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Application of Copper Coatings onto Used-Fuel Canisters for the Canadian Nuclear Industry

2016· book-chapter· en· W4234913661 on OpenAlexaffabout
Phuong Vo, Dominique Poirier, J.-G. Legoux, Éric Irissou, Peter Keech

Bibliographic record

VenueASM International eBooks · 2016
Typebook-chapter
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsNuclear Waste Management OrganizationNational Research Council Canada
Fundersnot available
KeywordsCoatingCopperMaterials scienceMetallurgyRadioactive wasteSpent nuclear fuelCorrosionScale (ratio)EngineeringWaste managementComposite materialGeography

Abstract

fetched live from OpenAlex

Abstract The Nuclear Waste Management Organization (NWMO) investigates approaches for managing Canada's used nuclear fuel. As part of a larger program investigating concepts of copper coatings, NWMO has begun exploring copper cold spray in collaboration with the National Research Council. Within the coating program, a large variety of copper coating sizes have been investigated, from small corrosion coupons to full-scale used-fuel containers/canisters (UFCs). This chapter demonstrates the successful application of copper coating technology to full-scale geometric representative Mark II UFC mock-up configurations through activities involving powder selection, general coating development, UFC coating optimization, and prototyping.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score0.368

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.232
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations10
Published2016
Admission routes2
Has abstractyes

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