Cross-jurisdictional analysis and forecasting of North American nuclear fuel inventory using a standardized unit
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
This study fills the noted gap in comparative analyses of spent nuclear fuel (SNF) by assessing inventories from two key nuclear power regions, the USA and Canada, using a comprehensive analytical framework and standardized data from 2009 to 2021. In the USA, SNF inventory increased by 14.7 % in fuel assembly weight and 47 % in residual heavy metal content compared to Canada, in line with their use of light water reactors. Canada's SNF production is directly correlated to its nuclear power output, influenced by the lower burnup of natural uranium fuel used in CANDU reactors (R 2 = 0.57; p-value < 0.05) while the USA shows insignificant correlation, likely due to a variety of reactor types and higher burnup rates (R 2 = 0.008; p-value > 0.05). Further, the study identifies a strong negative correlation between uranium mine production and SNF inventory in the USA, indicating a reliance on imports amidst negligible domestic mining. In contrast, Canada also exhibits moderate negative dependency due to its position as a major uranium exporting jurisdiction. The obtained negative correlations with coal rents in both countries indicate a shift towards more nuclear energy use, impacting economic growth and energy patterns. The developed predictive models indicate a higher future SNF increase in Canada than in the USA. These findings are essential for planning the transition from temporary to permanent SNF disposal, ensuring safe long term management of radioactive waste.
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 | 0.000 |
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