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Record W2346219913 · doi:10.12943/cnr.2015.00052

DEVELOPMENT OF VERY LOW-LEVEL RADIOACTIVE WASTE SEQUESTRATION PROCESS CRITERIA

2015· article· en· W2346219913 on OpenAlexaffvenueabout
Nicholas Chan, P.C.F. Wong

Bibliographic record

VenueAECL Nuclear Review · 2015
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsRadioactive wasteWaste managementContainment (computer programming)Environmental scienceInterimMixed wasteEngineeringComputer science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.296
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes3
Has abstractyes

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