Bibliographic record
Abstract
Heavy water (deuterium oxide) played a sinister role in the race for nuclear energy during the World War II. It was a key factor in Germany's bid to harness atomic energy primarily as a source of electric power; its acute shortage was a factor in Japan's decision not to pursue seriously nuclear weaponry; its very existence was a nagging thorn in the side of the Allied powers. Books and films have dwelt on the Allies' efforts to deny the Germans heavy water by military means; however, a history of heavy water has yet to be written.Filling this gap, Heavy Water and the Wartime Race for Nuclear Energy concentrates on the circumstances whereby Norway became the preeminent producer of heavy water and on the scientific role the rare isotope of hydrogen played in the wartime efforts by the Axis and Allied powers alike. Instead of a purely technical treatise on heavy water, the book describes the social history of the subject.The book covers the discovery and early uses of deuterium before World War II and its large-scale production by Norsk Hydro in Norway, especially under German control. It also discusses the French-German race for the Norwegian heavy-water stocks in 1940 and heavy water's importance for the subsequent German uranium project, including the Allied sabotage and bombing of the Norwegian plants, as well as its lesser role in Allied projects, especially in the United States and Canada. The book concludes with an overall assessment of the importance and the perceived importance of heavy water for the German program, which alone staked everything on heavy water in its quest for a nuclear chain reaction.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".