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ПРОБЛЕМЫ ПОСТАВОК МЕТАЛЛОВ ДЛЯ ОРУЖЕЙНЫХ ЗАВОДОВ КАЗЁННЫМИ ГОРНЫМИ ЗАВОДАМИ УРАЛА В КОНЦЕ XVIII - ПЕРВОЙ ЧЕТВЕРТИ XIX ВЕКА

2025· article· ru· W4415695336 on OpenAlexaboutno aff
Александр Алексеевич Бакшаев

Bibliographic record

VenueBulletin of Udmurt University Series History and Philology · 2025
Typearticle
Languageru
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
Fundersnot available
KeywordsArtilleryFactory (object-oriented programming)Quarter (Canadian coin)First world warWorld War II

Abstract

fetched live from OpenAlex

В статье показаны трудности в выполнении нарядов оружейных заводов казёнными горными заводами Урала в конце XVIII - первой четверти XIX вв. Источниками исследования послужили материалы федеральных и региональных архивов, описания оружейных предприятий, составленные артиллерийскими офицерами, а также нормативные акты. Отмечается, что горные заводы региона с XVIII в. снабжали металлом оружейные заводы, а в начале XIX в. они становятся основным поставщиком сырья для изготовления огнестрельного оружия. Показано, что значительное количество бракованного железа вызывало нарекания военного ведомства и привело к созданию специальных комитетов, которые изучили причины производства некачественного металла. Горное ведомство в ответ обвиняло в изготовлении бракованного оружия оружейных мастеров. Одной из причин поступления на оружейные заводы ствольного железа низкого качества были нечёткие требования к его приёмке, зафиксированные в инструкции 1804 г. В итоге, в изучаемый период так и не удалось получить железо нужного качества для заварки стволов. Горные заводы накапливали задолженности перед оружейными предприятиями, выполняя наряды не в полном объёме. The article shows the difficulties in the implementation of weapons factory orders by the state-owned mining plants of the Urals in the late 18 - first quarter of the 19 centuries. The sources of the study were materials from federal and regional archives, descriptions of weapons enterprises compiled by artillery officers, and regulatory acts. The author notes that the mining plants of the region supplied weapons factories with metal from the 18 century, and in the early 19 century they became the main supplier of raw materials for the manufacture of firearms. The author shows that a significant amount of defective iron caused complaints from the military department and led to the creation of special committees that studied the causes of low-quality metal production. The mining department, in turn, blamed weapons masters for the production of defective weapons. One of the reasons for the receipt of low-quality barrel iron at the weapons factories was the unclear requirements for its acceptance, recorded in the instructions of 1804. As a result, during the studied period, it was not possible to obtain iron of the required quality for welding barrels. Mining plants accumulated debts to weapons factories, not fulfilling orders in full.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0190.001

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 head0.015
GPT teacher head0.202
Teacher spread0.187 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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