DEVELOPMENT OF VERY LOW-LEVEL RADIOACTIVE WASTE SEQUESTRATION PROCESS CRITERIA
Bibliographic record
Abstract
Segregating radioactive waste at the source and reclassifying radioactive waste to lower waste classes are the key activities to reduce the environmental footprint and long-term liability. In the Canadian Standards Association’s radioactive waste classification system, there are 2 sub-classes within low-level radioactive waste: very short-lived radioactive waste and very low-level radioactive waste (VLLW). VLLW has a low hazard potential but is above the Canadian unconditional clearance criteria as set out in Schedule 2 of Nuclear Substances and Devices Regulations. Long-term waste management facilities for VLLW do not require a high degree of containment and isolation. In general, a relatively low-cost near-surface facility with limited regulatory control is suitable for VLLW. At Canadian Nuclear Laboratories’ Chalk River Laboratories site an initiative, VLLW Sequestration, was implemented in 2013 to set aside potential VLLW for temporary storage and to be later dispositioned in the planned VLLW facility. As of May 2015, a total of 236 m 3 resulting in approximately $1.1 million in total savings have been sequestered. One of the main hurdles in implementing VLLW Sequestration is the development of process criteria. Waste Acceptance Criteria (WAC) are used as a guide or as requirements for determining whether waste is accepted by the waste management facility. Establishment of the process criteria ensures that segregated waste materials have a high likelihood to meet the VLLW WAC and be accepted into the planned VLLW facility. This paper outlines the challenges and various factors which were considered in the development of interim process criteria.
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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".