Bibliographic record
Abstract
Aging of a CANDU nuclear power plant affects various safety margins of the plant. Margin to fuel sheath dryout is one of the safety margins that have been detrimentally affected, leading to a reduced margin to dryout with time. If no proactive actions are taken, the plant will have to de-rate its operation at an earlier time. To postpone the de-rating, the Canadian nuclear Industry has taken multi-initiatives to restore, or partially restore the safety margins that have been eroded due to plant aging. One of the initiatives is modification/re-optimization of the current fuel design, in order to improve the fuel thermalhydraulic performance, i.e., to suppress fuel sheath dryout, whereby offset partially the erosion of margin to fuel sheath dryout. In response to the initiative of fuel bundle modification, the Canadian Nuclear Safety Commission (CNSC) — the nuclear safety regulator — has set clear requirements and expectations and followed rigours processes and procedures for reviewing and licensing the modified fuel. This paper summarizes the fuel modification program in Canada, and the CNSC requirements, expectations, and review processes associated with licensing review of fuel modifications in Canada.
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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".