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Towards modern railroads

2022· article· en· W4311161463 on OpenAlexaboutno aff
A. B. Voulfov

Bibliographic record

VenueTransport Technician Education and Practice · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsTicketContext (archaeology)Quarter (Canadian coin)State (computer science)Economic historyWorld War IIHistoryEngineeringArchaeologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

The historical events that predetermined the current state of domestic railways in the context of the daily life of compatriots are described. It is emphasized that, having given birth to a new tradition of messages, the Russians have created a new system of relations with the world. The railroad played a leading role in this and has a long and honorable history. The railway, the famous Russian cast-iron, has a long and honorable history. They gave a huge impetus to the development of mail and telegraph (the telegraph was already on the first highway St. Petersburg — Moscow, Tsar Nicholas expressed the liveliest interest in it, asked the telegraph operator to find out the weather in St. distance. Subsequently, the appearance of the cast iron changed: a contact network with a walking row of poles, modern locomotives and wagons, reinforced concrete sleepers, standard structures came to it, a train ticket can be taken without leaving home — this is inevitable and correct. In 1988, the railways of the USSR carried a quarter of the world freight turnover. Without railways, one cannot imagine the history and fate of the Russian state, and literally in all areas of its life.

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)0.002
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 score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.005

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 head0.031
GPT teacher head0.348
Teacher spread0.317 · 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
Published2022
Admission routes1
Has abstractyes

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