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Record W4323046538 · doi:10.1080/10402659.2023.2185509

A Framework for Assessing Nuclear Terrorism Threats in Bangladesh

2023· article· en· W4323046538 on OpenAlexaff
Md Mahbub Uz Zaman

Bibliographic record

VenuePeace Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTerrorismNuclear terrorismNuclear weaponEnergy securityNational securityComputer securityNuclear ethicsBusinessPolitical scienceInternational tradeLawEngineeringComputer science

Abstract

fetched live from OpenAlex

We live in a world where thousands of nuclear weapons exist. Many countries and even terrorist organizations want to acquire nuclear weapons. The ambiguous and transnational nature of terrorist organizations challenges the national security of many states. Bangladesh is a small and densely populated country with a nuclear energy plant. Although Bangladesh has a nuclear energy policy, it has no atomic security policy or legal framework. The dearth of military capabilities, administrative facilities, and human resources with proper skills and experiences makes Bangladesh vulnerable to nuclear terrorist attacks. This research aims to build a framework that would be useful in assessing the security threats from the likelihood of nuclear terrorism in a country like Bangladesh. This nuclear security assessment framework could be useful in assessing security threats from nuclear terrorism in non-nuclear-weapon countries.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.005
Science and technology studies0.0020.005
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.105
GPT teacher head0.432
Teacher spread0.327 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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