Reframing the inadvertent human intrusion scenario to improve public understanding of repository safety
Bibliographic record
Abstract
The Nuclear Waste Management Organization (NWMO) is responsible for implementing Adaptive Phased Management (APM), the federally approved plan for the safe long-term management of Canada's used nuclear fuel.Under this plan, used nuclear fuel will ultimately be placed within a deep geological repository in a suitable host rock formation.The primary objective of a deep geological repository is the long-term containment and isolation of used nuclear fuel.The long-term safety of the repository is based on a combination of the properties of the waste material, engineered barriers, and geology.As the project moves toward site selection and in preparation for the licensing process, the NWMO is performing preliminary post-closure safety assessments of the potential sites.These assessments help determine the potential effects of the repository on the health and safety of people and the environment in the long term after repository closure.In alignment with national and international guidance, these safety assessments consider potential effects during the normal evolution of the repository and disruptive event scenarios, including inadvertent human intrusion scenarios.Such scenarios, in which future humans are assumed to inadvertently drill into the repository and bring fuel and radioactive debris to the surface environment, are used for illustrative purposes.Inadvertent human intrusion scenarios where all repository barriers are bypassed often assume no precautions.Evaluations of these scenarios can lead to high estimates of dose consequences, which do not reflect the repository's safety.This paper frames the human intrusion scenario in a way that aligns with national and international guidance and strengthens public understanding of the safety of the repository.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".