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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 OpenAlex
Md Mahbub Uz Zaman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.888
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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