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Record W2603723954

ORGANIZATIONAL AND ECONOMIC MECHANISM OF OIL AND GAS PROJECTS IN THE RUSSIAN ARCTIC SHELF

2016· article· en· W2603723954 on OpenAlexvenueno aff
Anni Nikulina, Marina Nikolaevna Kruk

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticMechanism (biology)Investment (military)The arcticFossil fuelBusinessPoliticsRussian federationPetroleumEnvironmental economicsIndustrial organizationEconomicsEconomic policyPolitical scienceGeologyOceanographyEngineeringWaste management
DOInot available

Abstract

fetched live from OpenAlex

Authors of the paper prove the need of development of the organizational and economic mechanism of development of oil and gas fields in the Arctic shelf of the Russian Federation. The organizational and economic mechanism of oil and gas projects in the Russian Arctic should take into account strategic issues of oil and gas sector of Russia. It must be a universal algorithm of the choice of the investment scheme for development of oil and gas fields in the Arctic shelf. This mechanism should also estimate efficiency of participation for all concerned parties. The mechanism provided by authors includes evaluation of public, commercial and budget effectiveness, evaluation of social, economic, political and innovative effects, quality evaluation of the offered investment schemes and also evaluation of impact of oil and gas projects on the main involved participants – stakeholders.

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)0.004
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.021
GPT teacher head0.269
Teacher spread0.249 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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