Romanian Tritium for Nuclear Fusion
Bibliographic record
Abstract
The demand for tritium is expected to increase when ITER (the International Thermonuclear Experimental Reactor) begins operation in the mid-2020s. Romania is expected to detritiate its CANDU (Canada Deuterium Uranium) units at Cernavoda starting 2024, with the goal of improving radiological safety and reactor performance. Detritiation will result in a significant quantity of tritium being produced and thus Romania has an opportunity to supply tritium for fusion. In this assessment, ITER has been used as a reference device requiring tritium, as the projected tritium extraction schedule from Cernavoda aligns favourably with ITER operation. The findings suggest that Romania is capable of providing a total of 6.2 kg of tritium to ITER over its 20 year operation, generating a potential revenue of $186 M (USD). Opportunities associated with the supply of Romanian helium-3 are also considered as a hedging option, which has the potential to generate $120 M (USD) in the case of zero tritium sales. Greater involvement in future fission-fusion tritium-related activities through experience in tritium technologies is also discussed as a unique opportunity for Romania.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".