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On the Design Features of Russian Chests (16th — the First Quarter of the 20th Century)

2023· article· en· W4378212913 on OpenAlexaboutno aff
Gleb A. Pudov

Bibliographic record

VenueObservatory of Culture · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
Fundersnot available
KeywordsCraftQuarter (Canadian coin)Quality (philosophy)HistoryProduction (economics)Archaeology

Abstract

fetched live from OpenAlex

Chest has been used by man for centuries. It served not only as a storage container for documents, valuables, dowry, but also as a table, bed and bench. Throughout the history of Russian chest craft, several basic designs have developed. Despite the importance of the problems and questions related to the design features of the Russian chest, no special research was devoted to them. Information found in the literature is sketchy, and the sources give only the basis for assumptions. The purpose of this article is to identify and analyze the main designs that existed in the Russian chest production. The main tasks include: the introduction of new information into scientific circulation and the analysis of specific works. The research material involved works from the collection of the State Russian Museum and other museums. Chronological framework of the study is from the 16t through the first quarter of the 20th centuries. This is explained by the fact that the first Russian preserved chests dated back to the 16th century, and beginning with the first quarter of the 20th century, mechanization of production had become increasingly growing in the chest craft, which resulted in a significant decrease in the quality of products. The author comes to the following conclusions: there were four main designs in Russian chest production – sarcophagus, frame-panel (as a variant of the first), ‘dovetail’ and manufacture; there was a dependence of the design of chests on the forms of production organization; the design of the chest can currently be only an additional attributing feature; the repertoire of designs to which European masters applied, was richer than accepted in the Russian chest craft.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.267
Teacher spread0.219 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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