzbekistan that is still in operation today after 47 years. Since 1991, China has executed at least 16 tests, and has several commercial UCG projects for chemical and fertilizer feedstocks. In 2000, Australia began a large pilot (Chinchilla) which produced syngas for 3 years before a controlled shut-down and controlled restart. As present, multiple commercial projects are in various stages of development in the U.S., Canada, South Africa, India, Australia, New Zealand, and China to produce power, liquid fuels, and synthetic natural gas.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.001 |
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 it