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Record W3168953876 · doi:10.1051/e3sconf/202127001023

Conceptual foundations of legal support for engineering in Arctic studies of climatic changes

2021· article· en· W3168953876 on OpenAlexaboutno aff
Nikolay Makhonko, Sergey A. Belousov, Е. А. Тарасова

Bibliographic record

VenueE3S Web of Conferences · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArcticGeopoliticsEnvironmental resource managementLegislationPolitical scienceThe arcticEnvironmental planningGeographyEcologyEnvironmental scienceLaw

Abstract

fetched live from OpenAlex

The article is devoted to the problems of the development of the Arctic as a territory of international cooperation, taking into account the national interests of individual states. The specificity of geopolitical, social, economic, and climatic conditions determines the need to develop conceptual foundations of legal support for the implementation of environmental engineering processes at the development of the Arctic and research on climatic changes of the region. The article analyzes the main strategic and legal documents regulating the implementation activities in relation to the technical and technological support in the question of the development of the Arctic territories and the preservation of climatic stability. The options for creating an adequate system of convergence of national and international legal regulation in the field of determining anthropogenic pollutants and fixing key indicators of the state of the Arctic environment are detailized and characterized. The scientific substantiation of the causes and consequences of climate change in the Arctic ecological systems is given. The advantages of scientific research with the use of modern engineering and digitalization methods, as well as the usage of information and communication technologies for the prompt exchange of environmentally significant information, are revealed. It is noted that thе most topical issues, the national strategies for the development of the Arctic zones of the Russian Federation, Denmark, Norway, and Canada are of a similar nature. They have common approaches to the preservation of vulnerable Arctic ecological systems and the conceptual foundations of legal support for engineering in Arctic scientific research in the field of climate change and conservation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.911
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

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

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 head0.107
GPT teacher head0.380
Teacher spread0.273 · 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 teacher head, 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

Citations0
Published2021
Admission routes1
Has abstractyes

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