The article provides an overview of the current infrastructure of medical peer-reviewed journals in Russia, and lists the main problems in a historical perspective. The directions of journal development are considered in the context of consolidating the joint efforts of the editorial and publishing community to improve and promote the publications of Russian-speaking authors. The article concludes that the creation of a reliable infrastructure of medical publications will become the basis for the development of equal and fair relations with the editorial and publishing communities of other countries. 

The article presents the analysis of Russian journals whose topics are related to the areas of activity of the Scientific Council on Control Theory and Processes at the Department of Energy, Mechanical Engineering, Mechanics and Control Processes of the Russian Academy of Sciences. Results of a survey of the leading Russian scientists in this field of science, including members of the council, helped to form a preliminary list of journals. The characteristics of these journals and their existing ratings are presented.

It is noted that the well-known scientometric indicators do not allow one to evaluate the journals’ development pathways directly. A proposed indicator characterizes the average rate of change in a journal’s impact factor over a given time interval. The values of development indicators have been calculated and analyzed according to the Russian Index of Science Citation (RISC) and Scopus databases for the abovementioned journals included in these databases. The development pathways of some individual journals are considered.

The article gives conclusions and recommendations that may be useful to the editorial staff – with a view to promoting their publications and to authors – in choosing a journal for publication. 

The impact of artificial intelligence technologies, neural networks, and chatbots on science and education has induced widespread discussion in the academic community. It is no longer possible to contain the use of neural networks such as ChatGPT for writing texts, including scientific texts. The present study is done in a qualitative approach. The aim of the study is to analyze the application of large language models on the example of ChatGPT in the scientific publishing activities of Russian scientists. The practice of using chatbots does not always satisfy the user and the scientific community as a whole. On the one hand, the user is confronted with the lack of the requested information. On the other hand, the scientific community, and especially editors and readers of scientific journals, question the feasibility of neural networks due to the shortcomings of large language models that have been widely disputed in scientific publications. This study shows that there is another reason to distrust neural networks. Incompleteness and opacity of the information produced by artificial intelligence is related to the texts on which neural networks are trained. For Russian science, this problem poses a serious threat, since popular artificial intelligence companies use mostly English-language texts to teach their neural nets. The author puts forward the opinion that the social and humanitarian knowledge produced in modern Russia remains outside the scope of texts used for training neural networks. This point of view is supported by research by Russian scientists on Arctic governance. The data is absent in the English-language texts of ChatGPT but reflected in Russian-language publications. 

The results of the research difference of the calendar date between begining and ending editorial processes in the Journal of “Almaz – Antey” Air and Space Defence Corporation are given, and the counting of dates per month for beginning the processes (entering articles, transferring to literacy editing etc.). Based on the analysis it was concluded that the incoming article might be considered as an incoming application to queuing system, which the scientific journal is. For such incoming application can be estimate the distribution functions incoming flows, average and maximum term be in queuing system, also as the distribution functions of the service mode and another characteristics, which stay unchanged (stationary) in time for researched scientific journal. 

Regression analysis is a rather popular and uncomplicated method of analyzing experimental data. If the results of correlation analysis tell us about the presence of a statistically significant relationship between the studied features, the results of regression analysis represent a graphical description of the nature of this relationship. The article considers the points that authors usually do not pay attention to, but to which the editor should pay attention, and the reviewer simply must do this. Among such points are false predictions, non-Gaussian distribution of residuals, and lack of confidence intervals. 

Professional community recommendations on the content of academic journal websites mostly include criteria for indexing in databases, however these recommendations do not consider the authors’ and reviewers’ perspective on the website contents and design. To address this, we analyzed these recommendations through a survey of 198 Russian academic journal authors and reviewers, using a continuous sampling technique. The survey took place in April and May 2024. The questionnaire was based on the Principles of Transparency and Best Practice in Scholarly Publishing by COPE, DOAJ etc. The survey also focused on the journal website content, design, mobile version, and publication strategy of academic journal website users. We analyzed the survey results for two partially overlapping sets of authors who published in journals indexed in the Web of Science Core Collection, Scopus, and Russian Citation Science Index Core, or in journals listed by the Higher Attestation Commission of Russian Federation. The study revealed that both COPE’s recommendations and users of academic websites value information regarding aims and scope of the journal, copyright fees, review policies, timelines for the editorial and publication process, and licensing. However, Russian authors and reviewers put less emphasis on website sections that address ethical principles and authorship criteria. They prioritize having an online editorial office, security certification, scientific journal indexing and abstracting information, additional educational materials, and the ability to customize the website for devices with different screen sizes. We also discuss the importance of HTML meta tags for promoting the journal’s website. The findings of the research may contribute to promotion of Russian academic journals in international databases, improve the efficiency of communication between authors, reviewers and editors, and develop a set of recommendations that complement international publishing conventions. 

On February 13, 2024, the 99th anniversary of the “Great Russian Encyclopedia” (GRE) (the successor of the “Great Soviet Encyclopedia”) was celebrated. However, it was only in 2020 that work began on the scientific and educational GRE portal, which was launched in test mode on May 26, 2022 (https://bigenc.ru/). By the editorial staff of “Physical Sciences”, to date, about 2,000 articles written by outstanding physicists and selected by the representative Editorial Board have been posted on the portal. The partners of the portal are reputable scientific and educational organizations: the Russian Academy of Science (RAS), Lomonosov Moscow State University (MSU), other leading universities of the Russian Federation, and the Russian Academy of Education. The priorities of the GRE portal are reliability and accessibility. The paper presents statistics of visits to the GRE portal over the past two years. Another important electronic resource dedicated to the physical sciences and therefore analyzed jointly with the editorial board of the GRE “Physical Sciences” is the journal Uspekhi Fizicheskikh Nauk (UFN). The first issue of the UFN was published in April 1918, and the UFN website (www.ufn.ru) was opened on December 26, 1994. Since 1995, there have been statistics of visits to the UFN website, which, for the first time, allowed the UFN Editorial Board to find out how many readers it has, who they are, where they come from, what their interests and preferences are? By 2016, DOI was assigned to the entire archive of articles from the UFN in both Russian and English. By April 2024, 1075 issues of the UFN containing 11,819 articles (cited 164,216 times, data collected by DOI) written by 8,799 authors were posted on the UFN website, and 405,365,547 times visited the semantic pages of the site. Statistics of visits to the UFN website and its features in recent years will be covered in this article.

The statistics of visits to the GRE Portal and the UFN website demonstrate the growing society’s request for reliable, time-tested information supported by the reputation of the editorial board and publishing houses.

The Science Space information and analytical system, developed as an application to the Russian Science Citation Index (RSCI), is used by RSCI user organizations to correct the editorial policy of their publications. However, there is no available information on the extent to which it is effective in measuring journal bibliometric performance. In the proposed article, using the example of the journal Chemical Physics and Mesoscopy, good experience in using the system was found. With its help, over the course of a year, it was possible to find and link about 500 new citations to the journal – approximately 10% of the existing volume.