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Record W2985704013

The Arctic Countries’ Supply Chain Strategies in The Context of Arctic Territory Delimitation

2019· article· en· W2985704013 on OpenAlexaboutno aff
Isabella D. Elyakova, Roman Dmitrievich Sleptsov, А А Пахомов, Alexandr Lvovich Elyakov, Darya Victorovna Tumanova

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticContext (archaeology)The arcticUnited Nations Convention on the Law of the SeaOrder (exchange)Political scienceGeographyState (computer science)Supply chainEconomyConventionBusinessOceanographyEconomicsLawComputer scienceGeologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The article discusses the supply chain strategies of the so-termed Arctic Five – the Russian Federation, Canada, the USA, Norway and Denmark, which have borders in the Arctic in the context of the search for their common goals and objectives in order to develop possible ways and means to solve the main common problem – the territory delimitation in the Arctic between these countries. Much has been written about the legal methods of maritime delimitation in the Arctic, but their essence is to compare the principles of “Sectoral division” in the Arctic with the norms of the 1982 “United Nations Convention on the Law of the Sea”. Meanwhile, the current international situation and the current state of the Arctic countries in relation to each other in the sphere of military power, economy, science and climate change in the Arctic, force us to consider the issue of territory delimitation in the Arctic in an extensive aspect.Â

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 score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.001
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 head0.020
GPT teacher head0.295
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
Published2019
Admission routes1
Has abstractyes

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