[Purposes] This article aims to analyse the construction and development model of journal group of the “AME Publishing Company (AME)”, hoping to provide a reference for the clusterization, internationalization development and knowledge service platform construction of English journals in China. [Methods] 63 English medical scientific and technical journals of AME were referred to as research objects. The data on journal publication, publishing cooperation, editorial board construction, database inclusion, digitalization construction, etc., were collected. Additionally, the publication mode, clustered development, experience, and lesson of AME were analyzed and summarized by bibliometrics method. [Findings] By focusing on multidisciplinary collaboration, keeping abreast with the trends in medical fields, consolidating digital platforms, improving publishing service, and building the journals from strength to strength, AME has established a certain level of influence and recognition in the medical academic publishing field and formed a certain brand effect. AME has become a significant force in the academic publishing field. But there was still room for improvement in the evaluation and supervision for the operation of journals. [Conclusions] A relatively complete profile of journals and a mature and professional operation system have been created by the AME Publishing Company. Furthermore, this publisher has built a mature and sustainable English journal incubation platform.

[Purposes] This paper aims to explore the characteristics of pre-review within 24 h (24 h review) and the differences between 24 h review and traditional publishing model of scientific journals, and thus provide a reference for optimizing the publishing model and promoting the development of the scientific journals in China. [Methods] We systematically compared the differences between 24 h review and multi-journal submission (MJS) model put forward by Cell Press, and summarized the characteristics, advantages, and shortcomings of 24 h review model, based on the online research. [Findings] The traditional publishing model adhered to the principle of “single submission”. In contrast, the MJS model in Cell Press allows for simultaneous submissions to multiple journals. 24 h review model adopts a “5 min submission + 24 h feedback” mode to achieve synchronous pre-review across multiple journals, with a decision on whether the manuscript would be submitted for peer review within 24 h. The 24 h review model is characterized by rapid feedback and clustering management. It can significantly improve the submission efficiency and authors’ experience, and strengthen the collaboration and influence of the journal cluster. Meanwhile, higher requirements of the publishing process, the management of publishers, and the professionalism of the editors were proposed. [Conclusions] The scientific journals in China can benefit from 24 h review model, which can enhance the overall competitiveness of journal clusters by cultivating the multi-skilled editors for mulitple journal collaboration, integrating publishing resources, and developing a talent echelon.

Purposes To analyze the bibliometric characteristics of journals selected for the Phase II of “Excellence Action Plan of China’s STM Journals” （hereinafter referred to as “Excellence Action”）， explore strategies to promote the high-quality development of China’s STM journals based on these findings. Methods Based on bibliometric indicator data from the 2024 Edition of the Chinese Science and Technology Journal Citation Report （Core Edition） （Chinese journals） and the SCI Journal Citation Report （JCR） （English journals）， we conducted statistical analysis on the Chinese and English journals selected for Phase II of “Excellence Action”（including leading journals and tiered journals）. Additionally， we compared and analyzed the trends in relevant indicators for journals that received funding in the first phase but were not selected for the second phase. Combining project application and evaluation requirements （project planning feasibility， academic influence， editorial team， publishing operations， and dissemination capabilities）， we conducted a comprehensive discussion combining quantitative and qualitative analysis. Findings The overall funding rates for Chinese and English journals selected for the second phase of the “Excellence Action” were 35.1% and 50.4%， respectively. Quantitative indicators such as comprehensive evaluation metrics and impact factor were not decisive factors in determining whether a journal was selected. The selected Chinese and English journals were highly concentrated in the three major administrative units of the Chinese Academy of Sciences， the China Association for Science and Technology， and the Ministry of Education （72.5% for Chinese journals and 78.5% for English journals） as well as in research-strong provinces/cities such as Beijing and Shanghai. Conclusions The selection results of the second phase of the “Excellence Action” reflect a comprehensive orientation that balances quantitative indicators and qualitative assessments. The selection philosophy and practices of the “Excellence Action” provide important insights for China’s efforts to build world-class STM journals. Future high-quality development of scientific journals requires a focus on and strengthening of initiatives such as scholar-led journal publishing， leveraging academic leadership， balancing publication scale with academic quality， enhancing editorial and publishing service capabilities， and strengthening sustainable development and platform construction.

[Purposes] To establish a journal policy framework and documents in line with international standards and can be referred to by independently established China’s English scientific journals, in order to enhance the recognition of the China’s journal quality in the international academic publishing community. [Methods] By collecting the selection criteria of important databases such as WoS and Scopus, the recommendations and guidelines of main international academic publishing organizations such as COPE and ICMJE, the research ethical guidelines such as the Helsinki Declaration, the relevant policies of China, and drawing on the experience of international publishing institutions, the structure and necessary contents of the journal policy are analyzed and established. [Findings] A journal policy framework including peer review policy, editorial policy, research ethics and reporting guidelines has been established, the key points on contents and document writing are clarified. [Conclusions] The journal policy documents constructed based on this research has been reviewed and proved by international databases and international academic publishing organizations, and demonstrated to meet the international standards.

[Purposes] Irregular citation behaviors in academic journals exhibit complex forms and ambiguous boundaries. Existing guidelines often fail to encompass the full range of practical scenarios, with insufficient attention paid to questionable citation practices. [Methods] Drawing on retraction data, policy documents, and academic literature related to citation misconduct, this study analyzes citation irregularities from multiple dimensions, including behavioral forms and identification criteria. [Findings] It categorizes citation misconduct that must be strictly prohibited, as well as citation practices that deviate from academic norms and should be treated with caution. Based on these, the study proposes a backlist and graylist of citation behaviors. [Conclusions] By constructing the blacklist-graylist framework, this study provides a theoretical basis for identifying and preventing citation misconduct in the academic community. It aims to raise awareness among authors about citation norms and the integrity risks of gray-area citation practices, while also offering guidance for journals to establish more refined and actionable citation standards.

[Purposes] This study aims to systematically compare how Chinese and Western academic journals govern the risks associated with generative AI (GenAI) participation in academic paper writing, providing insights and recommendations for domestic academic ethics under the impact of AI. [Methods] Using grounded theory, the authors conducted a three-level coding of official statements from 300 leading Western journals and performed a parallel comparison of their core categories with corresponding texts from Chinese journals. [Findings] Both Chinese and Western academic journals have recognized the multifaceted ethical and legal risks of GenAI participation in academic writing and are attempting to manage these risks through two main approaches: subject accountability and ethical regulation. However, discrepancies exist in the specific content and norms. The study also identifies several issues in Chinese journals, such as a low volume of official statements, lack of clear disclosure of usage boundaries recognized in the West, absence of a unified declaration format, insufficient explanation of third-party detection report submission requirements, and unreasonable limitations on the extent of GenAI use. [Conclusions] Following the principle of “drawing on advanced Western experience while grounding in China’s reality”, the study suggests that Chinese academic journals should consider adopting Western practices in areas such as intellectual property and privacy protection in GenAI-assisted writing, early warning mechanisms for public opinion triggered by algorithmic bias, accountability assignment for editorial entities, fulfillment of journals’ social obligations, and interpretive clauses for ambiguous usage boundaries.

[Purposes] To explore the influencing factors of the short video communication effect of popular science journals, and to provide reference for the short video operation of popular science journals in China. [Methods] Taking the WeChat channels accounts of the journals selected in the list of “China’s Excellent Popular Science Journals” as an example, with the help of the elaboration likelihood model, through content analysis and regression analysis, this paper explores the influencing factors of the dissemination effect of the contents of WeChat channels account of popular science journals from the core and peripheral routes of the model. [Findings] The study found that the video dissemination effect of the contents of WeChat channels account of popular science journals, which was bound to the WeChat public account, had the same account name as the journal, and was good at using topic tags, was better. The communication effect of contents of WeChat channels account of popular science journals can not be significantly improved by the participation of communication subjects. The dissemination effect of landscape mode short videos of scientific knowledge and entertainment produced by animation and live shooting within 60 s is relatively good. [Conclusions] Popular science journals should speed up the layout process of WeChat channels platform, adhere to the concept of “content is king”, take the production of interesting short videos of scientific knowledge as an important carrier to promote the in-depth integration of journal media, and continue to optimize the dissemination effect of popular science content by fully grasping the recommendation rules and user characteristics of the short video platform.

[Purposes] To provide basic data and evaluation indicators for management departments at all levels, research institutions, journal editorial departments and researchers. [Methods] Using data from Chinese core scientific journals, statistical analysis was conducted on the overall including citation and source indicators, disciplines, regions, the number of articles and basic information of the journals. [Findings] From 2021 to 2023, the main indicators such as the core impact factors, and the ratio of funded papers in journals have been increasing year by year, but core total citations slightly decreased. Beijing, Shanghai, Jiangsu, Hubei and Shaanxi provinces have the largest number of core journals. In 2023, 443197 papers were published in core journals in the field of natural sciences and 49408 in the field of social sciences. China’s core scientific journals (including natural science and social science fields) with a publication duration of 20 to 50 years account for the majority. The largest number of bimonthly periodicals which the natural science field accounted for 46.1% and the social science field accounted for 54.2%. [Conclusions] The academic influence of Chinese core scientific journals is increasing.

[Purposes] To explore the evolutionary trend of academic misconduct and the contamination status of the literature pool, thereby providing a foundation and recommendations for targeted measures to improve scientific research integrity. [Methods] Retraction data from 1995 to 2024 were sourced from the Retraction Watch Database. The temporal evolution patterns of academic misconducts were analyzed based on the retraction reasons. The contamination status of the literature pool was analyzed based on the proposed real-time and cumulative pollution indices, as well as the temporal evolution of retraction delays and the citations of the retracted articles. [Findings] Traditional academic misconducts, including plagiarism, falsification, and duplication, have been persisting, while emerging misconduct such as image issues, fake peer review, paper mill, and randomly generated content have become mainstream reasons for retraction. The pollution indices of the literature pool are slowly rising, with the global cumulative pollution index reaching 2.8? and China’s real-time pollution index increases rapidly. The global average retraction delay is prolonged, and the h-index of the retracted articles mostly falls within the range of 60~90. [Conclusions] Global retractions exhibit characteristics of regional concentration, complex and concealed reasons, and slowly rising pollution indices of the literature pool. It is imperative to establish a monitoring and warning mechanism for academic misconduct, systematically standardize and optimize the retraction process, and scientifically construct quality assessment systems and control strategies to maintain the cleanliness of the literature pool.

Purposes This paper discusses the process of negative chain effects caused by generative artificial intelligence （GenAI） in academic publishing， and explores the regulatory approach of GenAI based on the academic publishing scenario. Methods Based on the risk chain， this paper sorts out the formation process of negative chain effects， analyzes how the commercialization of AI intensifies negative chain reactions from the perspective of commercial interests， and then proposes regulatory approaches by matching risk characteristics with policies and regulations. Findings GenAI has formed four negative chain effects through 11 gradual stages： bad money driving out good money， a cycle of cognitive errors， rampant academic dishonesty， and amplified academic injustice. The commercialization of AI has intensified the negative chain reactions by solidifying the direction of academic production， reshaping the academic research evaluation system， and raising the economic barriers to academic publishing. Conclusions The regulatory approaches of GenAI need to pay attention to scenario adaptation， policy coordination and dynamic adjustment at the same time： first， risk level classification and responsibility allocation should be based on subject scenarios and publishing activity roles； second， effective connection between legal provisions and implementation details should be achieved in the fields of data governance and intellectual property rights； finally， a dynamic governance mechanism based on sandbox testing and triggered updates should be established.

Purposes This study aims to compare the efficacy of three popular AI tools （Doubao， Kimi， and DeepSeek） in proofreading medical journal articles， to provide a reference for their rational application in improving editorial efficiency. Methods A total of 43 final-accepted and author-confirmed research articles published in issues from 1 to 12 of 2024 in the Journal of China Medical University were randomly selected. Using manual proofreading as the gold standard， the proofreading performance of Doubao， Kimi， and DeepSeek was statistically analyzed based on the following indicators： grammar， punctuation， quantities and units， numeral usage， terminology， company names， URLs， and software names. Chi-square tests or Fisher’s exact tests were employed for comparisons. Findings Manual proofreading detected 1718 errors in total. The error detection counts for Doubao， Kimi， and DeepSeek were 287 （16.71%）， 127 （7.39%）， and 505 （29.39%）， respectively， with statistically significant differences among the three tools （P < 0.05）. Pairwise comparisons revealed that DeepSeek significantly outperformed the other two tools， with an error detection rate 1.76 times that of Doubao and 3.98 times that of Kimi. Doubao also performed significantly better than Kimi （P < 0.05）. In the comparison of detection rates across various error categories， DeepSeek achieved significantly higher rates in company names （61.54%）， URLs （92.31%）， capitalization （80.00%）， and software names （100.00%） than both Doubao and Kimi （all P < 0.05）. Conclusions DeepSeek demonstrates an advantage in the breadth of error detection， followed by Doubao， while Kimi exhibits the weakest overall detection capability. DeepSeek’s performance in detecting errors in URLs， capitalization， and software names approached human-level performance， suggesting its potential for practical proofreading applications. However， the total number of errors detected by all three AI tools remained significantly lower than that identified through manual proofreading， indicating that general-purpose AI tools still have limitations and pose potential risks in the proofreading of medical articles. Further optimization is needed to enhance their efficacy in this specialized domain.

[Purposes] This study investigates strategic approaches for China’s long-established English-language academic journals to achieve self-reliant development amid the tide of building internationally top-tier journals.[Methods] Using Science Bulletin as a case study, this paper review and summarize this journal’s decade-long publishing practice as well as analyze existing challenges by closely centering on original mission of embracing the world while being rooted in Chinato formulate methodological frameworks for advancing high-impact journals. [Findings] Through systematic optimization, Science Bulletin has achieved tremendous development in both academic and social impact, now ranking among the top 5% of international multidisciplinary natural science journals. [Conclusions] Through a decade of reform, Science Bulletin has successfully transformed itself, exploring a self-reliance and self-strengthening path with Chinese characteristics. The journal’s evidence-based practice provides a transferable candidate model for advancing the sustainable development of world-class scientific journals in China.

Purposes By analyzing the current status of clustered development， exploring the path of intensification， this study aims to address the issues of dispersion and homogeneity of Chinese scientific journals， providing references for the top-level design， large-scale development， and personalized construction of Chinese scientific journal clusters， and enhancing the brand influence and resource integration capabilities of building world-class scientific journals. Methods Using the questionnaire survey method， based on the data of 63 domestic scientific journal clusters， the characteristics of the establishment stage， the type of operating units and sources of funds， the scale and language distribution of journals， the operation and management model， academic influence， exploration of academic services， international cooperation， and the construction of digital publishing and new media platforms of the clusters were summarized and analyzed. Findings The challenges faced during the development process were summarized， such as clustering without intensification， lagging digital publishing platform construction， unclear talent team structure and training models， single financing channels， and unclear business models， and development suggestions were provided. Conclusions The clustered development of Chinese scientific journals has achieved remarkable results， with accelerated improvement in scale and quality. However， structural problems such as regional and disciplinary imbalances are prominent， which require further discussion among peers.

Purposes To standardize academic publishing and accelerate the dissemination of preprints， and to standardize the citation format of preprints. Methods Conduct online research to sort out the citation formats of journal articles and preprint platforms， and compare and analyze the standards related to preprint citation at home and abroad. Findings The survey found that the citation format of preprints in scientific journal articles is not consistent with the recommendations of preprint platforms， and there is an urgent need to standardize the citation format of preprints. Conclusions Preprints should be included as an independent literature type in the existing reference citation standards. The citation elements should fully reflect the characteristics of preprint resources， adopt existing international standard formats， and be arranged in accordance with reference citation standards.

[Purposes] To explore the application scenarios and value of generative artificial intelligence (GenAI) in the multimodal matrix of health science popularization in medical journals. [Methods] The literature review method was used to analyze the current application status of GenAI in health science popularization text, images, audio, video and other modalities. Mainstream GenAI models such as DeepSeek, DouBao, and Dreamina AI were selected for the application practice of multimodal transformation in medical science popularization, and the application effectiveness was analyzed. [Findings] The application of GenAI in multimodal health science popularization in medical journals is still in its early stages, but it has shown significant application value. Large language models represented by DeepSeek can optimize popular science content; Image generation models such as DouBao can efficiently create popular science illustrations, posters, journal IPs, and emoticons; Dreamina AI and other video generation models can create video materials; Intelligent video tools such as Jianying can significantly improve the efficiency of science popularization short video production; Digital human technologies such as Chanjing can create digital avatars for medical experts. [Conclusions] GenAI can be applied to various scenarios of multimodal health science popularization, significantly improving the production efficiency of science popularization content in medical journals and effectively enhancing the dissemination effect. However, it is necessary to ensure the accuracy of content and avoid potential ethical risks.

[Purposes] Identifying and addressing issues in the digital publishing platforms of academic journal clusters in China’s universities to promote the development of university journal cluster platforms. [Methods] Through literature review, case studies, and telephone surveys, employing methods such as summarization and logical analysis, this research investigates the journal cluster platforms of 18 “Double First-Class” universities, identifies common issues, analyzes potential causes, proposes development pathways, and introduces the practical experience of Xi’an Jiaotong University. [Findings] Currently, university journal cluster platforms face issues such as uneven development, limited quantity and capacity, unclear positioning, weak functionality, lack of user service awareness, and limited influence. These problems stem from the dispersed distribution of university journals, weak organizational capacity, insufficient sustained investment, weak self-sustaining capabilities, and a shortage of technical talent. When constructing journal cluster platforms, universities and journal management departments should adhere to intensive development, clarify platform construction goals, dynamically adjust and evolve progressively, increase human resource investment, promote technical collaboration, enhance multifunctional convenience, highlight distinctive features, explore big data and artificial intelligence technologies, and strengthen profitability. Xi’an Jiaotong University has established the silk road journal cluster through cluster-based development, supporting it with a dedicated platform and implementing a three-step strategy for steady progress. The construction unit has assigned internal specialists, actively sought external technical cooperation, and created a platform offering full-process functional services, multilingual support, and empowerment through big data and artificial intelligence. Through professional team operations and platform brand building, profitability is strengthened, ensuring the long-term sustainability of the platform. [Conclusions] The development of university journal cluster platforms remains insufficient. Universities should clearly recognize the crucial supporting role of these platforms for journal clusters, fully leverage their functions, and create user-friendly and intelligent university journal cluster platforms.

[Purposes] This study explores the application prospects of AI in review process to provide insights for the digital and intelligent development of academic publishing. [Methods] Based on literature research and comparative analyses of review policies in domestic and international academic journals, using SWOT analysis, the study systematically examines the advantages, disadvantages, opportunities, and challenges of AI-assisted review,constructing a SWOT analysis matrix. [Findings] AI technology has potential for application in the review process, which can improve review efficiency and enhance the objectivity of reviews. However, problems such as hallucination, bias, security, and trust need to be addressed to achieve large-scale application. This relies on the development of trustworthy intelligent review systems and the establishment of supervision mechanisms. [Conclusions] In the future, to achieve human-machine collaborative AI-assisted review, it is necessary to enhance AI’s technical transparency, strengthen accountability, establish an open data alliance, and implement regulation and governance for AI's technical limitations and ethical risks. Through the dual optimization of technology and systems, AI has the potential to become a crucial tool in streamlining the academic review process.

[Purposes] This study explores the citation advantage of preprints published by highly cited scholars and compares this advantage with their journal article citation advantage, aiming to reveal and understand the role of author reputation in the dissemination and diffusion of preprints. [Methods] Taking preprints from the platforms arXiv, bioRxiv, and medRxiv as the research objects, we group together preprints that were posted on the same platform in the same year and subsequently published in the same journal within that year. Within each group, the primary author of the most highly cited preprint is defined as a highly cited scholar, while authors whose citation counts are more than 1% lower than that of the highly cited scholar are defined as non-highly cited scholars. Linear regression models were used to compare the citation differences between preprints authored by highly cited scholars and non-highly cited scholars, as well as the differences after formal journal publication. [Findings] Preprints and journal articles published by highly cited scholars both exhibit a citation advantage, with the citation advantage being more pronounced in journal articles than in preprints. [Conclusions] Author reputation plays a crucial role in the dissemination and diffusion of preprints, as preprints published by highly cited scholars receive more attention and citations. It is recommended that preprint platforms optimize their recommendation algorithms to enhance the fairness of scientific communication.

Purposes To explore the current status of ethical guidelines regarding artificial intelligence generated content （AIGC） on the official websites of Chinese medical journals， and propose strategies for improving the ethical review system of AIGC. Methods A total of 421 medical and health journals indexed in the World Journal Clout Index（WJCI）of Scientific and Technological Periodicals（2024） were included in the study. The official websites of these journals were reviewed to assess the ethical guidelines requirements regarding AIGC. Findings Among the 421 medical journals included in this study， only 100 （23.8%） had established specific ethical requirements for AIGC， highlighting a pervasive lack of awareness of ethics. There were significant differences in the ethical guidelines requirements for AIGC across journals with different publication languages， primary sponsors， and indexing databases （categories and quantities）. The development of ethics in Chinese-language journals is less developed than that of English-language journals. The statements regarding AIGC ethical guidelines in these journals are unclear in terms of scope definition， disclosure requirements， and authorship policies， indicating a lack of adequate attention to the establishment of ethical review systems for AIGC. Conclusions Chinese medical journals should enhance the supervision of AIGC ethical guidelines by implementing a trinity framework of “policy regulation + technical safeguards + accountability statements”， and bolstering editorial training， prioritizing official website development， thereby facilitating the establishment of comprehensive review systems for AIGC ethics.

Purposes This study monitors the global development of open access （OA）， studies the rationality of article processing charges （APCs）， and analyzes trends in research funding flows， with the aim of providing insights and recommendations for the management of research funding and the promotion of high-quality scholarly communication in China. Methods Based on SCIE data and OA journal websites， we conducted a statistical analysis of global OA journal publishing， authorship， APCs， as well as Chinese authors’ OA publications and APC expenditures. Findings In 2024， a total of 8604 global OA journals and 246 Chinese OA journals were indexed in SCIE， respectively representing year-on-year increases of 10.96% and 14.95%. The global OA publication volume and the publication volume of Chinese OA journals respectively rose by 11.46% and 19.85%. Publications by Chinese authors accounted for 30.09% of the global OA output. Chinese authors published approximately 313500 OA papers across more than 6276 OA journals， with total APC expenditures of about 6.474 billion Yuan（RMB）， increasing by 13.83% in publication volume and 22.38% in APC spending compared with 2023. The National Natural Science Foundation of China （NSFC） remained the primary funding source supporting OA publications by Chinese authors， with its annual APC expenditure rising by 13.31%. Conclusions Both globally and in China， the volume of open access （OA） publications and the total APC expenditures continue to rise， becoming increasingly concentrated in a few major international commercial publishers. To address this trend， it is recommended to reform the academic evaluation system， promote the development of local open access platforms， establish clear open publishing regulations， and strengthen institutional management of the entire publication process.

[Purposes] To explore the innovative pathways, development outcomes, and lessons learned from the centralized management model of university journals. [Methods] Taking “Xi’an Jiaotong University Journal Cluster” as an example, this study combines the evolutionary process of the journal group and its management model innovations to summarize specific innovative practice pathways, achievements, and insights. [Findings] The centralized management model has enabled“Xi’an Jiaotong University Journal Cluster” to achieve significant results in launching new journals, enhancing academic influence, promoting scholarly communication, and constructing the “Silk Road Journal Cluster”. [Conclusions] The centralized management model ensures the sustainable development of journal groups through top-level design, innovative management models, operational reforms, organized research initiatives, and collaborative journal operation models. It serves as a significant approach for the clustered management of university journals.

Purposes The purpose is to summarize experiences and lessons for the transformation and development of academic publishing institutions in China，through systematic and in-depth research into the business model transformation of the five major international academic publishing groups. Methods An integrated methodology combining SWOT analysis， case study research， and inductive summarization was systematically employed. Findings The five major international academic publishing groups actively participate in open access publishing， continuously integrate scientific research platforms and tools， collaboratively upgrade to knowledge solution providers， and proactively explore the deep integration of AI with high-quality resources， thereby seizing opportunities in the transformation of academic publishing， strengthening market influence， cultivating new revenue avenues， and developing emerging business segments. Conclusions China’s academic publishing institutions should seize the opportunity presented by the development of open access journals to actively merge into the transformation of open access scholarly ecosystem； strengthen business diversification to extend the academic publishing industry chain； integrate platforms as a key component to advance journal cluster development； and proactively explore the application of AI tools to extract the full potential value of academic resources.

[Purposes] This paper aims to comprehensively analyze the international influence of Chinese scientific papers, and to provide reference for China to enhance its international scientific competitiveness and discourse power in the academic field. [Methods] Based on the SCI and ESI databases, this paper conducts an in-depth analysis of the international influence of Chinese scientific papers from four aspects: international citation status, cited Chinese papers, high-level international papers, and international co-authored papers. [Findings] In 2023, the number of Chinese scientific papers cited by international papers ranked first globally. The number of highly cited papers secured the second position worldwide, while the count of hot papers topped the global list. The number of papers published in top international journals ranked second globally. Additionally, China produced 151200 internationally co-authored papers. [Conclusions] The international influence of Chinese scientific papers has reached a relatively high level, but there is still room for improvement in pioneering achievements in fundamental research fields.

[Purposes] To reflect the current application of artificial intelligence (AI) in Chinese scientific journal dissemination, and to summarize the evolution of dissemination characteristics in the AI context, and to provide theoretical references and practical methods for the dissemination of scientific journals. [Methods] Through literature reviews, field investigations, and expert interviews, this study investigated the application of AI technologies in scientific journal operations, including topic selection, content production and dissemination. It also summarized the changes in dissemination characteristics. [Findings] AI technologies have improved the effectiveness and efficiency of scientific journal dissemination, leading to significant transformations in communication direction, audience types, and interaction modes. [Conclusions] The study summarizes the evolution of dissemination characteristics in scientific journals under AI influence, including horizontal knowledge flow within vertical dissemination frameworks, the audience has expanded from specialized personnel to the public, and the shift from unidirectional to bidirectional interaction. A three-dimensional model is proposed to visualize this evolutionary process.In response, scientific journals should fully utilize new technologies, explore innovative dissemination models, cultivate and recruit skilled personnel, and establish standards to enhance dissemination capacity.

[Purposes] To analyze the new trends and transformations in international academic publishing under the open science environment, providing insights for the development of China’s academic publishing ecosystem. [Methods] Through literature review and case studies, the shifts in academic publishing models were examined from the dimensions of publishing processes and content. [Findings] In terms of publishing processes, the traditional “Collection-Review-Publication” model is transitioning to the emerging “Publish-Review-Curate” model. In terms of publishing content, the focus has shifted from single elements to the entire research process. Correspondingly, infrastructure such as persistent identifier systems, data storage facilities, and standardization frameworks are also being advanced. [Conclusions] Based on China’s context, recommendations for addressing these changes are proposed, including reshaping the communication ecosystem to “return” science to scientists, strengthening infrastructure to empower publishing service innovation, and guiding and incentivizing innovation to deepen reforms in scientific evaluation.

[Purposes] This study aims to explore the focal points, trends, and blind spots of artificial intelligence content topics in the WeChat official accounts of scientific and technological journals, so as to promote the integrated development of scientific journals. [Methods] Python was used to crawl relevant articles in the past five years. The BERTopic method was applied to analyze the hot topics and their evolutionary trends, and the Gephi clustering method was utilized to sort out the national artificial intelligence policy system. By comparing, the blind spots in topic setting were identified. [Findings] The relevant topics can be divided into four dimensions: technology, application, product service, and ethics. There is a lack of discussion on issues such as data specification, model infrastructure, scenario coverage, market-oriented products, rights protection, technology/data security, and industry standards. In the future, artificial intelligence technology will focus on model data/training and generative large-scale models. Protein molecules and coal mining may become popular application scenarios, and ethical governance will be a hot topic. [Conclusions] Based on this, a four-dimensional strategic optimization framework of “technology-application-product-risk” was proposed to provide methodological support for the in-depth integrated development of scientific journals.

Purposes To explore the development path and framework of AI-driven transformation for scientific journals’ knowledge service， and provide practical references for intelligent knowledge services in scientific journals. Methods Firstly， we conducted a systematic analysis of the characteristics and evolutionary process of the intelligent knowledge service of scientific journals. Next， we presented a case study of the STM publishing industry， and then analyzed the deployment of AI policies， the integration of AI technologies and the development of AI applications. Finally， we provided an AI application strategy for scientific journals. Findings We proposed a four-dimensional framework of “Scene-Resource-Model-Policy” for the intelligent knowledge service of scientific journals. Specifically， this includes： constructing a trustworthy AI corpus based on journal resources， guaranteeing model professionalism based on domain knowledge and publishing standards， developing scenario-driven AI applications， and improving the AI governance system of scientific journals. Conclusions AI for Science （AI4S） is accelerating the transformation of scientific journals into intelligent knowledge services. The STM publishing industry should develop AI strategies， and establish feasible implementation plans.

[Purposes] To explore the optimization strategy of health science popularization of medical academic journals(medical journals for short) in the era of converged media, and provide reference for its effectively responding to pseudo science popularization, better performing the mission of science popularization, and serving the national health cause. [Methods] On the basis of combing the theoretical basis and research framework of health science popularization in medical journals, aiming at the current situation and challenges of its dissemination, the SACRE model of “medical communication” was introduced. Combined with the science popularization practice cases of representative journals, the optimization strategies of health science popularization in medical journals were summarized and analyzed from five elements: scientific subject, audience, clinic content, route, and effect. [Findings] The health science popularization of medical journals under converged media mode meets the requirements of “medical communication” and its SACRE model. Based on SACRE model, it can be optimized by emphasizing scientific subjects, subdividing the audience based on the theory of “perceived disease distance”, disseminating conclusive clinic content, adapting to health demand scenarios, and evaluating the effect of popular science dissemination based on primary prevention, so as to effectively meet the challenges and needs in the era of converged media. [Conclusions] The optimization strategy of health science popularization based on the SACRE model of “medical communication” is more authoritative, scientific and systematic, which can solve the contradiction between the public’s urgent need for medical science popularization and the lack of authoritative information, and improve the efficiency of health communication of medical journals.

Purposes To evaluate the diagnostic efficacy of generative artificial intelligence （GenAI） in detecting statistical results errors in biomedical journals. Methods A convenience sampling method was used to include 21 positive samples （with statistical errors in results） and 21 negative samples （without statistical errors in results）. Kimi and DeepSeek（both deep thinking and non-deep thinking modes） were employed， combined with three prompting strategies ［direct questioning， literature reference （single or dual-paper jointly）， and terminology prompting （full-text review or table-by-table review）］ to form 10 combined strategies. The diagnostic performance of these ten strategies was compared. Findings DeepSeek deep thinking demonstrated the highest sensitivity （47.6%～100.0%） and accuracy （71.4%～90.5%） across all prompting methods， followed by DeepSeek non-deep thinking， with Kimi performing the worst. Literature reference and specialized terminology prompting methods yielded superior sensitivity and accuracy compared to direct questioning within the same GenAI model. “DeepSeek deep thinking + literature reference （dual-paper jointly）” achieved the highest accuracy （90.5%）， while “DeepSeek deep thinking +terminology prompt （table-by-table review）” yielded the highest sensitivity （100.0%） and most comprehensive error detection. Except for “DeepSeek deep thinking + terminology prompt” （specificity： 85.7% for full-text review， 71.4% for table-by-table review）， all other combination strategies demonstrated specificity above 90%. Conclusions DeepSeek deep thinking demonstrated superior performance in detecting statistical errors in biomedical journals. Literature reference and terminology prompting were more effective than direct questioning， though false positives occur. It is recommended that editorial offices adopt “DeepSeek deep thinking+literature reference （dual-paper jointly）” for initial manuscript screening， and “DeepSeek deep thinking+terminology prompt （table-by-table review）” for detailed statistical verification of flagged manuscripts and unpublished studies， issueed by manual validation.

Purposes To conduct an in-depth analysis of the current status of generative artificial intelligence （AI） usage policy and regulation construction in information resources management journals both domestically and internationally， providing references and inspirations for the development of domestic information resources management journals. Methods Taking the journals in the field of information resources management （information science & library science） indexed by CSSCI and JCR （SCIE and SSCI） as the research samples， and based on the criterion of whether they have released policies on the use of generative AI， 61 journals were finally selected for analysis. The grounded theory method was employed to sort out and analyze the generative AI usage policies and regulations they have issued. Findings Most of the international journals in the field of information resources management belong to large international publishing groups， and their policies and regulations on the use of generative AI are basically systematic. In contrast， domestic journals in this field are still in the initial stage of formulating policies on the use of generative AI， lacking systematic and structured governance policies for generative AI. Conclusions Domestic journals in the field of information resources management should actively embrace the trend of generative AI application， fully leverage the strengths of all parties， and enhance their governance capabilities and effectiveness in generative AI. From a macro-strategic perspective， the development of the information resources management discipline and the governance concepts of related industry fields should be utilized to empower the governance of generative AI in field journals. From a micro-implementation perspective， each journal should formulate generative AI application policies that conform to the characteristics of the discipline， set up clear policy sections on their websites， clarify the norms and boundaries of generative AI usage， establish measures for handling violations， and retain the discretionary power of the journal.

[Purposes] To explore the current situation, problems and countermeasures of the industrialization of scientific and technological periodicals in China under the background of open science, and to provide theoretical basis and practical suggestions for promoting the sustainable development of scientific and technological periodicals industry in the open science environment. [Methods] Using the expert interview method and literature research method, the academician experts, journal publishing policy experts, digital publishing technology experts, domestic and foreign publishing institution experts and experts in the field of library and information technology were interviewed to summarize the characteristics of the transformation of the traditional scientific and technological periodical industry at this stage. [Findings] Open science has put forward new requirements for the transformation of the traditional scientific and technological journal industry, including the need for collaboration in the research and production stage, the need for transparency and efficiency in the review stage, the demand for business model innovation in the publishing and distribution stage, the demand for diversification in the knowledge dissemination and impact assessment stage, and the cross-stage systematic demand. China’s scientific and technological periodicals industry is undergoing four changes: from scattered fragmentation to intensive integration and evolution, from content carriers to knowledge service platforms, from catch-up imitation to characteristic development, and from index-only to multi-evaluation paradigm change. [Conclusions] The future development of China’s scientific and technological periodical industry should focus on five aspects: industrial integration (from a single medium to a cross-border ecosystem), technology-driven (AI empowerment and data value release), open transformation (coexistence and development of multi-level open models), evaluation reform (multiple value orientation and quality core), and international collaboration (seeking win-win cooperation in competition). Through deepening reform, technological innovation and model change, China’s scientific and technological journal industry can contribute Chinese wisdom and solutions to global open science while serving the country’s innovation and development.

Purposes To address the limitations of commercial proofreading software， as well as systematic shortcomings in the current generative artificial intelligence （GAI） workflow， this study developed an agent tailored to copyediting-proofreading needs， in order to enhance the efficiency and quality of editorial work. Methods The agent called Déjà Lu （meaning “already read” in English） was independently developed using Python and JavaScript， and its performance was evaluated through a combination of quantitative analysis and questionnaire-based user surveys. Findings The Déjà Lu agent innovatively realizes automated and intelligent processing of proofreading， polishing， and translation for academic manuscripts， with an average processing speed of about 0.007 seconds per character. The proofreading function improved the error calibration rate by an average of 15%， with overall processing time varying across tasks. The polishing function enhanced language expression quality by an average of 7%， while the total processing time was significantly shortened by up to 92%. The translation function achieved good accuracy， with its overall processing time markedly reduced by up to 83%. Editors and authors generally gave positive evaluations of the agent’s performance. Conclusions The modular， hierarchical， and user-friendly Déjà Lu agent ensures strong maintainability， reusability， and extensibility. It can be effectively integrated into editorial workflows to enhance efficiency， providing a new tool and practical paradigm for the integration of artificial intelligence （AI） and academic publishing.

Purposes This study aims to analyze the characteristics of Chinese scientific journals indexed in the Emerging Sources Citation Index （ESCI）， which is expected to serve as a reference for improving the international dissemination of Chinese scientific journals. Methods Multivariate statistical， data analysis were used to study the 14 ESCI-indexed Chinese scientific journals. To be specific， data on the basic journal information， English content presentation， international topic selection， and citation index were collected. Findings Through improving the English-language websites and metadata presentation， achieving indexing in multiple international databases， 14 journals have initially established an international dissemination system. However， they still face challenges in terms of global academic impact， such as high self-citation rate， a significant proportion of zero citation papers， and low discipline ranking. Conclusions On the premise of a clear orientation， Chinese scientific journals should made appropriate strategies. Journals with a certain level of international visibility should focus on international topic selection and international academic activities， increase publication and provide bilingual publishing when necessary. Journals lacking international visibility should strengthen English content presentation， join cluster platform， and apply for index by international databases.

Purposes To conduct a cross-sectional evaluation of the AI-generated content （AIGC） detection capabilities of iThenticate， Wanfang Wencha， CNKI， and Jianziyuan AIGC detection tools on medical abstracts， aiming to provide a reference for the appropriate application of such tools. Methods A total of 518 randomly selected review article abstracts served as the original text group. Corresponding AI-polished and AI-generated text groups were created. The three sets of texts were assessed by the four detection tools for AIGC writing identification. Detection results were recorded， and accuracy， consistency， sensitivity， and specificity were calculated. Findings The results showed significant differences among the tools in terms of result presentation and decision thresholds. iThenticate exhibited limited applicability for Chinese texts， while domestic AIGC detection tools demonstrated higher detection rates for fully AI-generated texts but showed notable false positives and false negatives for AI-polished texts， with low consistency and sensitivity. Conclusions AIGC detection can be employed as an auxiliary technical tool for risk alert and manuscript triage， and should be integrated with author disclosure policies， editorial judgment， and industry standards to collectively uphold academic integrity and publishing order.

Purposes To explore the dynamic changes in the distribution of authors' countries and regions in Chinese social science journals included by SSCI from 2020 to 2024， and to provide reference data for enhancing the international development of Chinese journals included by SSCI. Methods Using the InCites database， we collected metrics and publication information for all papers published in Chinese SSCI-included journals from 2020 to 2024. We further compared the number of papers published and the average citations per paper from different countries and regions in 15 Chinese SSCI journals from 2020 to 2024. Findings From 2020 to 2024， there were significant differences in the number of papers published and the proportion of international collaboration papers （11.85%～47.80%） among the 15 SSCI-included journals in China. From 2020 to 2024， scholars from 97 countries and regions published academic papers in China’s 15 SSCI-included journals. Among them， Chinese scholars contributed the most papers to China’s SSCI-included journals， with their contribution rate increasing year by year， but their average citations per paper were below the overall average. Excluding China， American scholars have the highest contribution to China’s SSCI-included journals， but their share of publications has been decreasing year by year； scholars from W7 countries have seen a steady increase in the number of publications and the highest average citations per paper. In all papers published annually from 2020 to 2024， the number of publications and contribution of foreign authors in China’s SSCI-included journals have shown a decreasing trend year by year. Conclusions In the future， Chinese journals included in the SSCI should actively seek out high-quality papers from renowned scholars in the field of social sciences abroad， while ensuring a steady supply of high-quality domestic manuscripts. They should also participate in international academic conferences to enhance their visibility and attract submissions from foreign scholars. These efforts will promote the high-quality development and internationalisation of Chinese journals included in the SSCI.

[Purposes] To investigate the implementation effect of the “Data Availability Satatement” policy in academic journals, especially the availability degree of associated data of papers. [Methods] Based on the FAIR principle, an evaluation index for the availability of scientific data was constructed. Considering the disciplines to which the journals belong, five journals in the Nature series were selected. A random sampling method was adopted to randomly select one issue of each journal every year to form a research sample. Check one by one whether the sample papers contain data availability statements, whether they are accompanied by supporting data, and the degree of data availability, etc. [Findings] The associated data of the papers in the Nature series of journals performed well in most indicators, such as the data acquisition channels provided by the papers and the ease of processing of the data format, which well guaranteed the sharing and reuse of the data. However, the indicators such as the data containing relevant information of the paper, providing citation information for the paper, the data containing licensing information, and the data containing usage instructions performed poorly, indicating that there is still room for improvement in these aspects. [Conclusions] Journals can enhance the implementation effectiveness of the “Data Availability Statement” policy by refining data submission and evaluation norms, deepening cooperation with data storage platforms, establishing a data classification and grading review mechanism, providing data availability services and guidelines, and reaching a consensus on the openness of associated data of papers.

[Purposes] To continuously enhance the influence of scientific journals, better serve the national’s science and technology development strategies, this study summarizes the developmental strategies and practices adopted by Journal of Materials Science & Technology (JMST) in its journey to expand influence, enhance publication volume, aiming to explore pathways for scientific journals to achieve high-level self-reliance. [Methods] Through online research, literature review and data analysis, the key initiatives implemented by JMST under the backdrop of rapid technological advancement, favorable national policies were summarized, which included streamlining journal governance and operational mechanism, broadening disciplinary coverage, transforming publishing model, rigorous manuscript screening for quality, expanding publication volume and enhancing dissemination via multi-channel strategies following upon the clear development goals. [Findings] JMST achieved sustainable growth in both publication volume and influence, with annual publications reaching approximately 1000 papers. It has emerged as a disciplinary leader in materials science, demonstrating initial capabilities in self-reliance. [Conclusions] The strategy of expanding influence and enhancing publication volume proves effective for scientific journals to attain self-reliance. JMST’s experience provides a replicable model for domestic journals navigating the dual challenges of academic excellence and international competitiveness.

Purposes To analysis development of scientific journal clusters and digital journal group publishing platform and propose a clear direction for future endeavors. Methods Adopting literature and data research methods， to search and collect relevant research results and materials to sort out the related policies as well as beneficial measures for the practice exploration of scientific journal clusters and digital journal group publishing platform， and its character during nearly 20 years. Findings Since the beginning of this century， with the promote of the policy of enterprise system reform and publishing digital transformation as well as the financed with the fund of such as China Science and Technology Journal Excellence Action Plan， a series of professional journal clusters of scientific journals（such as Beijing Zhuozhong Publishing Co.， Ltd，Optics Journal Union and Chinese Medical Association） and its digital publishing platform greatly developed. In addition， comprehensive scientific journals clusters digital publishing platform（such as SciEngine， SciOpen） have been self-construction independently. And all these will be helpful to the future with continuously developing and improving in these years. Conclusions A series of scientific journal clusters and digital journal group publishing platform have been built in these years and should further improve in following years.

[Purposes] Facing the shortcomings of journal impact metrics evaluation, the journal normalized disruption index (JNDI) was designed as a journal innovation evaluation index, which evaluated journals in the field of pharmacy, to develop the scientific evaluation system and promote scientific innovation. [Methods] We selected 29836 articles classified into the WoS category “pharmacology & pharmacy” published in 2016 with a cumulative citation time window of 7 years as the research objects, covering 218 journals. We extracted papers, journals, and citation data from WoS, JCR, and OpenCitations. We analyzed the distribution, correlation, and ranking changes of each index and explored the evaluation effect of RDI and JNDI on the paper level and journal level. [Findings] RDI, which is least affected by the number of references, has the best mathematical properties and evaluation effect among all the D variants. JNDI has advantages over JDI in distribution characteristics and stability. JNDI can distinguish subtle differences between journals. JNDI has a moderately weak positive correlation with the impact metrics. The journals’ JNDI rankings are quite different from the JIF rankings. [Conclusions] JNDI can be used as an index to evaluate the innovation of journals. It is robust and can be applied to interdisciplinary evaluation scenarios. JNDI combined with the impact metrics can identify innovative journals and avoid them being underestimated due to unpopular research fields, non-English-speaking countries, etc. The accuracy of JNDI will be affected by database coverage and journal classification issues, so special attention should be paid when applying JNDI.