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Record W3083499789 · doi:10.5430/rwe.v11n5p90

Transformation of Industrial Enterprises in the Digital Economy

2020· article· en· W3083499789 on OpenAlexvenueno aff
С. В. Новиков

Bibliographic record

VenueResearch in World Economy · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Development and Digital Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceAutomationDigital economyProcess (computing)Digital transformationTransformation (genetics)Synchronization (alternating current)Industrial organizationProcess managementManufacturing engineeringIndustrial engineeringBusinessEconomic systemEngineeringEconomicsTelecommunicationsOperating systemWorld Wide Web

Abstract

fetched live from OpenAlex

The article is devoted to the analysis of transformation processes of high-tech industrial enterprises operating in the digital economy. It is noted that in the modern economy of Russia the technologies of the third and fourth technological paradigm (TP) prevail, therefore the technologies of the fifth and sixth ones are “high” for it. The structure of the transformation processes of a high-tech enterprise in the framework of the development of digital technologies with the allocation of technological levels of automation of the production process is considered. To optimize the processes of technological transformation, the author proposes to use a modified structure. A characteristic feature of the proposed structure is the presence in it of the so-called “intelligent agents”, which are specialized software modules that are controlled by a special data exchange protocol. Modules also have the ability to implement synchronization mechanisms with business objects and provide the technical ability to integrate three or more different information systems.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.195
GPT teacher head0.296
Teacher spread0.101 · 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 designTheoretical or conceptual
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

Citations5
Published2020
Admission routes1
Has abstractyes

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