Postclosure Performance Assessment of a Hypothetical Canadian Deep Geological Repository for Thorium-Containing Advanced Heavy Water Reactor Fuels
Bibliographic record
Abstract
Lattice physics depletion calculations were performed to obtain postburnup fuel compositions for several candidate advanced heavy water reactor fuels. These fuel compositions were used as input for a deep geological repository (DGR) modeling tool for hydrogeology simulations to simulate the transport of radionuclides to the surface, to find the radionuclides that reach the surface path through the biosphere, and to estimate the hypothetical dose rate to humans located above the DGR.Three primary factors were found to contribute to surface dose rate: burnup, composition of the primary waste matrix, and percentage of thorium in the fuel. Higher burnup and thorium percentage contribute to increased surface dose rates through increased 129I production, while a primarily uranium waste matrix increases surface dose rate through faster dissolution leading to increased radionuclide release rate from the fuel. For all the hypothetical fuels investigated, the estimated dose rates are well within the Nuclear Waste Management Organization’s hypothetical DGR’s acceptance criterion of 0.3 mSv/year.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".