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Record W2907614798

ОРГАНИЗАЦИЯ ТРАНСПОРТИРОВКИ ПРОДУКЦИИ КАЗЁННЫХ ГОРНЫХ ОКРУГОВ УРАЛА В ПЕРВОЙ ПОЛОВИНЕ XIX ВЕКА

2018· article· ru· W2907614798 on OpenAlexaboutno aff
Бакшаев Александр Алексеевич

Bibliographic record

VenueВестник Удмуртского университета. Серия «История и филология» · 2018
Typearticle
Languageru
FieldPhysics and Astronomy
TopicElectrical and Electromagnetic Research
Canadian institutionsnot available
Fundersnot available
KeywordsDestinationsState (computer science)Quarter (Canadian coin)BusinessNavyTourismEconomyGeographyArchaeologyEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The article considers the delivery of products of state-owned metallurgical works in the Urals to consumers in the first half of the 19 century. Based on a complex of published sources (historical and statistical descriptions, materials of the Mining Journal), as well as archival documents, the author concludes that the state mining districts produced metals mainly for the Military and the Navy Department for the needs of arms enterprises, arsenals and seaports in various regions of the Russian Empire. Metals and products of state enterprises were delivered by land and water. Within districts, the products were transported by land to state piers on local roads. Due to the poor condition of the road network inside the state districts, transportation was carried out in winter. In spring, in state caravans, the products were floated to destinations in Central Russia. The author notes that the delivery of products by water was carried out mainly by the resources of the Mining Department under the supervision of the caravan inspectors, who were subordinate to the staff of officials and employees. In the first quarter of the 19 century, the state used the services of private contractors for the transportation of products to piers and their rafting to destinations. As a result, the imperfection of the transport system of the region, its remoteness from the main sales areas led to an increase in the cost of products of state-owned works. The time of delivery of military products to the destinations increased, which led to violations of the deadlines for the performance of 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.

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)0.002
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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
Published2018
Admission routes1
Has abstractyes

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Same venueВестник Удмуртского университета. Серия «История и филология»Same topicElectrical and Electromagnetic ResearchFrench-language works237,207