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Record W4405943646 · doi:10.18822/edgcc643554

Analytic review of the first 15 years of journal functioning

2024· article· en· W4405943646 on OpenAlexaff
Oleg Alekseevich Frolov, M. V. Glagolev, Irina Terentieva

Bibliographic record

VenueEnvironmental Dynamics and Global Climate Change · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPublishingScarcityPolitical scienceClimate changeLibrary sciencePublic relationsEcologyComputer science

Abstract

fetched live from OpenAlex

This article reviews the activities of the journal Environmental Dynamics and Global Climate Change (EDGCC) over the 15 years since the publication of its first issue. The journal aims to inform interested readers about scientific and educational developments within the themes of "Environmental Dynamics" and "Global Climate Change." The main objectives of the journal include: Publishing scientific papers, reviews and discussions addressing topics related to the composition, structure, and functioning of natural and anthropogenically disturbed systems under the climate change. Informing about the main results of scientific work carried out within priority areas of research in university, academic and industry sciences on the Earth and the environment Fostering open scientific dialogue to improve the quality of research. Promoting national and international best practices in applying cutting-edge technologies. The journal accepts papers in both Russian and English. Submissions may include methodological, theoretical, and experimental works, ranging from regionally focused and federally funded projects to independent research yet to receive formal grant support. Recognizing the scarcity of high-quality Russian-language reviews in certain areas of global ecology and climatology, the journal also welcomes reviews and lectures by leading scientists to fill this gap. Papers undergo a double-blind peer review process, typically involving three reviewers who evaluate manuscripts anonymously without knowledge of the authors or their affiliations. This article presents scientometric data on the publication activity of EDGCC, along with an analysis of materials deemed most useful to readers. In addition to the review of the last 10 years published previously, this article evaluates the journal's performance over the past five years. It highlights changes in publication format, particularly the shift to electronic-only articles, and their impact on key metrics. Papers with the highest reader engagement (measured by website views and citations) are identified. The analysis reveals that theoretical studies attract the greatest interest, followed closely by experimental works. Notably, a “Discussion” paper achieved the fastest citation rate, while a "Chronicle" paper recorded the highest number of abstract views in the past five years. The journal's two-year impact factor has remained stable over the last five years, achieving competitive results compared to 27 peer journals with similar themes, where our regular contributors publish frequently. The number of authors publishing in EDGCC has remained consistent, averaging 16 authors annually, with approximately 50% being new contributors each year. A trend of increasing article half-life is observed over the past decade. The average h-index of EDGCC authors has shown an upward trend over time. In terms of "probability of citation after reading," EDGCC ranks third among the analyzed journals.

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)0.074
metaresearch head score (Gemma)0.352
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0740.352
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0400.036
Science and technology studies0.0040.004
Scholarly communication0.0220.011
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.004

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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.

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
Published2024
Admission routes1
Has abstractyes

Explore more

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