MétaCan
Menu
Back to cohort
Record W2997275420 · doi:10.1007/978-94-6265-347-4_15

Possible Means to Overcome Tendencies of the Nuclear Weapons Ban Treaty to Erode the NPT

2020· book-chapter· en· W2997275420 on OpenAlexfundno aff
Stefan Kadelbach

Bibliographic record

VenueT.M.C. Asser Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsNuclear weaponTreatyObligationPolitical scienceArms controlLawDe factoCold warEngineeringInternational tradeBusinessPolitics

Abstract

fetched live from OpenAlex

While the United Nations General Assembly has adopted the text of a ‘Treaty on the Prohibition of Nuclear Weapons’, chances for its implementation are slim. Almost all (declared or de facto ) nuclear-weapon States are planning to enlarge or to modernise their arsenals, and both Russia and the United States have developed postures that revive Cold War scenarios. In such an environment, tendencies eroding the NPT regime must be countered. The most promising option appears to be to advocate for more dialogue and confidence building. Many non-nuclear-weapon States have a vital interest to promote this approach and ought to cooperate in facilitating such a process. The contribution discusses the options under international law of progressive improvement within and outside the new Ban Treaty which might contribute to the obligation to strive for a comprehensive prohibition of nuclear arms.

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: Other
Teacher disagreement score0.013
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0050.006
Open science0.0010.002
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0130.004

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 head0.052
GPT teacher head0.285
Teacher spread0.233 · 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
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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueT.M.C. Asser Press eBooksSame topicNuclear Issues and DefenseFrench-language works237,207