Bibliographic record
Abstract
This chapter describes the potential of the aqueous homogeneous reactor, briefing readers on the physics and history of the subject, whilst providing both current and possible future applications for this reactor technology. These reactors were some of the first nuclear reactors ever constructed, and provided valuable information on critical mass and other nuclear physical properties on fissile solutions. The compact nature of these reactors, combined with their inherent safety characteristics, have made them attractive for the generation of medical radioisotopes and neutrons for experimentation. However, material corrosion issues and advanced development of solid-fuelled light water reactors would curtail much interest in the technology in the 50’s. Although operating temperatures of this type of reactor are usually low, even such low temperature heat is useful in process and industry; such a reactor can be used for environmentally-friendly district heating or the supply of process heat in industry, and could even be used to produce hydrogen. With modern advances in physics and chemistry, and disruptions in conventional energy sources; such reactors in their modern form may serve an important role: supplying various energy demands that could be derived from nuclear power, but may not require more advanced and costly reactor technologies.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".