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Manufacturing of Military Products According to Naval Orders by Mining Plants of the Urals at the End of the 18th — First Quarter of the 19th Centuries

2024· article· en· W4399471459 on OpenAlex
А. А. Бакшаев

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHistory and modern perspectives · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMaritime and Coastal Archaeology
Canadian institutionsnot available
Fundersnot available
KeywordsNavyShipbuildingQuarter (Canadian coin)Port (circuit theory)ShipyardState (computer science)EngineeringInvestment (military)Operations researchEconomic historyOperations managementBusinessHistoryArchaeologyPolitical scienceLawComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

The purpose of the research. The article discusses the organization of the implementation of orders of the maritime department by state-owned mining plants in the Urals. Based on materials from federal and regional archives, as well as regulations, the formation of a system for the supply of metals and other products for the fleet at the end of the 18th century is shown. According to the Manifesto of May 21, 1779, only state-owned mining plants were to carry out orders for the army and navy. At the beginning of the 19th century with the approval of instructions for the acceptance of guns, shells and metals from mining plants, a regulatory supply base for army and navy orders is formed. The author is noted that Ural enterprises supplied iron for the needs of shipbuilding and port construction, anchors and cast iron for ballast. In the first quarter of the 19th century the specialization of the region's mining plants in the production of products for the Baltic ports and the Arkhangelsk port took shape. Some of the metals and anchors were sent to the Black Sea ports. With the increase in military threat on the eve and during the Napoleonic wars and the growth of shipbuilding, the volume of orders of the naval department increased. As a result, already in the second decade of the 19th century mining factories could not fully carry out military orders.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.189
Teacher spread0.176 · 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