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Record W3177355011 · doi:10.30853/mns210166

Battle Painting as Historical Document. Specificity of A. E. Kotzebue’s Creative Method

2021· article· en· W3177355011 on OpenAlexaboutno aff
Dmitry Vladimirovich Lyubin

Bibliographic record

VenueManuscript · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCentral European and Russian historical studies
Canadian institutionsnot available
Fundersnot available
KeywordsBattlePaintingQuarter (Canadian coin)Context (archaeology)OriginalityThe artsVisual artsArtArt historyLiteratureHistoryAncient historySociologyArchaeologySocial scienceQualitative research

Abstract

fetched live from OpenAlex

The paper aims to reveal specificity of the creative method of the prominent but undeservedly forgotten Russian battle painter A. E. Kotzebue in the context of the Russian and foreign academic battle painting of the half - third quarter of the XIX century. Scientific originality of the study lies in the fact that relying on previously unpublished documentary sources, the researcher identifies common and peculiar features of Kotzebue’s creative method in the context of the Russian and foreign academic battle painting of the half - third quarter of the XIX century. As a result, it is proved that A. E. Kotzebue’s creative method was developed during his studies at the Imperial Academy of Arts and didn’t change over the course of his life; this method was typical of academic battle painting of the half - third quarter of the XIX century. Adherence to established methods allowed the painter to create pictures which can rightfully be called historical documents.

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)0.005
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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.011
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.042
GPT teacher head0.306
Teacher spread0.264 · 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
Published2021
Admission routes1
Has abstractyes

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