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IMPROVING THE BARREL IRON PRODUCTION IN THE URAL MINING PLANTS IN THE SECOND QUARTER OF THE 19TH CENTURY

2025· article· en· W4414208290 on OpenAlexaboutno aff
А. А. Бакшаев

Bibliographic record

VenueUral Historical Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsBarrel (horology)Production (economics)Quarter (Canadian coin)Precious metalQuality (philosophy)Nonferrous metalPeacetime

Abstract

fetched live from OpenAlex

The article, based on materials from federal and regional archives, describes the problems in the production of iron for gun barrels in the Ural mining plants in the second quarter of the 19th century. It is noted that the mining industry enterprises have been supplying the weapons factories with metal since the 18th century. Despite the approval in the early 19th century of regulatory acts defining the requirements for the properties and dimensions of iron, and quality control by representatives of the military department, no special rules for its acceptance have been developed. The lack of clear verification requirements led to the fact that weapons factories received a significant amount of iron of unsatisfactory quality, unsuitable for gunsmiths to weld barrels. As a result, the amount of defective metal increased, and the debt of mining plants to the military department grew. The mining and military departments began to pay attention to the problem of improving the barrel iron production in the 1820s. Special committees of representatives from both departments developed rules for testing iron, but they were not included in the new instructions for accepting military products from mining plants in 1831. Their development dragged on until the mid-1840s. Improvements in the technology for barrel iron production were made through experiments conducted by both the military department and the Ural mining plants. As a result, during the period under study, it was not possible to obtain iron suitable for weapons factories.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

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 studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.172
Teacher spread0.167 · 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
Published2025
Admission routes1
Has abstractyes

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