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Record W1955296848 · doi:10.1787/9789264013810-10-en

Research and Development on Accelerator-Driven Systems

2006· book-chapter· en· W1955296848 on OpenAlexaboutno aff
V. P. Bhatnagar, S. Casalta, M. Hugon

Bibliographic record

VenueNuclear Science · 2006
Typebook-chapter
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear transmutationWork (physics)Radioactive wasteActinideEngineeringNuclear engineeringEnvironmental scienceNuclear physicsWaste managementPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

A fast subcritical reactor coupled to a particle accelerator is a concept of transmutation system that would allow large quantities of minor actinides to be burned efficiently. The research on transmutation encompassing accelerator-driven systems (ADS) is a part of the EURATOM research and development programme that lies within the area of partitioning and transmutation (P&T) of long-lived radionuclides in nuclear waste. P&T is one of the most notable research areas of the EURATOM Fifth (1998-2002) as well as the Sixth (2002-2006) Framework Programmes (FP). The objective of the research work in this area is to determine practical ways of reducing the amount and/or hazard of the waste to be disposed of. In FP5, there are 13 projects in this area with a total budget of about 69 M€ EU contribution is about 28 M€ In FP6, the research in this area, with a EU contribution of about 30 M€, strengthens the work that has been carried out in FP5 with a view to building a European Research Area (ERA) in this field. This has lead to integrating all EU activities on partitioning into one integrated project, and the same is planned for the transmutation activities. Moreover, a targeted project concerning the impact of P&T on waste management has also been initiated. International co-operation in the area of P&T with non-EU countries (such as Canada, USA and Japan), including the Commonwealth of Independent States (CIS) is also outlined.

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: Other · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.847

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 integrity0.0000.001
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 head0.053
GPT teacher head0.247
Teacher spread0.194 · 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
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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