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Record W2507496341

Management Tools of Cost Controlling at the Gas Transportation Enterprise

2016· article· en· W2507496341 on OpenAlexvenueno aff
Vera Vladimirovna Plenkina, А. Taubayev, Olga Viktorovna Lenkova

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEconomic, Social, and Public Health Issues in Russia and Globally
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceHierarchyEnterprise managementPoint (geometry)Management scienceEnterprise softwareProcess managementRisk analysis (engineering)Knowledge managementBusinessEngineering
DOInot available

Abstract

fetched live from OpenAlex

The importance of controlling in modern conditions is defined. A brief overview of the main evolutionary stages in the development of the theory and methodology of controlling is provided. The expediency of projection of the concept of controlling on the cost management system at the gas transportation enterprise is justified. The paper points at the grouping of controlling methods in general scientific methods, methods of a number of individual sciences, and specific methods, which are offered to divide into general management methods and methods of cost controlling. The author’s systematization of enterprise-wide management tools of controlling is provided, depending on the most significant areas of activity of the enterprise, management functions, levels of the management hierarchy and the nature of implemented targeted enterprise systems. The cost management methods are structured by management functions and stages of production and sales. The authors point at the predominant classification of each method into strategic and operational tools. The recommendations for further practical use of the presented systematization are provided.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.005
Science and technology studies0.0010.002
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.062
GPT teacher head0.349
Teacher spread0.288 · 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 designObservational
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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Internet Banking and CommerceSame topicEconomic, Social, and Public Health Issues in Russia and GloballyFrench-language works237,207