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Record W2944933713 · doi:10.1080/25751654.2019.1621425

Nuclear Submarines in South Asia: New Risks and Dangers

2019· article· en· W2944933713 on OpenAlexaff
Зиа Миан, M. V. Ramana, A. H. Nayyar

Bibliographic record

VenueJournal for Peace and Nuclear Disarmament · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsUniversity of British Columbia
FundersDefence Research and Development Organisation
KeywordsSubmarineNuclear weaponAeronauticsGovernment (linguistics)Nuclear warfareSoftware deploymentBusinessPolitical scienceInternational tradeEngineeringForensic engineeringLawMarine engineering

Abstract

fetched live from OpenAlex

The South Asian nuclear race is moving to sea, with India’s government announcing that it has successfully put nuclear weapons at sea, and evidence suggesting that Pakistan is preparing to do so. This article traces India’s decision to deploy nuclear-powered submarines, some armed with nuclear weapons, and the debate in Pakistan on the utility of nuclear-armed submarines and the possible acquisition of nuclear-powered submarines. The article then reviews the global history of submarine accidents, especially those where nuclear-powered submarines were involved, and looks in particular at the consequences of a potential naval reactor accident where radioactivity might be released into the environment. Such naval reactor accidents constitute a major but unappreciated challenge associated with the deployment of nuclear submarines in addition to new pathways for escalation to nuclear war that are more widely recognized.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.007
Scholarly communication0.0040.006
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.044
GPT teacher head0.327
Teacher spread0.283 · 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 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

Citations26
Published2019
Admission routes1
Has abstractyes

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