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Record W7057287267

THE INITIAL STAGE OF THE FORMATION OF THE BLACK SEA ARMY IN THE BUGO-DNISTROV MEASURE

2023· article· en· W7057287267 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy · 2023
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianStage (stratigraphy)Black seaQuarter (Canadian coin)State (computer science)Cold war
DOInot available

Abstract

fetched live from OpenAlex

The need for mobile fearless units that could oppose the Ottoman army in the last quarter of the 18th century contributed to the formation of an irregular formation from former Zaporizhia, which was later called the Black Sea Army. The army created for participation in the Russian-Turkish war of 1787–1791 left a noticeable mark in the history of the southern Ukrainian region, both in its military and socio-economic history. This article, written on the basis of the analysis of unpublished and published documents by I. Dmytrenko, P. Korolenko and other researchers of the State Archives of the Krasnodar Territory, highlights the process of gathering former Zaporizhia by volunteers from across the Danube and various corners of the Ochakiv Steppe. The author drew attention to the problems that arose during the formation of the army and the benefits that were "generous" to Catherine II.

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)0.000
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.004
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.083
GPT teacher head0.332
Teacher spread0.250 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueThe Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogySame topicHigh voltage insulation and dielectric phenomenaFrench-language works237,207