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Record W7127046962 · doi:10.56700/r0135-8919-1215-m

«Afghan Impasse» of the Islamabad (2021–2023)

2024· article· W7127046962 on OpenAlexaboutno aff
Н.А. ЗАМАРАЕВА

Bibliographic record

Venuenot available
Typearticle
Language
FieldSocial Sciences
TopicSecurity, Politics, and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Government (linguistics)Quarter (Canadian coin)Population

Abstract

fetched live from OpenAlex

Я присоединяюсь к благодарности коллег за приглашение, за столь высокую трибуну. И искренне благодарна, конечно, и это честь для нас — присутствие афганских друзей в Москве. Пакистан и Афганистан имеют много общего за последние 40 лет с точки зрения силового захвата власти. Исламабад приветствовал возврат афганских талибов в августе 2021 года, возлагая большие надежды на установление давно ожидаемых дружественных отношений. Представители генералитета Пакистана одними из первых приехали с визитом в Кабул. Представлялось, что это был один из переломных периодов в пакистано-афганских отношениях. I want to thank you for participation. I want to thank our guests from Afghanistan for coming to Moscow. Pakistan, and Afghanistan have a lot in common in the nearest 40 years in terms of seizure of power. Islamabad welcomed the return of Talibs in 2021. And it relied on the anticipated friendly relations, as the representatives of generals of Pakistan were one of the first to come to Kabul, and it was one of the crucial moments in Pakistani-Afghani relations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.004

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 head0.023
GPT teacher head0.313
Teacher spread0.290 · 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 designObservational
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

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