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Record W2279038543

Денежная система малороссийской части Брянщины. Xvii - начала xviii вв

2011· article· ru· W2279038543 on OpenAlexaboutno aff
В. М. Пусь

Bibliographic record

VenueВЕСТНИК Брянского государственного университета · 2011
Typearticle
Languageru
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsCurrencyCirculation (fluid dynamics)Quarter (Canadian coin)Ancient historyGeographyHistoryEconomic historyEconomicsArchaeologyEngineering
DOInot available

Abstract

fetched live from OpenAlex

XVII начала XVIII вв. произошло окончательное становление российской денежной системы на Стародубщине.The currency system of the malorosia part of the Bryansk region of the XVII-XVIII centuries is conditionally divided in several periods. In the beginning of the XVII century the Russian currency system spread out over that territory. The currency circulation of the malorosia part of the Bryansk region (1618-1648) was actually Polish-Lithuanian. Features of the currency circulation (1648 1685) were conditioned by political events running in that area.In the middle of the third quarter of XVII century the prevailing value of the currency system still belonged to Rech Pospolitaya but starting from 1860 coins of Russian state appeared. Those were russian copper kopecks and efimok with a sign. From the 80-s of XVII to the beginning of XVIII the definitive formation of the Russian currency system was established in Starodubsky region.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0330.009

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 head0.108
GPT teacher head0.283
Teacher spread0.175 · 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
Published2011
Admission routes1
Has abstractyes

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