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Record W4403270777 · doi:10.21544/2359-3075.301100

Safeguards and nuclear- powered submarines a model for special procedures on the nuclear fuel cycle

2024· article· en· W4403270777 on OpenAlexaboutno aff
Marcos Valle Machado da Silva

Bibliographic record

VenueRevista da Escola de Guerra Naval · 2024
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear fuel cycleNuclear engineeringEngineeringAeronauticsEnvironmental scienceSystems engineeringFuel cycle

Abstract

fetched live from OpenAlex

This article focuses on the safeguards provided by the International Atomic Energy Agency (IAEA) and how to apply them to nuclear fuel used by nuclear-powered submarines (SSN) developed by a Non-Nuclear-Weapon State (NNWS).Brazil is developing its own SSN, and Australia -supported by the AUKUS partnership -will also operate an SSN around 2030.Countries such as the Republic of Korea, Iran, and Canada have already shown current or past interest in SSN.In this context, it is worth thinking about models to conciliate the safeguards provided by the IAEA and the development and operation of an SSN by an NNWS.The article presents a model in three steps.Firstly, it focuses on the normative framework of the IAEA on this issue.Secondly, it addresses the methodology and structure of the model.The last section presents the model building for each phase of the nuclear fuel cycle.The research outcome was the development of a model, structured following the nuclear fuel cycle, that combines four variables -NNWS interests, proliferation risks, safeguards, and possible key points of application of safeguards.This methodological approach makes the model unique and points out a future pathway of negotiation between the IAEA and an NNWS with an SSN program.

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 score0.659
Threshold uncertainty score0.746

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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