MétaCan
Menu
Back to cohort

Bystrova, Nina E. ‘Russkii vopros’ v 1917 - nachale 1920 g.: Sovetskaya Rossiya i velikie derzhavy. Moscow: Institut rossiiskoi istorii RAN, Tsentr gumanitarnykh initsiativ, 2016. 368 p

2019· article· en· W2918474973 on OpenAlexaff
David Schimmelpenninck van der Oye, S.A. Mironyuk

Bibliographic record

VenueRUDN Journal of Russian History · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and Russian Geopolitical Military Strategies
Canadian institutionsBrock University
Fundersnot available
KeywordsDiplomacyPolitical scienceFront (military)Economic historyHumanitiesRussian revolutionNarrativePeriod (music)HistoryLawArtGeographyPoliticsLiterature

Abstract

fetched live from OpenAlex

Long dismissed as the "forgotten war", Russia's involvement in the World War I is fi nally getting the attention it deserves.This renewed interest in the confl ict, resulting from many commemorations and conferences, not to mention freer access to the archives, has also done much to make the Eastern Front an important part of the Great War's broader narrative.The same is true of Russian diplomacy during the period.It is against that background that the international "Russia's Great War and Revolution" project of has produced a two-volume collection devoted to Russia's foreign aff airs from 1914 to 1921.'Russkii vopros' v 1917 -nachale 1920 g.: Sovetskaya Rossiya i velikie derzhavy [The 'Russian Question' from 1917 to the beginning of 1920: Soviet Russia and the Great Powers], the new book by Dr.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.004
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0130.007

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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueRUDN Journal of Russian HistorySame topicEuropean and Russian Geopolitical Military StrategiesFrench-language works237,207