Status of Canada’s Geoscientific Site Evaluations for a Deep Geological Repository for Used Nuclear Fuel
Bibliographic record
Abstract
The Nuclear Waste Management Organization (NWMO) is responsible for implementing, collaboratively with Canadians and Indigenous people, Canada’s plan for the safe, long-term management of used nuclear fuel. The NWMO is working to implement Canada’s plan, in a manner that protects both people and the environment. Canada’s plan calls for containment and isolation of used nuclear fuel in a deep geological repository, which is made up of a series of natural and engineered barriers. This facility will be located in an area with informed, willing hosts within a suitable rock formation. In 2010, the NWMO initiated a nine-step site selection process to seek an informed and willing community to host Canada’s deep geological repository. The geoscience site evaluation process includes three main technical evaluation steps to assess the suitability of candidate areas in a stepwise manner. By the end of 2012, twenty-two communities had expressed interest in learning more about the project. As of the end of 2022, two areas remain in the site selection process. The NWMO is on track to identify a single, preferred location for this facility by approximately end of 2024. This paper describes the approach, methods and criteria being used to assess the geoscientific suitability of the sites, and lessons learnt to date. Activities to interweave Indigenous Traditional Knowledge with western science are also discussed.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".