Publications doi: 10.3390/publications14030050

Authors: Tong Shen Xiaoling Sun

Artificial intelligence is reshaping scientific research, yet its contribution may be associated with whether methods are matched to the types of research problems. This study investigates this question in medical informatics using 40,107 articles published during 2000–2024. Large language models are used to identify three AI method families—traditional machine learning, neural network methods, and generative AI—while a knowledge-distilled classifier groups studies into three problem types: comprehension-oriented, solution-oriented, and exploration-oriented. The study then examines how different problem–method combinations are associated with citation impact and recombinatorial novelty. AI use increased sharply after 2018 and became increasingly embedded in medical informatics. All three methods are positively associated with citation impact, with relatively stronger associations for generative AI. Associations vary by problem type: all three methods are positively associated with impact in solution-oriented studies; neural networks and generative AI are positively associated with impact in comprehension-oriented studies, whereas neural networks are negatively associated with impact in exploration-oriented studies. Traditional machine learning is positively associated with novelty in comprehension-oriented and solution-oriented studies, whereas neural networks are positively associated only in solution-oriented studies. These findings suggest that AI’s contribution to science is associated with specific problem–method combinations and that broad claims about AI’s role can obscure heterogeneity across research tasks.

Publications doi: 10.3390/publications14030049

Authors: Orlando Meneses Quelal Alba Lucía Yamá Taimal

This study analyzed the structural evolution of the Ecuadorian publishing ecosystem indexed in Scopus during the period 2016–2025 using indicators of scientific production, bibliometric impact, quartile positioning, citation concentration, editorial persistence, and women’s participation. Bibliometric information was obtained from the SCImago Journal & Country Rank (SJR) database by constructing a longitudinal journal-year panel of Ecuadorian scientific journals. The results revealed a sustained expansion of the national publishing ecosystem, reflected in substantial growth in publication output, journal coverage, citation performance, and average SJR values. However, this expansion was not accompanied by equivalent improvements in quartile positioning, as journals classified in Q3 and Q4 continued to predominate throughout the study period. The analysis also identified a high concentration of bibliometric impact within a limited set of journals, along with significant disciplinary transformations, characterized by the growing participation of Engineering and STEM-related fields. Female participation increased over time, although heterogeneous patterns persisted across disciplinary areas. To provide an integrated perspective on ecosystem evolution, a Composite Indicator of Editorial Development (CIED) was constructed, combining dimensions of visibility, citation efficiency, editorial coverage, quartile positioning, and impact dispersion. Overall, the findings indicate that the Ecuadorian publishing ecosystem has strengthened its editorial development and international visibility over the last decade, while persistent asymmetries in quartile distribution and citation concentration continue to pose important challenges to broader integration into the global structure of scientific communication.

Publications doi: 10.3390/publications14030048

Authors: Yasiel Pérez Vera

Diamond Open Access journals face increasing challenges in ensuring metadata quality, interoperability, persistent identification, digital preservation, and international visibility while operating with limited financial and technological resources. Although Open Journal Systems (OJS) provides a robust publishing platform, the absence of an integrated technological governance model can hinder the systematic coordination of scholarly communication infrastructures. This study proposes and evaluates a Technological Governance Framework for Diamond Open Access journals using a Design Science Research methodology. The framework is organized into five governance dimensions: metadata management, persistent identifiers, scholarly interoperability, digital preservation, and editorial technologies. To support the assessment of technological governance performance, five composite indicators were integrated into a Technological Governance Index (TGI). The framework was evaluated through its implementation in the Innovación y Software journal, demonstrating its practical feasibility within a real Diamond Open Access publishing environment. The implementation achieved high levels of metadata quality, persistent identifier adoption, preservation, and interoperability, with a TGI of 97.43%. The journal also received the inaugural Crossref Metadata Excellence Award in the New Members category in 2025, providing complementary evidence of the metadata quality achieved in the evaluated case study. Although the results demonstrate the feasibility of the proposed governance model within the evaluated institutional context, further multi-journal studies are required to assess its transferability and broader applicability. The proposed framework provides a structured and measurable basis for coordinating technological capabilities in Diamond Open Access publishing and for future research on technological governance, metadata quality, interoperability, and digital sustainability.

Publications doi: 10.3390/publications14030047

Authors: Annalena Seyr Ulrich S. Tran Martin Voracek

In a time where the methods of science are frequently called into question, open science practices are gaining increased importance. A particularly cooperative form of transparent science is the approach of adversarial collaboration (AC), where research groups with different explanations of the same phenomenon work closely together to develop a study and publish their results jointly, regardless of the outcome. The aim of this work, a systematic mapping review, is to provide a comprehensive overview of the formal aspects of AC and identify the relevant factors that need to be considered when applying this method. For this purpose, both AC studies and publications related to this topic were analyzed. The total of 89 articles retrieved, analyzed, and integrated indicates that accounts on this topic have slightly increased (mostly in psychology) in recent years. However, only a handful of authors have delved more deeply into ACs, and there currently is no journal specifically promoting ACs. The analyzed sources provide a solid foundation for best-practice recommendations and a comprehensive overview of the pros and cons of AC, in the form of organized lists of AC-related known advantages and challenges (alongside solutions to the latter ones). Specifically, some AC studies show weaknesses in study quality, mainly due to a lack of information on the implementation steps. This systematic mapping review serves not only as an introduction to the topic, but also as a guide for future ACs.

Publications doi: 10.3390/publications14030046

Authors: Javier Fernando Angulo-Osorio César Daniel Valdivia-Portugal Karina Rosas-Paredes Diego Fernando Angel Angulo-Osorio Gustavo Eduardo Reinoso-Flores

This article describes the design, development, and user acceptance evaluation of the Monitor CRIS UCSM, a research monitoring system (RMS) built on the Elsevier Pure REST API for the Universidad Católica de Santa María (UCSM), Arequipa, Peru. The study addresses two research questions: (RQ1) can an API-based CRIS monitoring solution be implemented on a commercial Research Information Management System (RIMS) to meet institution-specific regulatory requirements, and (RQ2) to what extent do institutional stakeholders perceive such a system as usable, normatively relevant, and useful for strategic decision-making? The system integrates bibliometric data from Pure into dashboards covering research production metrics, RENACYT-qualified researcher profiles, SDG alignment, and regulatory compliance indicators aligned with Peruvian higher education legislation (Law No. 30220, SUNEDU, CONCYTEC), implemented on a three-tier architecture (Laravel 11/Vue.js 3/MySQL 8.0) with role-based access control. A User Acceptance Test (UAT) conducted with 134 institutional stakeholders, using an instrument adapted from the System Usability Scale (SUS) and structured into four dimensions, showed excellent internal consistency (α = 0.90), a composite SUS-adapted score of M = 81.12 (SD = 5.83), and very favorable ratings across all four dimensions (global M = 4.32; SD = 0.14 on a 1–5 Likert scale). These findings, bounded to the UCSM institutional case, support the technical feasibility of API-based CRIS monitoring within a single institution. The decision-making utility reported here reflects internal stakeholder perceptions gathered through a single UAT administration, not measured organizational outcomes, external adoption, or longitudinal use.

Publications doi: 10.3390/publications14030045

Authors: Pablo Dorta-González María Isabel Dorta-González

This study investigates how YouTube content producers incorporate scientific evidence into their videos. The purpose is to understand which types of knowledge sources most influence science-related video production and how alternative communication channels shape the visibility of research. A dataset encompassing 81,302 scientific papers in biotechnology serves as the empirical foundation for this analysis. Through log-linear regression modeling, the results reveal a divergence. While a research paper’s integration into digital video creation scales positively with its prominence in public-facing platforms (news and Wikipedia), it correlates negatively with traditional scholarly benchmarks, namely peer-reviewed citations, policy document references, and patent applications. Video creators, it appears, prioritize public visibility over conventional academic influence. This asymmetry underscores a systemic gap in how scholarly outputs filter into digital communication spaces.

Publications doi: 10.3390/publications14030044

Authors: Adilbek K. Bisenbaev

This paper proposes a level-based scientific maturation master plan (SMMP) for strengthening research projects prior to manuscript submission. A weak manuscript is often not simply a weak text but an immature project that has been translated too early into publication form. Contemporary research management is better at registering deadlines, deliverables, resources, and visible publication signals than at diagnosing the internal maturity of a scientific object. The result is false readiness: a project may have a topic, structure, literature, methodological vocabulary, and a polished manuscript but still lack a mature problem, a coherent conceptual architecture, a testable design, sufficient evidence, and a disciplined contribution. To address this gap, this paper proposes a nine-level SMMP, moving from thematic impulses to peer review and publication readiness. The model integrates noncompensatory gates, evidence packages, red flags, maturation debt, bottlenecks, the publication maturation gap, and peer-review readiness. Methodologically, the paper is a conceptual design study supplemented by a proof-of-concept documentary application to publicly available CORDIS project biographies. The framework shows how to distinguish publication polish from scientific maturation and how to translate expert criticism into concrete presubmission actions.

Publications doi: 10.3390/publications14030043

Authors: Eungi Kim

This study examines how different prompt anchoring strategies influence the conceptual representation of LLM-generated keywords and compares those effects with the effects of model selection. A controlled exploratory experiment evaluated four prompt conditions—No Examples, Brief Keywords, Detailed Explanations, and Author-Based Examples—across T. D. Wilson’s four information behavior dimensions using 1068 abstracts. Four LLMs (GPT-4o-mini, Claude-3-haiku, Gemini-2.0-flash-lite, and DeepSeek V3) were evaluated under all prompt conditions, yielding 17,036 valid observations. Results indicate that model identity accounts for substantially more variance in keyword generation (η2 = 0.309) than prompt condition (η2 = 0.069), although these estimates should be interpreted with caution given the repeated-measures design and assumption violations. Prompt anchoring, however, consistently reconfigured the conceptual distribution of outputs across all models, indicating that it influences conceptual representation even when model effects are larger. Author-Based Examples substantially increased representation of the typically underrepresented Information Sharing dimension, whereas Detailed Explanations produced the highest overall generation rates and the broadest dimensional coverage. These findings further indicate that different anchoring strategies involve consistent trade-offs in dimensional coverage. The study thereby identifies prompt anchoring as a source of methodological variation in LLM-assisted content analysis, indicating that anchoring strategies should be explicitly specified, justified, and reported as part of the study methodology.

Publications doi: 10.3390/publications14030042

Authors: Yuan Liu Yanyan Huang Lingxian Xie Tiantian Guo Yi Zheng Xudong Hu Wenjin Huang

Currently, the “Planning–Dissemination–Empowerment” approach has become a widely adopted practice paradigm for scientific journals to serve industrial scientific and technological innovation. Nevertheless, how to achieve the effective transformation from knowledge production to scientific and technological innovation remains a core issue urgently to be addressed in the academic publishing sector. Taking Yangtze River as the research sample, this paper constructs and conducts an in-depth analysis of a systematic practical path of “Planning–Dissemination–Empowerment” targeting the improvement of research achievement transformation efficiency. Under this path, the planning segment accurately identifies core issues aligned with national strategies and frontline engineering demands through demand anchoring, ensuring the pertinence and application value of academic content; the dissemination segment relies on a diversified digital matrix to realize precise delivery and efficient diffusion of research findings, accelerating the transmission of academic outputs; the empowerment segment intervenes from three dimensions of talent cultivation, decision support, and technology implementation, promoting the conversion of academic achievements into practical innovation capabilities. Practice demonstrates that this path has not only produced more than 1500 high-impact papers but also directly facilitated multiple scientific and technological innovations. Talent empowerment has fostered a cohort of young scientific and technological backbones; decision empowerment has directly underpinned national emergency decision-making via 3 policy advisory reports adopted by central authorities; technology empowerment has driven breakthroughs in key technologies such as barrier lake emergency disposal, with relevant achievements winning the First Prize of Hubei Provincial Science and Technology Progress Award. In addition, the optimal reservoir operation technology was applied in the 2024 basin-wide flood control, reducing flooded arable land by 170,000 hectares and preventing the evacuation of tens of thousands of residents, thus achieving the integration of academic influence and tangible social benefits. Rather than a mere restatement of industry consensus, the path proposed in this paper reveals the underlying mechanism through which scientific journals are deeply embedded in the innovation chain and catalyze the shift from “consensus” to “practical outcomes” via systematic design. Combined with discussions of multi-industry cases, this path provides an operable theoretical framework and practical paradigm for scientific journals to play more substantial and verifiable roles in the national innovation system.

Publications doi: 10.3390/publications14030041

Authors: Adam Szromek

Cross-level inference errors constitute a specific source of misleading scientific interpretation. They arise when the meaning assigned to a finding is transferred from one level of analysis to another without sufficient methodological justification. The conceptual aim of this article is to explain how a formally valid statistical association may become misleading when its interpretation or communication goes beyond the level at which the data were collected and the association was estimated. The practical aim is to propose a procedure for checking level alignment. The article is conceptual and review-based in nature. It relies on a purposive, problem-oriented synthesis of literature from research methodology, social epidemiology, multilevel analysis, selection bias, spin and exaggeration in scientific communication, and misinformation in and about science. Its contribution consists of linking the classical methodological problem of ecological and atomistic fallacies with the communicative processes through which scientific findings are reformulated in abstracts, press releases, media reports, and secondary summaries. On this basis, the article proposes a model of alternative pathways leading from a statistical association specific to a given level to a public claim, distinguishing a level-aligned pathway from a pathway leading to a Level-Misaligned Public Claim. The article also introduces the Inference-Level Alignment Procedure as a procedure for checking the alignment between the level of inference and the level of communication. This procedure includes two diagnostic checkpoints: alignment between analysis and inference, and alignment between inference and communication. The article argues that responsible scientific interpretation and communication require not only fact-checking, but also checking whether the level of analysis, the level of inference, and the level of communication or recommendation remain aligned.

Publications doi: 10.3390/publications14030040

Authors: Kenny Cesar Alca Carrasco Obert Marín-Sánchez Ruy D. Chacón Jimmy Ango-Bedriñana Homero Ango-Aguilar

Scientific output in health sciences has grown exponentially, yet its landscape remains under-analyzed in emerging economies. In Peru, Microbiology and Parasitology are disciplines of strategic relevance for public health, but no specific bibliometric analysis exists. This study provides the first baseline to identify thematic gaps and characterize research patterns within the SciELO Peru collection. Through a descriptive bibliometric analysis of 549 Microbiology and Parasitology articles indexed in the SciELO Peru collection (2000–2023), temporal, regional, and institutional indicators, methodological design, and journal characteristics were evaluated using R v4.4.0. Results show that production peaked in 2021, coinciding with the COVID-19 pandemic period and accompanied by a marked increase in Virology-related publications. Lima accounted for 77.3% of the SciELO Peru corpus national output, with UPCH (17.5%), INS (14.9%), and UNMSM (13.7%) leading institutional activity. Bacteriology was the dominant area (44.1%), while Mycology was the most underrepresented (2.4%), and cross-sectional designs predominated (63.9%). Notably, real international collaboration was limited to 1.8%, and RPMESP was the sole Bradford core journal, accounting for 48.5% of the corpus, with no articles appearing in Q1 journals. These findings reveal that while production shows sustained growth, it is marked by high geographic concentration and a scarcity of applied technological research within the analyzed corpus. These findings highlight the urgent need to decentralize research and reorient Peru’s health science agenda toward critical, under-studied disciplines.

Publications doi: 10.3390/publications14030039

Authors: Ana Chacón-Luna Patricio Álvarez-Muñoz Ayrton Mariño-Arreaga Ángel Morán-Herrera Marco Faytong-Haro

Quartile rankings of journals have become shorthand for research quality in many national evaluation systems. This Commentary offers a non-systematic documentary analysis of this phenomenon in Spain and selected Latin American systems. It conceptualizes these arrangements as quartile regimes: configurations of rules, indicators, organizational routines, and incentives that make the Journal Citation Reports or SCImago quartile position of a journal function as a high-stakes proxy for research quality. The article draws on legal and policy texts, agency criteria, reform documents, peer-reviewed literature, and selected integrity cases used as illustrative vignettes rather than prevalence evidence. Spain is analyzed as an early and influential case in which sexenios and accreditation made journal indicators central to individual careers, although the 2024 sexenio criteria now move explicitly toward qualitative narratives, broader outputs, and responsible indicators. Mexico, Brazil, Colombia, Argentina, and Peru are treated as purposive Latin American cases that show distinct pathways through individual recognition schemes, graduate-program evaluation, journal-indexing systems, career committees, and publication bonuses. The article argues that quartile regimes reshape publication language, research agendas, disciplinary hierarchies, authorship practices, and integrity risks, with particularly strong effects in the social sciences and humanities and in regional journal ecosystems. Current reform efforts, including the Agreement on Reforming Research Assessment, the Coalition for Advancing Research Assessment, FOLEC-CLACSO, and the ALAEC manifesto, show that quartiles can be repositioned as weak contextual signals within broader, field-sensitive frameworks that value quality, bibliodiversity, multilingual communication, open science, and societal relevance.

Publications doi: 10.3390/publications14030038

Authors: Dirk H. R. Spennemann

This paper investigates how generative AI produces and propagates hallucinated academic references, focusing on the recurring non-existent citation “Education Governance and Datafication” attributed to Ben Williamson and Nelli Piattoeva. Drawing on 196 accessible source papers identified through Google Scholar and Google searches, the study analyses the structure, recurrence, and onward citation of this phantom reference. It shows that hallucinated citations are not random inventions but patterned re-combinations of real authors, journals, dates, and keywords, with duplication occurring in nearly 30% of these hallucinated citations. The paper also reports a structured interrogation of ChatGPT 5-mini about how it generates citations and finds that, absent of verification, the model reconstructs plausible references from learned patterns rather than factual recall. Finally, 110 AI-generated essays on datafication and school governance were examined: while most references were genuine or partly accurate, 29.8% remained fully hallucinated citations, including exact matches to the most common phantom citation, and an additional 29% were partially hallucinated citations. The findings highlight ongoing risks to academic integrity and show that web-enabled AI still does not fully eliminate fabricated references.

Publications doi: 10.3390/publications14020037

Authors: Gina Joubert

Finding willing peer reviewers is challenging. This viewpoint describes a health sciences reviewer’s experience regarding the decision to decline or accept review invitations, and the review process and outcome in terms of journal communication and duration. This audit included all manuscript review invitations received by the researcher in 2022–2024. Information was noted from emails received from the journals. Of 130 review invitations received, 49 (38%) were accepted. The most common reason for declining review invitations (23/81; 28%) was that the researcher, a biostatistician, did not regard herself as having the necessary clinical background. Of the 49 accepted invitations, reviews were submitted for 46 manuscripts (94%), with 24 manuscripts (52%) requiring more than one review round. The reviewer was informed of the journal decision after each review round for 22 (48%) reviewed manuscripts. However, the final journal decision regarding acceptance or rejection of the manuscript was received for only 14 (30%) reviewed manuscripts. Journals provided comments of other reviewers for 44% (n = 20/46) of reviewed manuscripts. To align with International Committee of Medical Journal Editors recommendations, journals should provide feedback to reviewers regarding other reviewers’ comments and the final journal decision. Journal information regarding the usual number of review rounds and duration may influence potential reviewers’ willingness to participate.

Publications doi: 10.3390/publications14020036

Authors: Shahryar Sorooshian

Literature reviews are essential for synthesizing existing knowledge, mapping research domains, identifying intellectual structures, and highlighting research gaps within a field. However, many literature reviews are incomplete because database search strategies are not adequately specified or validated. Search strategies are frequently underreported and undermotivated across the systematic review literature and bibliometrics, while query formulation remains time-consuming, error-prone, and particularly difficult in interdisciplinary or rapidly evolving topics. This article fills that void by developing a guideline for designing a professional topic query in existing academic databases and emphasizing search design as the front-end validity problem in bibliometric research. The article uses the Artificial Intelligence Think Tank framework as a methodological engine and applies it to bibliometric retrieval engineering via structured interaction with generative AI systems and human experts. The paper assists scholars performing bibliometric studies, scientometric analyses, systematic literature reviews, scoping reviews, and hybrid evidence-synthesis projects.

Publications doi: 10.3390/publications14020034

Authors: Kasaraneni Purna Prakash Kasaraneni HimaJyothi Salini Rosaline Yellapragada Venkata Pavan Kumar Gogulamudi Pradeep Reddy Naveen Mukkapati

Bibliometric data from various databases are crucial for exploring research trends through a bibliometric analysis. Usually, deduplicating records and merging several citation index databases for bibliometric research is tedious, particularly when dealing with larger datasets. Although several manual and automatic merging processes are available in the academic literature, some key issues were identified during the implementation of existing merging processes. To address such issues, this paper proposes an open-source preprocessing pipeline developed using R programming for a simple merging of bibliometric data collected from multiple databases. This open-source reproducible preprocessing pipeline precompiles and deduplicates records based on a Digital Object Identifier (DOI). To implement this proposed research work, bibliometric data are considered from Scopus, Web of Science and Lens databases. The key outcomes of this research work are identifying multiple DOIs and Titles, standardizing the DOIs, and deduplicating records to obtain a merged dataset without noisy data. This enables researchers to conduct an effective bibliometric analysis.

Publications doi: 10.3390/publications14020035

Authors: David A. Hernandez-Paez Mónica Acuña-Rodriguez Kevin Fernando Montoya-Quintero Jhon Victor Vidal-Durango

Aligning mental health research with territorial health needs remains a critical goal, yet the global distribution, coherence, and impact of scientific output across income groups remain poorly understood. We conducted a meta-research study combining scientometric analyses with longitudinal data on 60 health and development indicators. Over 386,000 peer-reviewed publications were retrieved from five major databases. Linear regressions, meta-analyses, and meta-regressions were performed, stratified by World Bank income classification. We find that high-income countries (HICs) accounted for 67% of publications, exhibiting the highest research density but the lowest potential marginal health returns. In contrast, low-income countries (LICs) showed the strongest associations between research volume and improvements in life expectancy (β = 0.13; p < 0.01) and child mortality (β = −1.38; p < 0.01). Structural moderators such as governance quality, health expenditure, and education explained up to 48% of between-group variance. In conclusion, the global landscape of mental health research remains unequal. While scientific production is concentrated in HICs, its population-level association is greatest in LICs. These findings underscore the need to redirect investments and enhance research coherence with health needs, particularly through governance safeguards and capacity building in underrepresented regions.

Publications doi: 10.3390/publications14020033

Authors: Peter van den Besselaar Charlie Mom

Rejection of review invitations due to time constraints is putting pressure on the peer review system, showing that less time-consuming ways of reviewing are needed. This paper presents the results of a field experiment with a new format for grant peer review and answers the question of whether this new format is less time-consuming while still providing high-quality reviews. In the new approach, the Peer Circle (PC), a team of reviewers collectively evaluates several grant applications. The PC was applied to four fields and compared with four similar fields using conventional peer review. Qualitative and quantitative methods have been used to analyze heterogeneous data such as interviews with and a survey of the peer reviewers; text analysis of the review reports; and statistical analysis of bibliometric applicant data. The comparison suggests that the PC saves time and enlarges the reviewer population considerably. Most reviewers felt that the quality of the PC evaluations was at least as good as that of the conventional evaluations, if not better. Given these findings, the experiment is now continued on a much larger scale. Apart from that, the theoretical implication is that the way of organizing peer review has an important effect on the functioning of the system.

Publications doi: 10.3390/publications14020032

Authors: Hiran H. Lathabai Raghu Raman Prema Nedungadi

Despite its many limitations, peer review is the most preferred research assessment scheme for research proposal assessment at the individual level. Although scientometric assessment offers effective assessment frameworks, certain limitations, including the proven and potential misuse of scientometric indicators, hinder its wide adoption. Informed peer review is viewed as an effective way of harnessing the advantages of peer review and scientometric/quantitative assessment wherein one may complement the limitations of the other. Informed peer review frameworks are still prone to many inherent challenges in scientometric assessment and peer review. The importance of intelligent review frameworks that can be more advanced and effective than informed review frameworks lies there. With the advent of AI and generative AI (GenAI), a plethora of opportunities are available to convert informed peer review frameworks to intelligent review frameworks but not without challenges and concerns. In this work, we discuss the possible opportunities for effective AI intervention in an existing informed peer review framework to transform it into an intelligent review framework. Although the selected existing informed peer review framework emphasized the ‘novelty first’ policy, it did not provide any means or guidelines to execute it. The proposed conceptual ‘intelligent review framework’ addresses this very well by exploring the effective use of AI/ML techniques for the process and is envisioned to have the flexibility to adapt to future technological developments in AI, GenAI, etc. Possible challenges and a roadmap for possible evolution with anticipated technological changes, etc., are also discussed.

Publications doi: 10.3390/publications14020031

Authors: Gary Christiam Farfán-Chilicaus Alexander Fernando Haro-Sarango Angela Fremiot Rodriguez-Armas César Augusto Herrera-Asmat Silvia Mabel Cachay-Salcedo Rosa Amable Salcedo-Dávalos Violeta Claros-Aguilar de Larrea Emma Verónica Ramos-Farroñán

This exploratory methodological study demonstrates an integrated workflow that combines systematic evidence collection Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA 2020), bibliometric mapping, and Transformer-based natural language processing (RoBERTa) to generate multi-layer insights from Circular Economy-related scholarship, using circular bioeconomy literature as a domain case (2017–2025). Searches across Scopus, ScienceDirect, Taylor & Francis, and SAGE retrieved 2643 records; after deduplication and screening, 50 studies were included (mean quality 13.2/16; 68% high quality). Bibliometric mapping (VOSviewer; Scopus subset n = 1468) revealed three thematic clusters that converge with five conceptual framings extracted via qualitative synthesis, providing cross-method validation of the pipeline’s structural and interpretive outputs. The NLP layer identified a predominantly positive discursive valence in the English-language title–abstract–keyword corpus derived from Scopus records, with declining polarity and increasing subjectivity over time. Because these estimates were obtained from composite bibliographic text fields rather than full-text discussion sections, they should be interpreted as indicators of narrative framing rather than as direct evidence of epistemic bias or empirical overstatement. Within that scope, the joint reading of polarity, subjectivity, hedging, and measurement gaps suggests a possible mismatch between acknowledged evaluative limitations and the caution used to communicate them.

Publications doi: 10.3390/publications14020030

Authors: Sizhe Liu Ying Zhou Yongmei Song Cong Chen

Annotation and indexing of classical Chinese medical texts enable the extraction of core information, facilitating structured annotation and standardised indexing. These processes provide essential support for knowledge retrieval, digital utilisation, and in-depth analysis of these texts. Recent advances in digital technologies have opened new possibilities for annotation and indexing, offering transformative approaches to address challenges arising from the abstract, concise, and complex nature of classical Chinese medical literature. However, existing research has largely overlooked the intrinsic interconnection and synergistic mechanisms between annotation and indexing within the workflow. This study examines annotation and indexing as an integrated whole, reviewing the current state of research, identifying existing challenges, and proposing future directions. The findings reveal that major challenges in the annotation and indexing of classical Chinese medical texts centre on four key areas: cultural connotation, rule formulation, result dissemination, and technical algorithms. Addressing these issues requires a systematic approach, including the development of a cultural heritage framework for Traditional Chinese Medicine, the establishment of standardised annotation and indexing principles, the construction of high-quality corpora, the optimisation of data circulation mechanisms, and the refinement of intelligent algorithms. Advancing the annotation and indexing of classical Chinese medical texts not only promotes their efficient circulation and secondary utilisation but also lays a solid foundation for the large-scale mining of Traditional Chinese Medicine knowledge, its modern transmission, and cross-disciplinary intelligent applications, thereby driving the innovative development of the field.

Publications doi: 10.3390/publications14020029

Authors: Carol Nash

There is contested use of Google Scholar as a primary database for PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) reviews. However, well-cited articles identify Google Scholar as insufficiently reliable and evaluate its use as supplementary. Subsequent systematic review searches have accepted this relegation of Google Scholar to supplementary status, citing these articles as the reason. This study questions this acceptance by (1) revealing the type of difficulties with Google Scholar identified in these well-cited publications compared with PRISMA guidelines, and (2) examining several PRISMA scoping review primary database searches performed by this author since 2023 for the adequacy of Google Scholar results compared with them. The results reveal that the reasons for considering Google Scholar a supplementary database regarding PRISMA status are not convincing, as they are unrelated to PRISMA guidelines for systematic reviews. Google Scholar returned the greatest number of included studies for the majority of post-2023 scoping reviews conducted by this author. These results demonstrate that the accepted advice to authors that Google Scholar should be a supplementary database is unsupported. Based on the results of this research, the suggestion is to accept Google Scholar as a primary database, comparable in all relevant ways to other primary databases for a PRISMA-style review.

Publications doi: 10.3390/publications14020028

Authors: Irina D. Turgel Olga A. Chernova

The BRICS countries are playing an increasingly significant role in shaping a multipolar model of global science. This study aims to assess the academic influence of economic journals published in BRICS countries from the following key perspectives: academic standing, relevance, influence sustainability, internationalization, and external institutional recognition (lack of isolation). The methods of bibliometric, comparative, and cluster analysis were used. The study revealed that the BRICS countries have significantly increased their presence in the Scopus database. However, their scientific publishing landscape is highly heterogeneous. Russia and India exhibit the highest publication volumes among the BRICS countries, albeit with relatively low citation rates and a low level of internationalization. Meanwhile, Chinese, South African, and Indonesian journals have the highest citation rates and strongest integration into the global discourse. Cluster analysis identified five groups of journals with a range of academic influence levels, from peripheral contributors to international leaders. Additionally, country-specific features of their distribution were determined. The present research provides insights into the pivotal role of national journals in overcoming peripherality and strengthening the academic influence of nationwide science. The research methodology can be used to develop strategies that promote nations to become part of the global research community.

Publications doi: 10.3390/publications14020027

Authors: Zhenning Guo Haoran Mao Fang Zhang

With the rapid advancement in Generative Artificial Intelligence (GenAI), AI-generated content (AIGC) lacking human cognitive oversight is increasingly permeating open web environments and academic communication systems. This study integrates longitudinal retraction data (Retraction Watch Database, 1990–2026), web-scale analyses of AI-content penetration (Common Crawl, 2013–2026), and bibliometric mapping of governance scholarship (Web of Science Core Collection, Scopus, Google Scholar, 2020–2026) to diagnose the cross-level misalignment between synthetic-content diffusion, AI-related misconduct pressure, and governance attention. On this basis, it proposes a Normalized Coverage Index (NCI) to measure the relative relationship between scholarly attention to AI-related academic misconduct governance and the level of misconduct pressure observed through retraction data across disciplines. The results reveal pronounced asymmetries at the disciplinary level. Fields such as chemistry (0.04), physics, mathematics & statistics (0.11), and life sciences & biology (0.34) exhibit clear governance gaps, whereas Education shows a comparatively excessive level of attention (NCI = 29.26). Since 2022, AIGC has expanded rapidly across open web corpora, accompanied by a sharp rise in AI-related retractions, which also exhibit a longer detection lag than traditional forms of misconduct (2.77 years vs. 1.91 years). Although the volume of academic governance-related research has grown rapidly, its proportion within the broader body of AI-related research has declined, suggesting that scholarly attention to governance has not kept pace with technological diffusion. Consequently, a structural misalignment in governance—closely tied to the allocation of attention—has emerged within the academic system in the era of GenAI. This misalignment may pose potential risks to the robustness of the knowledge production system. Addressing it requires rebuilding epistemic infrastructure through provenance transparency, auditable workflows, and governance-aware seed corpora aligned with empirically concentrated risks.

Publications doi: 10.3390/publications14020026

Authors: Spyridon Plakias

The rapid growth of scientific publications in sport science has intensified competition for publication and increased the importance of methodological rigor, transparent reporting, and effective scientific communication. Despite the availability of general guidance on scientific writing, recommendations specifically tailored to the context of sport science publishing remain fragmented. The aim of this narrative review was to synthesize methodological, conceptual, and editorial perspectives in order to identify the key factors that influence the quality and publishability of sport science research. The review examines major dimensions of research quality, including theoretical grounding, methodological rigor, statistical inference, open science practices, and the structure of scientific manuscripts. In addition, common weaknesses that frequently lead to manuscript rejection, such as limited scientific contribution, methodological flaws, statistical misinterpretation, and inadequate scientific writing, are discussed. Building on this synthesis, the article proposes an integrated conceptual framework that conceptualizes publishable sport science research as a progressive process moving from conceptual foundations to methodological and analytical rigor, research transparency, and effective scientific communication. The framework, presented as a funnel, illustrates how these interconnected dimensions ultimately contribute to two complementary outcomes: the advancement of scientific knowledge and the practical application of research findings in sport contexts. By providing a structured overview of these elements, the proposed framework aims to support researchers in designing more rigorous studies, improving manuscript quality, and strengthening the impact of sport science research.

Publications doi: 10.3390/publications14020025

Authors: Dyah Puspitasari Srirahayu Dian Ekowati Tiara Kusumaningtiyas Esti Putri Anugrah Alifian Sukma Misita Anwar Hanis Diyana Kamarudin

The rapid advancement of artificial intelligence (AI) is reshaping the landscape of library and information science, significantly altering the roles and responsibilities of information professionals. This paper aims to examine the transformations of information professional roles in the era of artificial intelligence. This study conducted a systematic literature review (SLR) emulating the PRISMA 2020 protocol. Titles and abstracts were screened based on predefined inclusion criteria, including English full-text journal articles, review papers, and conference papers indexed in Scopus addressing the roles and competencies of information professionals in the era of artificial intelligence. The study employed a conceptual and review analysis of documents to examine the use of AI and its impact on the roles of information professionals. We investigated the positive and negative effects of AI on the roles of information professionals, as well as the evolving role of information professionals in routine process automation. AI’s presence and transformation of virtually all the information professionals’ roles are profound, with pertinent challenges. The impact of AI on the roles of information professionals are both positive and negative, while the roles of information professionals have undergone significant changes in the AI era. This paper presents a unique perspective on the evolving roles of information professionals in the era of artificial intelligence. It offers original insights into how AI is reshaping the profession, highlighting the profound impacts and transformations that are redefining traditional practices and skill sets.

Publications doi: 10.3390/publications14020024

Authors: Alberto Ciarrocca Ivan Heibi Ahmadreza Nazari Anna Nicoletti Martina Pensalfini Silvio Peroni Lucrezia Pograri Pietro Tisci Sergei Slinkin

The diversification of research outcomes produced within scholarly communication practices has led to a growing production of non-traditional research outputs (NTROs) such as datasets, software, databases, exhibitions, and multimedia materials, which are often poorly tracked by institutional systems. This study presents an exploratory study about knowledge production at the University of Bologna (UNIBO). This prominent national research institution offers a compelling case study to assess coverage, cross-repository overlap, and citation activity of NTROs across repositories. By harvesting and integrating metadata from the University of Bologna’s institutional CRIS system, the institutional repository AMS Acta, the general-purpose repository Zenodo, the disciplinary archive Software Heritage, and OpenCitations to gather citation information, we analyse the availability of UNIBO-affiliated NTROs and show that, while the UNIBO CRIS platform (i.e., IRIS) remains the primary registry for information on NTROs, a substantial number of them are hosted exclusively in external repositories. These findings highlight structural gaps in tracking NTROs in UNIBO IRIS and underline the need for improved interoperability and coordinated Open Science strategies and policies, at least at the local level, to ensure recognition of diverse research outputs.

Publications doi: 10.3390/publications14020023

Authors: Kay Smarsly

Large language model (LLM) chatbots, as a widely used form of generative artificial intelligence, have reduced the marginal cost of producing publication-style manuscripts and have expanded feasible routes for manipulating citation metrics within the publishing ecosystem. Citation-based indicators (e.g., the h-index, the i10-index, and total citation counts) remain embedded in research evaluation and are sensitive to indexing practices of bibliographic databases, with Google Scholar providing broad coverage combined with comparatively limited curation. In this study, a systematic literature review is conducted to synthesize reported mechanisms of citation-metric manipulation and to examine limitations of citation-metric use, including evidence reported in civil engineering. A Google Scholar proof-of-concept case study examines whether the indexing of LLM-assisted, non-peer-reviewed documents with concentrated references to a target author is associated with changes in author-level citation metrics under platform-specific conditions. After indexing, a stepwise increase in author-level metrics is observed, demonstrating the feasibility of citation-metric manipulation under the platform-specific conditions. Finally, this paper discusses the implications for research integrity and citation manipulation in the era of generative artificial intelligence. It also presents recommendations for researchers, academic institutions and evaluation committees, publishers and editors, bibliographic database providers, and funding institutions and policymakers.

Publications doi: 10.3390/publications14020022

Authors: Karen Blackmore Xin Gu Shaleeza Sohail

Government funding programs administered by the Australian Research Council (ARC) aim to advance national research priorities while generating scholarly and socio-economic impact. This study employs a descriptive bibliometric benchmarking approach to examine the relationship between funding levels and scholarly output for publications explicitly acknowledging ARC support. Using project-level funding data linked with journal articles published between 2009 and 2016, we analyze 10,565 ARC-funded projects receiving a total of AUD 4.6 billion and producing 54,639 journal publications. On average, each project received approximately AUD 437,720 and generated five publications, corresponding to a cost of about AUD 84,700 per article. We compare research productivity, citation impact, and return on investment across ARC Discovery and Linkage programs, as well as between STEM and HASS disciplines. The results reveal no strong correlation between funding amount and either publication volume or citation impact across ARC programs. STEM projects generally exhibit higher returns on investment and citation impact; however, a subset of HASS projects achieves exceptionally high efficiency relative to funding received. Notably, projects funded below AUD 100,000 demonstrate the highest return on investment in terms of both publication productivity and normalized citation impact. These findings suggest that smaller grants can yield disproportionately high scholarly returns, offering important implications for research funding allocation, efficiency evaluation, and performance assessment in public research systems.

Publications doi: 10.3390/publications14020021

Authors: Elise Lupon Grégoire Micicoi

The rapid integration of generative artificial intelligence into scientific publishing is reshaping how academic text can be produced, revised, and scaled. While transparent and limited use of AI for language support may be acceptable, a new structural vulnerability may be emerging in medical publishing: the large-scale production of short, plausible, and weakly individualized correspondence across multiple specialties. In this viewpoint, we describe and conceptualize a pattern that may be termed synthetic authorship, defined not as undisclosed AI use alone, but as a reproducible mode of scholarly output structurally facilitated by automation. We focus particularly on letters to the editor, a format that combines brevity, rapid editorial handling, and formal indexation, and may therefore be especially exposed to this phenomenon. Based on recurring patterns observed in PubMed-indexed literature, including unusually high publication velocity, abrupt thematic dispersion, and stylistic uniformity across unrelated domains, we argue that such outputs may challenge the authenticity, epistemic value, and editorial function of scientific correspondence. We do not present empirical proof of misconduct, but rather outline a conceptual framework for understanding this emerging risk and propose proportionate editorial safeguards, including cross-domain pattern detection and contextual assessment of authorship coherence. As AI lowers the threshold for generating domain-plausible commentary at scale, scientific publishing must adapt its integrity frameworks accordingly. In this context, vigilance toward synthetic authorship may become an essential component of editorial responsibility and post-publication quality control.

Publications doi: 10.3390/publications14010020

Authors: Niels Taubert

This review paper reviews research literature on Diamond Open Access (DOA) journals—sometimes also called Platinum Open Access—that was produced after this journal segment started to become a priority in European research policy around 2020. It contextualizes the current science policy debate, critically examines different understandings of DOA, and reviews studies on the role of such journals in scholarly communication. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyond understanding this particular journal segment, as it also challenges established views of the global system of scholarly communication.

Publications doi: 10.3390/publications14010019

Authors: Zhuoxi Tan Xin Yang Qinyu Chen Tao Chen

To address the efficiency and cost limitations of traditional manual cataloging, this study proposes a large language model-driven automated cataloging workflow in which the Metadata Extraction Agent (MEA), Description Cataloging Agent (DCA), Subject Analysis & Indexing Agent (SAIA), and Quality Control Agent (QCA) collaborate to perform cataloging tasks. Experiments are conducted using a dataset of over 33,000 CNMARC bibliographic records from a University Library, together with data from the Chinese Library Classification (5th edition). Meanwhile, the agent-based workflow framework directly employs large language models without additional enhancement techniques, thereby providing a useful experimental benchmark for evaluating future AI-assisted cataloging systems. The results show that the framework performs well in metadata recognition, bibliographic description, and macro-level classification tasks, and can relatively stably generate standardized records. However, limitations remain in fine-grained semantic indexing and the interpretation of complex contexts. Therefore, in light of the capability limitations revealed by the experimental results, the study argues that fully automated end-to-end cataloging relying solely on generative AI is not yet entirely feasible. Future improvements should integrate techniques such as retrieval-augmented generation, supervised fine-tuning, and structured reasoning prompts, while establishing traceable mechanisms to enhance the reliability of intelligent cataloging.

Publications doi: 10.3390/publications14010018

Authors: Diego Lara-Haro Alexander Haro-Sarango Patricia López-Fraga Angel Esquivel-Valverde

Epistemology underpins the scientific method by clarifying what counts as knowledge, which forms of evidence are admissible, and how procedures can legitimately support conclusions. Under accelerated publishing conditions, these assumptions are often left implicit, which can weaken the inferential coherence of peer-reviewed manuscripts. This study aimed to model reviewers’ perceived epistemological deficiencies as a multidimensional construct with an overarching global component. A 14-item instrument covering four latent domains was administered to 183 peer reviewers from a Latin American academic network. A second-order structural equation model was estimated using SEM with DWLS (lavaan). The model showed excellent fit (CFI ≈ 1.00; RMSEA = 0.000; SRMR = 0.033) and strong factor loadings, indicating a coherent global factor alongside distinct domain-specific components. Reviewers’ accumulated experience was positively associated with the global factor (β = 0.047; p = 0.013), whereas the recent volume of reviews was not statistically significant (p = 0.254). These results suggest that epistemological scrutiny may reflect more stable evaluative competencies than short-term reviewing activity. The instrument can inform editorial rubrics and reviewer training aimed at strengthening problem–theory–method coherence and reflexive methodological justification. Because the measure captures perceptions within a single regional network, further validation across disciplines and cultural contexts is recommended.

Publications doi: 10.3390/publications14010017

Authors: Cristian Zahn-Muñoz Patricio Viancos-González Nancy Alarcón-Henríquez Bastián Aravena-Niño Ezequiel Martínez-Rojas

The emergence of artificial intelligence tools in scientific production is generating significant challenges for scientific integrity and editorial governance, prompting journals and publishers to develop normative guidelines for their use. This study analyzes the current state of guideline implementation among Latin American journals indexed in Scopus and classified according to the Scimago Journal Rank (SJR). A quantitative approach was adopted, complemented by a descriptive documentary analysis based on a detailed review of the websites of 1119 journals from 17 Latin American countries. The collected data were systematized using Excel and analyzed through descriptive and inferential statistical techniques. The results indicate that only 27.2% of journals have explicit guidelines on the use of artificial intelligence, with a predominantly regulatory rather than punitive orientation that prioritizes technical support while restricting practices that compromise human intellectual control. Additionally, statistically significant differences were identified according to quality indicators, showing that journals with higher quality levels are more likely to have such guidelines. Overall, the findings reveal an incipient and heterogeneous regulatory development, underscoring the need to strengthen and harmonize editorial guidelines on artificial intelligence in order to safeguard transparency, clarify the responsibilities of the actors involved in the production and publication process, and protect the integrity of scientific communication.

Publications doi: 10.3390/publications14010016

Authors: Ricardo Curto-Rodríguez Alberto Leal-Matilla Daniel Ferrández Rafael Marcos-Sánchez

In the information society, open data is an important resource for creating economic value. This study conducts a systematic review, following the PRISMA methodology, of articles published between 2000 and 2025 in Scopus and Web of Science that include the terms Open Data and Spain (in Spanish or English) in their title and/or abstract, with the aim of assessing how Law 37/2007 on the reuse of public sector information has influenced the publications analyzed. After identifying 240 articles in Scopus and 109 in Web of Science and applying the exclusion criteria, we observe that 37 studies use the Diamond Open-Access publishing route. The results are organized into four categories corresponding to the research questions, which represent a meaningful theoretical contribution and enhance current knowledge on open data research in Spain. The identification of obstacles to the effective use of open data—such as the lack of standardization, poor information quality, and the vague definition of reuse conditions—entails practical implications of significant value for managers of open data portals seeking to improve their initiatives.

Publications doi: 10.3390/publications14010015

Authors: Alexander Haro-Sarango Silvia Cachay-Salcedo Julián Coronel-Reyes Jessica Saavedra-Vasconez Elizabeth Proaño-Altamirano Rosa Salcedo-Dávalos

This article examines how the Global Innovation Index (GII) has become the dominant technical language for assessing and legitimizing countries’ innovation performance, and what this implies for middle-income economies such as Ecuador and Peru. We conduct a systematic review of 89 Scopus-indexed studies, combining bibliometrics with natural language processing of abstracts. The results reveal a largely optimistic discourse that frames innovation as a national, systemic construct—structured around institutions, human capital, infrastructure, market and business sophistication—while relying heavily on standardized GII metrics. Topic modeling and sentiment analysis show limited critical scrutiny of the index itself. The comparative analysis of Ecuador and Peru highlights persistent gaps between innovation inputs and outputs, with Peru leading in human capital and markets but lagging in business sophistication, and Ecuador constrained by institutional and market weaknesses. We argue that the GII should be used as a diagnostic and reform tool, not merely as a reputational ranking.

Publications doi: 10.3390/publications14010014

Authors: Danakul Seitimbetova Kalima Tuyenbayeva Darukhan Karzhaubayeva Naim Ürkmez Galiya Ibrayeva

Digital transformation of libraries is a key driver of the development of scholarly communication, open access, and knowledge management; however, its sustainability largely depends on institutional and legal conditions. This study examines the level of legal literacy among library professionals and the institutional barriers affecting the digital transformation of academic and public libraries in the Republic of Kazakhstan. A mixed-methods research design was employed, combining a quantitative online survey of library professionals with a qualitative analysis of open-ended responses provided by library managers. The findings indicate that, despite a relatively high level of basic digital skills, legal literacy related to copyright, licensing, and open access remains insufficiently institutionalized. Significant differences were identified between academic and public libraries, reflecting variations in their institutional missions and managerial priorities. Based on the interpretation of empirical results and their comparison with international literature, the study proposes a conceptual model of digital–legal transformation of libraries that integrates digital competencies, legal literacy, and institutional support mechanisms. Additionally, a phased roadmap is developed to support the sustainable implementation of open-access practices and the development of institutional repositories within a nascent open science ecosystem. The study’s results inform the development of institutional digital strategies for libraries and contribute to the design of professional development programs for library staff.

Publications doi: 10.3390/publications14010013

Authors: Samantha Broadhead Henry Gonnet Marianna Tsionki

Through this qualitative systematic review, the authors ask the following: To what extent is the 300-word abstract fit for purpose in representing art and design practice-based research outputs on small and/or specialist institutional repositories? The abstract is an important part of the metadata when an Arts Practice-Based Output (APBO) is deposited on a repository. APBOs are non-traditional item types resulting from creative/artistic research processes. Examples include exhibitions, artefacts and digital videos. Little is known about how effectively these abstracts communicate research processes and insights across the art and design sector. This study aims to investigate how well the abstract communicates information about the arts practice-based research through a systematic review of APBOs. The eligibility criteria for inclusion in the review were as follows: APBOs must be from the date range January 2019 to January 2024, be an item type where the 300-word abstract is required, the abstract must be part of the publicly available metadata for the item, and outputs must be practice-based and from the art and design field. The date range (2019–2024) was employed because, during this time, APBOs had gained recognition in the wider research environment. APBOs from the reviewers’ institutional repository were not included in this study to avoid bias that could skew the results of the review. The data repositories from small and/or specialist Higher Education Institutions in the United Kingdom were searched for outputs which appeared to meet the eligibility criteria. These types of institution prioritise and produce more of these output types. A quality tool appropriate for creative/artistic research was applied to the identified dataset of APBOs. The resulting 27 APBOs’ 300-word abstracts were analysed using a thematic approach. Findings suggest that the 300-word abstracts contained information about the quality indicators such as whether the project got funding, the identities of prestigious collaborators and/or dissemination vehicles, and the international recognition of the research. Other identified themes were methodologies, contribution to knowledge, subject matter and item type.

Publications doi: 10.3390/publications14010012

Authors: Suzan Yalçın Sıddika Songül Yalçın

Background: The One Health framework emphasizes the interconnectedness of human, animal, and environmental health and is closely linked with the United Nations Sustainable Development Goals (SDGs). This study conducted a longitudinal bibliometric analysis of the Ankara Üniversitesi Veteriner Fakültesi Dergisi to assess how its scientific output from 2007 to 2024 reflects evolving One Health and sustainability-related research priorities. Methods: A total of 978 records covering the journal’s entire SCI-indexed period were retrieved from the Web of Science (WoS). Bibliometric analyses were conducted in R Studio (v4.5.1) using the Bibliometrix/Biblioshiny package. Keyword standardization, synonym harmonization, and clustering were applied to generate keyword co-occurrence networks, thematic maps, and multi-period thematic evolution analyses (2007–2013; 2014–2019; 2020–2024). WoS–SDG tagging was integrated and manually validated to evaluate alignment with sustainability and One Health domains. Results: The analysis revealed a clear thematic transition over time. Early publications focused on classical veterinary and production-oriented topics such as reproduction, physiology, nutrition, and livestock performance. During the mid-period, increasing emphasis was placed on epidemiology, pathogen detection, and antimicrobial resistance. In the most recent period, molecular diagnostics, infectious disease ecology, and environmental health emerged as central clusters. SDG 3 (Good Health and Well-Being) remained dominant but declined from approximately 79% of publications in 2007–2014 to 69% in 2020–2024, while SDG 13 (Climate Action) increased markedly after 2019, reaching mean values around 10%, indicating diversification toward environmental sustainability. The growing integration of diagnostic terms such as Polymerase Chain Reaction, cytokines, and histopathology reflects increasing research capacity and methodological modernization consistent with One Health priorities. Conclusions: The journal has undergone a substantial evolution from a predominantly traditional veterinary focus toward a more integrative, interdisciplinary, and sustainability-oriented research agenda aligned with One Health and SDG frameworks.

Publications doi: 10.3390/publications14010011

Authors: Luís Eduardo Pilatti Luiz Alberto Pilatti Gustavo Dambiski Gomes de Carvalho Luis Mauricio Martins de Resende

We compare the publication performance of open-access (OA) and subscription-based (SB) journals in Engineering using journal-level indicators from Scopus (CiteScore 2023 view; data collected on 2 December 2024). We analysed 3013 active Engineering journals with an assigned CiteScore quartile (Q1–Q4, where Q1 denotes the highest CiteScore quartile), of which 770 are labelled OA in Scopus; the remaining journals in each stratum were classified as SB. We stratified journals by CiteScore quartile and by the top 10% CiteScore percentile. We examined four indicators for 2020–2023: CiteScore 2023, total citations, number of published documents, and the percentage of cited articles. Because citation and publication counts are strongly right-skewed, we report medians and use Mann–Whitney tests with effect sizes (Cliff’s delta) and false discovery rate correction; Welch tests on log-transformed counts are used as sensitivity analyses. SB journals exhibit substantially higher citation and document medians across all quartiles and in the top 10% stratum, whereas CiteScore medians are very similar between access models. OA journals represent about one quarter of Engineering journals in Scopus, but remain underrepresented in the top 10% segment (125 of 484). Overall, OA provides a competitive level of impact, while SB titles still dominate accumulated visibility and editorial scale in Engineering.

Publications doi: 10.3390/publications14010010

Authors: Rachel Elizabeth Scott

Academic libraries support the mission and vision of their institution; in the case of most universities, this means providing a variety of services and resources in support of the research enterprise. This case study documents one library’s support for open access publishing to explore how it directly supports the research mission of a Carnegie Research 2 university. By leveraging relationships and investing existing collections resources and workflows—the sequence of decisions and labor through which librarians make scholarly and artistic works discoverable, accessible, and support their preservation—in open access publishing, the library has materially increased the visibility of locally produced scholarship and become a more visible campus collaborator.

Publications doi: 10.3390/publications14010009

Authors: Tindaro Cicero

The increasing emphasis on responsible research assessment has renewed the need for conceptual tools that help communicate the complementary roles of quantitative and qualitative evaluation. This essay proposes an interpretative metaphor that frames bibliometric indicators as the “blood tests” of research systems—heuristic devices that reveal multidimensional aspects of system vitality, balance, and dysfunction. The metaphor, grounded in standard categories of clinical diagnostics (hematological, hepatic, renal, lipidic, and cardiovascular panels), provides an accessible language for scholars and policymakers in research. Each bibliometric technique—ranging from publication and citation counts to patent analysis, altmetrics, and topic modelling—is associated with a diagnostic function such as screening, monitoring, or early risk detection. By linking established principles of responsible metrics (DORA, Leiden Manifesto, Metric Tide, CoARA) with the professionalization of evaluators, the essay situates the metaphor within current debates on bibliometric literacy and the ethical interpretation of indicators. Rather than prescribing metrics or decision rules, the contribution invites reflection on how evaluators can interpret bibliometric signals diagnostically—as contextual evidence for institutional learning, strategic decision-making, and the cultivation of healthy, adaptive research systems. Consistent with the essay format, this contribution does not propose a new evaluative methodology nor empirical validation. Instead, it advances a heuristic and communicative framework intended to emphasize the holistic, contextual, and professionally informed interpretation of quantitative indicators in the evaluation of research activity.

Publications doi: 10.3390/publications14010008

Authors: Zinaida Sokova Valery Kruzhinov Anna Glazkova

The integration of digital technologies into historical research is a global trend; however, its manifestation varies across national academic traditions. This study investigates the explicit articulation and terminological adoption of digital methods in Russian historical science by analyzing the prevalence and dynamics of specific technological terms in a large corpus of publications. We first constructed a controlled thesaurus of 166 digital technologies by manually curating keyphrases from Russia’s primary specialized journal in the field (“Istoricheskaya Informatika”, Historical Informatics). This vocabulary was then used to perform text-mining on two distinct corpora: a broad sample of 95K Russian-language history articles from various journals (2004–2024) and a focused sample of publications on the Great Patriotic War History from the Russian Science Citation Index (RSCI, 2014–2023). Our quantitative analysis reveals the frequency, trends, and thematic context of digital method mentions. The findings highlight a significant disparity between the specialized discourse of “Istoricheskaya Informatika” and the mainstream historical publications, while also identifying specific areas (such as archaeological studies) where certain technologies have gained traction. This research offers a novel, data-driven perspective on the “digital turn” in Russian historiography and contributes to the comparative study of digital humanities’ global development.

Publications doi: 10.3390/publications14010007

Authors: Chee Kong Yap

In 2003, as a young lecturer, I saw research as a craft to be learned, not a tally to be scored [...]

Publications doi: 10.3390/publications14010006

Authors: Paul Longley Arthur Lydia Hearn Isabel Smith

Over the past two decades, museums have increasingly experimented with digital technologies to connect with broader contemporary culture. This review article investigates the role crowdsourcing can play in transforming museums into more engaged environments, raising visibility and inclusivity, and involving diverse voices and populations in knowledge-creation processes. Its contribution is to provide an overview of the history, definitions and concepts of crowdsourcing, and examples of crowdsourcing policies and practices that have been adopted by museums. Participation in crowdsourcing has been influenced by gender, education, and socio-economic and cultural background. In the past, historical structures and traditions and infrastructural complexities have stood in the way of wider diversity and inclusivity. As museums move increasingly online, the circulation of information outside the museum’s walls is just as important as the specialist knowledge held within. Museums can play a leading role in public communication by reaching those who constitute the ‘crowd’. This paper explores how museums, through strong collaboration and various forms of crowdsourcing, such as citizen science and participatory engagement, can offer more wide-ranging open access for the sharing and democratisation of knowledge.

Publications doi: 10.3390/publications14010005

Authors: Dedy Kurniadi Rahmat Gernowo Bayu Surarso

University rankings based on scientometric indicators frequently rely on compensatory aggregation models that allow extreme values to dominate the evaluation, while also remaining sensitive to outliers and unstable weighting procedures. These issues reduce the reliability and interpretability of the resulting rankings. This study proposes a hybrid BWM–GRA–PROMETHEE (BGP) framework that combines judgement-based weighting Best-Worst Method (BWM), outlier-resistant normalization Grey Relational Analysis (GRA), and a non-compensatory outranking method Preference Ranking Organization Methods for Enrichment Evaluation (PROMETHEE II). The framework is applied to an expert-validated set of scientometric indicators to generate more stable and behaviorally grounded rankings. The results show that the proposed method maintains stability under weight and threshold variations and preserves ranking consistency even under outlier-contaminated scenarios. Comparative experiments further demonstrate that BGP is more robust than Additive Ratio Assesment (ARAS), Multi-Attributive Border Approximation Area Comparison (MABAC), and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), achieving the highest Spearman. This study contributes a unified evaluation framework that jointly addresses three major methodological challenges in scientometric ranking, outlier sensitivity, compensatory effects, and instability from data-dependent weighting. By resolving these issues within a single integrated model, the proposed BGP approach offers a more reliable and methodologically rigorous foundation for researchers and policymakers seeking to evaluate and enhance research performance.

Publications doi: 10.3390/publications14010004

Authors: Emanuela Gualdi-Russo Luciana Zaccagni

Secondary research is a cornerstone of health sciences, with substantial implications for clinical practice and health policy. Within the systematic review process, a key step is assessing study quality and risk of bias. Among the tools available for evaluating observational studies, the Newcastle–Ottawa Scale (NOS) holds a prominent position and is widely applied in medical research. However, ambiguities and excessive subjectivity have been noted in its application. In this commentary, we discuss the Newcastle–Ottawa Scale guidelines, providing illustrative examples and practical recommendations for completing its items. Improving the accuracy of risk-of-bias assessment is crucial for enhancing the reliability of data synthesis and interpretation in the health sciences.

Publications doi: 10.3390/publications14010003

Authors: Simone Fühles-Ubach Elisabeth Kaliva Martina Echtenbruck

The concept of the ‘teaching library’, which originated in the Anglo-American world, describes all activities of libraries in the field of promoting information, media, and data literacy, as well as other skills in dealing with analog and digital media. Although data literacy is explicitly mentioned in this definition, many training courses in academic libraries seem to focus more on promoting library use, information, and media literacy. Given that the creation of data management plans, along with the indexing, storage, and reuse of research data, have become standard elements of the research process, this article discusses the growing importance of academic libraries in teaching data literacy. It presents a modular course framework, developed in exchange with the university library, as a reusable model for data literacy education. The primary objective is to introduce this framework and illustrate its application; preliminary, exploratory insights from a self-assessment survey are provided to support this presentation. The limited participant count in the pre- and post-evaluations restricts the statistical generalizability of the findings but provides a solid empirical impression of the effectiveness of the course format. Results indicate substantial learning progress in fields where academic libraries have proven expertise. The main conclusion is that such library-integrated interdisciplinary courses provide a valuable framework for data literacy education and highlight strategic areas for library involvement.

Publications doi: 10.3390/publications14010002

Authors: Jean Paul Simon Castillo-Nuñez Carlos Alberto Minchon-Medina Angie Clemente-Vega Nohelia Rosa Vallenas-Aroni Marile Lozano-Lozano Myriam Báez-Sepúlveda

Open access (OA) has expanded scholarly publishing, yet concerns remain about the sustainability of journals indexed in selective databases. This study analyzes editorial predictors of discontinuation among 8730 journals simultaneously registered in the Directory of Open Access Journals (DOAJ) and indexed in Scopus, including 58 (0.66%) discontinued titles as of June 2025 (latest available update at the time of data extraction). The analyses revealed that a journal’s history of prior discontinuation was the strongest and most consistent predictor of future instability, confirming that discontinuation follows a path-dependent pattern rather than isolated events. Financial structure also played a decisive role: journals applying other editorial fees beyond standard article processing charges (APCs) were nearly four times more likely to experience discontinuation (IRR = 3.877, p = 0.048), while those following standardized APC models showed a protective but non-significant tendency (IRR = 0.378, p = 0.084). Journal age exhibited a modest yet significant positive effect (IRR = 1.032, p = 0.031), suggesting that older titles face a gradual accumulation of risk over time. By contrast, editorial practices such as plagiarism detection, waiver policies, and turnaround time showed no significant association. Overall, the findings indicate that discontinuation in Scopus-indexed OA journals is statistically associated with historical trajectories, financial transparency, and governance capacity, rather than by routine editorial procedures.

Publications doi: 10.3390/publications14010001

Authors: Zhihe Yang Xiaoyu Zhou Yuxin Jiang Xinjie Zhang Qihui Gao Yanzhu Lu Anqi Yang

In response to the persistent imbalance between the rapid expansion of scholarly publishing and the constrained availability of qualified reviewers, an empirical investigation was conducted to examine the feasibility and boundary conditions of employing Large Language Models (LLMs) in journal peer review. A parallel corpus of 493 pairs of human expert reviews and GPT-4o-generated reviews was constructed from the open peer-review platform PeerJ Computer Science. Analytical techniques, including keyword co-occurrence analysis, sentiment and subjectivity assessment, syntactic complexity measurement, and n-gram distributional entropy analysis, were applied to compare cognitive patterns, evaluative tendencies, and thematic coverage between human and AI reviewers. The results indicate that human and AI reviews exhibit complementary functional orientations. Human reviewers were observed to provide integrative and socially contextualized evaluations, while AI reviews emphasized structural verification and internal consistency, especially regarding the correspondence between abstracts and main texts. Contrary to the assumption of excessive leniency, GPT-4o-generated reviews demonstrated higher critical density and functional rigor, maintaining substantial topical alignment with human feedback. Based on these findings, a collaborative human–AI review framework is proposed, in which AI systems are positioned as analytical assistants that conduct structured verification prior to expert evaluation. Such integration is expected to enhance the efficiency, consistency, and transparency of the peer-review process and to promote the sustainable development of scholarly communication.

Publications doi: 10.3390/publications13040067

Authors: Kacper Sieciński Marian Oliński

Generative artificial intelligence (GenAI) is rapidly permeating research practices, yet knowledge about its use and topical profile remains fragmented across tools and disciplines. In this study, we present a cross-disciplinary map of GenAI research based on the Web of Science Core Collection (as of 4 November 2025) for the ten tool lines with the largest number of publications. We employed a transparent query protocol in the Title (TI) and Topic (TS) fields, using Boolean and proximity operators together with brand-specific exclusion lists. Thematic similarity was estimated with the Jaccard index for the Top–50, Top–100, and Top–200 sets. In parallel, we computed volume and citation metrics using Python and reconstructed a country-level co-authorship network. The corpus comprises 14,418 deduplicated publications. A strong concentration is evident around ChatGPT, which accounts for approximately 80.6% of the total. The year 2025 shows a marked increase in output across all lines. The Jaccard matrices reveal two stable clusters: general-purpose tools (ChatGPT, Gemini, Claude, Copilot) and open-source/developer-led lines (LLaMA, Mistral, Qwen, DeepSeek). Perplexity serves as a bridge between the clusters, while Grok remains the most distinct. The co-authorship network exhibits a dual-core structure anchored in the United States and China. The study contributes to bibliometric research on GenAI by presenting a perspective that combines publication dynamics, citation structures, thematic profiles, and similarity matrices based on the Jaccard algorithm for different tool lines. In practice, it proposes a comparative framework that can help researchers and institutions match GenAI tools to disciplinary contexts and develop transparent, repeatable assessments of their use in scientific activities.

Publications doi: 10.3390/publications13040066

Authors: Roberto da Silva José Palazzo M. de Oliveira Viviane Moreira

Ranking research groups plays a crucial role in various contexts, such as ensuring the fair allocation of research grants, assigning projects, and evaluating journal editorial boards. In this paper, we analyze the distribution of h-indexes within research groups and propose a single metric to quantify their overall performance, termed the α-index. This index integrates two complementary aspects: the homogeneity of members’ h-indexes, captured by the Gini coefficient (g), and the h-group, an extension of the individual h-index to groups. By combining both uniformity and collective research output, the α-index provides a consistent and equitable metric for comparative evaluation, essentially calculated as the average relative h-group multiplied by (1−g) and normalized by the maximum value of this quantity across all analyzed groups. We describe the full procedure for computing the index and its components and illustrate its application to computer science conferences, where program committees are compared through a resampling procedure that ensures fair comparisons across groups of different sizes. Additional results are presented for postgraduate programs, further demonstrating the method’s applicability. Correlation analyses are used to establish rankings; however, our primary goal is to recommend a fairer index that reduces deviations from those currently used by governmental agencies to evaluate conferences and graduate programs. The proposed approach offers a more nuanced assessment than simply averaging members’ h-indexes and can be applied broadly–for example, to university departments and research councils–contributing to a more equitable distribution of research funding, an issue of increasing importance.

Publications doi: 10.3390/publications13040065

Authors: Andrew M. Petzold Marcia D. Nichols

Recent decades have seen a rise of anti-science rhetoric, fueled by scientific scandals and failures of peer review, and the rise of trainable generative AI spreading misinformation. We argue, moreover, that the continued erosion of scientific authority also arises from inherent features in science and academia, including a reliance on publication as a method for gaining professional credibility and success. Addressing this multifaceted challenge necessitates a concerted effort across several key areas: strengthening scientific messaging, combating misinformation, rebuilding trust in scientific authority, and fundamentally rethinking academic professional norms. Taking these steps will require widespread effort, but if we want to rebuild trust with the public, we must make significant and structural changes to the production and dissemination of science.

Publications doi: 10.3390/publications13040064

Authors: Qiuyu Zhu Jing Li Yifei Chen Yuqing Zhang Jing Li Junren Ming

Open Access (OA) has emerged as a pivotal driver shaping the dissemination scope and academic impact of research findings. To clarify the impact of publishing models such as open access on the citation performance of biochemical papers, this study selects 177,745 biochemistry professional papers included in the core collection of the Web of Science (WoS CC) as the research data; we conduct an analysis of citation and impact advantages in biochemistry research. Employing correlation analysis, baseline regression modeling, and two-way ANOVA, our analysis indicates that: OA publications in biochemistry exhibit notable citation and impact advantages, which are positively correlated with the degree of openness, and the key determinants of the OA advantage encompass funding sources, reference count, and publication region. At present, China accounts for a disproportionately small proportion of OA papers in this field. In the context of the open-science paradigm, Chinese academic journals must systematically address their developmental bottlenecks and formulate publication innovation strategies to enhance the quality of academic publishing.

Publications doi: 10.3390/publications13040063

Authors: Bor Luen Tang

There is now widespread use of large language (LLM)-based generative artificial intelligence (AI) tools in academic research and writing. While these are convenient, quick, and output enhancing, they also arguably incur ethical issues, such as questionable authenticity and plagiarism. Here, I explore epistemological aspects of AI use in academic writing and posit that there is evidence for three related pitfalls in AI use that should not be ignored. These include (1) epistemic detriment or harm in terms of illusions of understanding, (2) potential for cognitive dulling or impairment, and (3) AI dependency (both habitual and/or emotional). Thus, any potential infringements of academic ethics aside, AI use in academic writing incurs intrinsic problems that are epistemic in nature. These epistemic downsides call for restraint and moderation beyond regulatory measures to address ethical issues in AI use.

Publications doi: 10.3390/publications13040062

Authors: Reyner Pérez-Campdesuñer Alexander Sánchez-Rodríguez Rodobaldo Martínez-Vivar Margarita De Miguel-Guzmán Gelmar García-Vidal

This study analyzes the temporal evolution of citations received by academic articles in the field of micro, small, and medium-sized enterprises (SMEs) and internationalization processes, with the aim of identifying patterns of growth and decline in scientific visibility. Based on a dataset of 1936 articles retrieved from Scopus, we constructed an article–year panel that enabled the application of multiple statistical approaches. Discrete-time survival models showed that the annual probability of receiving at least one citation is initially low, increases slightly until the fifth year, and then declines progressively thereafter. Negative binomial regression confirmed significant growth during the first five years, followed by a slowdown. Kaplan–Meier estimations reinforced this finding by showing that the cumulative proportion of articles receiving their first citation within a decade remains limited. These results confirm that citation dynamics are nonlinear and subject to early obsolescence, with most visibility concentrated in the short term. Importantly, this temporal bias in indexing and evaluation systems disproportionately favors recent publications while undervaluing older but still influential research. Such structural bias has profound implications for visibility and equity in scholarly communication, especially for disciplines and regions where citation cycles are longer. The findings thus validate the study’s propositions: first, that citation growth slows significantly after the fifth year, and second, that this slowdown represents a structural bias that amplifies inequities in research evaluation.

Publications doi: 10.3390/publications13040061

Authors: Xuan Wang Xinyi Zhang

The immense potential of artificial intelligence (AI) in academic journal publishing has significantly impacted scholarly communication between stakeholders, leading to increased research into ethical considerations for AI use in academic publishing. Due to the contextual nature of ethics and the ontological base of language as its own object of inquiry, the conceptual framework and underlying ideologies of AI ethics in linguistics deserve attention. In this study, we address the call for these ethical considerations by combining a hybrid thematic analysis (HTA) of the ethical guidelines available on 144 Social Sciences Citation Index (SSCI) linguistics journals’ and 11 corresponding publishers’ websites as of 31 October 2025, and a critical discourse analysis (CDA) case study on Language Testing, a representative journal with self-developed AI ethical guidelines. Through the HTA, we identified seven themes: accountability, authorship, citation practices, copyright, long-term governance, human agency, and transparency. The role allocation of CDA demonstrated that the AI ethical guidelines independently established by the linguistics journal expand the scope of stakeholders to include the sources of research data and technology, covering the informed consent of research participants and the responsibilities of the AI tool operators. Moreover, AI tools are given a beneficialized role, suggesting a more technology-assisted-oriented perspective and reflecting deeper trust in AI’s involvement. Through the findings, our study contributes to the broader understanding of ethical governance in relation to AI usage in discipline-based communication, highlighting the need for a more dialogic and diverse framework to share responsibility among stakeholders to promote the ethical use of AI.

Publications doi: 10.3390/publications13040060

Authors: Karol Król Maria Szkutak Elżbieta Legutko

Granny Josie’s Notebooks are salvaged notebooks written in 1946–1947 during a rural domestic science course for girls. This study aims to extract historically valuable information on the culinary heritage of post-war Poland and the housekeeping role attributed to women, with a specific focus on assessing the performance of Large Language Models (LLMs) in corpus analysis. The research began with an inquiry into the historical context of the notebooks. Three notebooks were digitised and stored in data repositories, then converted into editable vector text. The corpus was analysed with AI, and the results were compared with a text profile prepared by qualified linguists. According to the AI, the texts’ characteristic features are descriptions of nearly ritual food preparation, serving, and table setting. Women appear as central figures in post-war Polish housekeeping, acting as guardians of the hearth and planners and preparers of meals. However, AI’s interpretations were often overly idealised, with embellished descriptions that did not fully reflect the actual text. The digitisation and analysis of Granny Josie’s Notebooks provided new information about the culinary heritage of post-war Poland and preserved these materials from oblivion, while offering insights into the potential application of LLMs in corpus analysis.

Publications doi: 10.3390/publications13040059

Authors: William Viera-Arroyo Lya Vera Martín Moya Duther López Wilson Vásquez-Castillo Carlos Caicedo

Scientific production is a key indicator of a country’s academic and institutional development. This review followed a quantitative and descriptive bibliometric design using Lotka’s Law, aimed at analysing Ecuador’s scientific production in the area of Agricultural and Biological Sciences from 2014 to 2024. The bibliographic data were obtained from the Scopus database, which offers comprehensive coverage of the peer-reviewed literature and standardised metadata. Data (2881 documents) revealed publication patterns, collaboration networks and impact indicators. Lotka’s Law was applied to evaluate and describe author productivity among researchers affiliated with Ecuadorian universities and the Instituto Nacional de Investigaciones Agropecuarias (INIAP). The model yielded an average n-parameter of 2.56, indicating a moderate concentration among a small group of researchers. There was a sustained growth in scientific publications, especially after 2018, with a high proportion published in Q1 and Q2 journals. The institutions with the most relevant affiliations included PUCE, UTM, USFQ, INIAP, ESPOL and UDLA, all maintaining consistent contributions to scientific output. The keyword co-occurrence analysis revealed a thematic focus on biodiversity, taxonomy and conservation. The limitations of this study were related to the fact that the analysis was based only on data retrieved from the Scopus database and that the use of Lotka’s Law assumes a theoretical distribution that does not fully account for contextual factors. Overall, Ecuador’s scientific system shows progress in terms of research productivity; however, it requires further development and the strengthening of institutional and human research capacities to generate more equitable scientific production in terms of the number of researchers.

Publications doi: 10.3390/publications13040058

Authors: Diana Amirbekova Targyn Nauryz Mariyam Taskinbayeva Madina Bigabatova Aasso Ziro

This study examines the evolution of Kazakhstani research in the fields of economics and business research. We analyzed Scopus and Dimensions records for 2019–2023 following a PRISMA-like workflow with fully reproducible queries and time-stamped data extractions. We implemented both Bradford’s law of scattering and collaboration analysis. We report both journal-level (Scopus) and publication-level (Dimensions) results as complementary perspectives. Results show the applicability of Bradford’s law of scattering to research publications in Economics, Econometrics, and Finance, Business, Management, and Accounting, and Decision Sciences in Kazakhstan and globally. Collaboration analysis highlights strong regional ties and diversification. Authorship analysis reveals that 85.1% of publications have a Kazakhstan-affiliated first author. Publications were classified into three categories: Kazakhstan-Only (59.0%, N = 1585), International Collaboration with Kazakhstan-led authorship (31.5%, N = 845), and International Collaboration with Non-Kazakhstan-led authorship (9.5%, N = 255). International collaborations had 69–92% higher citation impact than domestic-only publications. The expansion of citing countries doubled in 2023 compared with 2019. Our contributions to bibliometric analysis and science policy are two-fold. First, we provide a comprehensive comparative analysis of publication patterns between Kazakhstani and global journals in economics and business-related fields, revealing specific areas requiring development. Second, we identify collaboration patterns, including citation analysis of studied fields. The analysis revealed strategies that can be applied in other emerging economies.

Publications doi: 10.3390/publications13040057

Authors: Eldar Knar

Modern approaches to research assessment often treat two independent dimensions: the degree of readiness (the progress of scientific maturity) and the Added Scientific Value (novelty, rigor, reproducibility, and societal significance). The present study aims to develop an integrative model that links the stepwise logic of Scientific Readiness Levels (SRLs) with the continuous evaluation of Added Scientific Value (ASV). To achieve this, we construct a two-dimensional quantitative framework, SRL × ASV, in which discrete readiness levels are combined with the multiplicative aggregation of normalized qualitative indicators—including novelty, rigor, reproducibility, openness, impact, and collaboration. Advancement to a higher readiness level becomes possible only when the evidential criteria are simultaneously satisfied and the ASV threshold value is reached. The model is formally defined and illustrated via the example of Kazakhstan’s national science funding system. The results demonstrate that the integration of SRL and ASV creates a reproducible and transparent decision-making structure in which weak components cannot be compensated by strong ones, and excessive dependence on purely metric-based evaluations is eliminated. By uniting maturity and quality within a single coherent system, the SRL + ASV model bridges the gap between developmental staging and scientific value, transforming research assessment into a transparent, evidence-based, and continuously improvable process applicable to the governance of responsible and reproducible science.

Publications doi: 10.3390/publications13040056

Authors: Tao Zhang Prachuab Tongsri Chakrit Ponathong

The Chengdu–Chongqing Economic Circle (CCEC) represents a key regional development initiative in China. University research collaboration plays a vital role in advancing its innovation ecosystem and supporting sustainable growth. This study examines inter-university collaboration among 47 public universities in the CCEC based on 53,968 co-authored publications from 2005 to 2024. Using bibliometric and visualization techniques in CiteSpace 6.4.R2, it explores the structure and evolution of collaboration from institutional, thematic, and author perspectives. The results reveal a steady expansion of collaborative activities driven by national innovation strategies. Leading institutions such as Sichuan University, UESTC, and Chongqing University act as central hubs connecting diverse research communities. Collaboration has diversified from traditional fields toward interdisciplinary areas including materials, environmental science, and applied mathematics. Author networks are becoming more cohesive, reflecting stronger knowledge integration across universities. The study highlights how policy-driven collaboration fosters regional innovation capacity and provides evidence-based insights for strengthening university networks and advancing the CCEC’s role as a science and technology innovation hub in western China.

Publications doi: 10.3390/publications13040055

Authors: Alexey Remizov Shazim Ali Memon Saule Sadykova

There is a growing need for comprehensive and transparent frameworks in bibliometric evaluation that support fairer assessments and capture the multifaceted nature of research performance. This study proposes a novel methodology for identifying top-performing researchers based on a composite performance index (CPI). Unlike existing rankings, this framework presents a multidimensional approach by integrating sixteen weighted bibliometrics metrics, spanning research productivity, citation, publications in top journal percentiles, authorship roles, and international collaboration, into a single CPI, enabling a more nuanced and equitable evaluation of researcher performance. Data were retrieved from SciVal for 1996–2025. Two ranking exercises were conducted with Kazakhstan as the analytical unit. Subject-specific rankings identified the top 1% authors within different research areas, while subject-independent rankings highlighted the overall top 1%. CPI distributions varied markedly across disciplines. A comparative analysis with the Stanford/Elsevier global top 2% list was conducted as additional benchmarking. The results highlight that academic excellence depends on a broad spectrum of strengths beyond just productivity, particularly in competitive disciplines. The CPI provides a consistent and adaptable tool for assessing and recognizing research performance; however, future refinements should enhance data coverage, improve representation of early-career researchers, and integrate qualitative aspects.

Publications doi: 10.3390/publications13040054

Authors: Nikolina Peša Pavlović Jadranka Stojanovski Iva Grabarić Andonovski

Over the past decade, the Open Science movement has profoundly transformed the way research is conducted, communicated, and assessed [...]

Publications doi: 10.3390/publications13040053

Authors: Annarita Barbaro Maria Cristina Barbaro Federica Napolitani

The Diamond Open Access (OA) model—characterized by the absence of fees for both authors and readers—has gained increasing attention in recent years. A wide range of scholarly journals are using this model, as emerged while mapping the Diamond OA landscape worldwide; however, some still depend on hybrid revenue streams such as print sales, subscriptions, and marginal APCs. A number of recent initiatives underlined the need to increase quality assurance, sustainability, and cooperation within the Diamond OA ecosystem. Among them, the Diamond OA Standard (DOAS), a framework comprising detailed guidelines and a self-assessment tool to facilitate Diamond OA publishing practices, was created by the DIAMAS project, sponsored by the European Commission. Annali dell’Istituto Superiore di Sanità, the official journal of the Italian leading public health research institution, is a Diamond OA journal. To improve transparency and quality, the editorial team used the DOAS self-assessment tool to evaluate its compliance with the standards proposed by DIAMAS and to identify potential areas for improvement. This article presents the process and findings of the DOAS self-assessment tool conducted on Annali ISS, with the aim of sharing insights and support with other journals seeking to align with the DOAS framework.

Publications doi: 10.3390/publications13040052

Authors: Rodrigo Alejandro-Salinas Diego A. Maticorena-Quevedo Alfonso Barnechea-Rey Percy Herrera-Añazco Vicente A. Benites-Zapata

Background: Orthopedic scientific publications play an important role worldwide. Because of the limited evidence in the Latin American literature, we aimed to evaluate the determinants of scientific publication among Peruvian orthopedics as an approach to the Latin American context. Methods: Analytical cross-sectional study. Orthopedic specialists and residents were enrolled during the 52nd Peruvian National Congress of Orthopedics and Traumatology. A form validated by experts was applied to collect variables. The crude and adjusted coefficients were calculated using bivariate and multivariate regression with 95% confidence intervals. Results: A total of 310 participants were included in our study. The prevalence of the scientific orthopedic publication was 34.84%. Multivariate regression showed that, working in a private hospitals, having an interest in tumors and pediatric orthopedics, being involved in teaching activity, belonging to a scientific society other than the Peruvian Society of Orthopedics and Traumatology, having more than one research project, having an international rotation, and active participation in meetings were factors associated with publishing orthopedic scientific articles, while coming from a university in the highlands as an undergraduate and having more than ten shifts per month was associated with publishing fewer scientific articles. Among residents, having had an international rotation was associated with publishing scientific articles. Conclusions: The determinants of scientific production described will serve to increase scientific production in different contexts considering the orthopedist’s training stage.

Publications doi: 10.3390/publications13040051

Authors: Javier Fernando Angulo-Osorio César Daniel Valdivia-Portugal Karina Rosas-Paredes

Research visibility has become a critical issue for universities, yet the institutional conditions that shape it remain underexplored. While Current Research Information Systems (CRISs) provide essential infrastructure for managing publications and researcher profiles, their impact depends on broader governance and cultural factors. This study compares four universities—two in Peru, one in Chile, and one in Spain—that have adopted the Pure CRIS platform. Data were manually extracted from institutional portals and analyzed descriptively, using normalized indicators such as publications per researcher, Sustainable Development Goal (SDG) alignment, and collaboration networks. Although based on a limited sample, the analysis highlights substantial contrasts: European institutions show consolidated integration of CRIS into national evaluation systems, while Latin American universities remain at earlier stages of adoption, with fragmented policies and limited international reach. The findings suggest that technological platforms alone are insufficient; institutional commitment, coherent policies, and academic cultures that value dissemination are decisive. These insights contribute a comparative framework to guide universities, particularly in Latin America, seeking to strengthen their global research visibility.

Publications doi: 10.3390/publications13040050

Authors: Btissam Acim Mohamed Boukhlif Hamid Ouhnni Nassim Kharmoum Soumia Ziti

The recent growth of generative artificial intelligence (AI) has brought new possibilities and revolutionary applications in many fields. It has also, however, created important ethical and security issues, especially with the abusive use of deepfakes, which are artificial media that can propagate very realistic but false information. This paper provides an extensive bibliometric, statistical, and trend analysis of deepfake research in the age of generative AI. Utilizing the Web of Science (WoS) database for the years 2014–2024, the research identifies key authors, influential publications, collaboration networks, and leading institutions. Biblioshiny (Bibliometrix R package, University of Naples Federico II, Naples, Italy) and VOSviewer (version 1.6.20, Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands) are utilized in the research for mapping the science production, theme development, and geographical distribution. The cutoff point of ten keyword frequencies by occurrence was applied to the data for relevance. This study aims to provide a comprehensive snapshot of the research status, identify gaps in the knowledge, and direct upcoming studies in the creation, detection, and mitigation of deepfakes. The study is intended to help researchers, developers, and policymakers understand the trajectory and impact of deepfake technology, supporting innovation and governance strategies. The findings highlight a strong average annual growth rate of 61.94% in publications between 2014 and 2024, with China, the United States, and India as leading contributors, IEEE Access among the most influential sources, and three dominant clusters emerging around disinformation, generative models, and detection methods.

Publications doi: 10.3390/publications13040049

Authors: Eungi Kim Frankline Kipchumba Sein Min

This study evaluates digital object identifier (DOI) hallucination in large language model (LLM)-generated scholarly citations, with a focus on systematic geographic disparities. To conduct this study, we systematically evaluated four LLMs (GPT-4o-mini, Claude-3-haiku, Gemini-2.0-flash-lite, and DeepSeek V3) using standardized information behavior prompts across ten countries with diverse income levels. The models generated 3451 citations, which we validated using the CrossRef API. The results showed that DOI hallucination follows systematic patterns influenced by model choice, geographic context, and publication recency. Hallucination rates exceeded 80% in lower-income countries and increased sharply for publications from the 2020s across all regions. Fabricated citations—citations that appear structurally complete but contain invalid DOIs—were especially prevalent in countries such as India and Bangladesh. Model-specific factors showed the strongest association with hallucination, followed by income level and publication period. These findings raise concerns about the epistemic reliability of LLM-generated scholarly references and underscore the need for region-aware training, real-time DOI validation, and robust verification protocols in academic contexts.

Publications doi: 10.3390/publications13040048

Authors: Stephen A. Bustin

Peer review fails when it is delivered without fairness, accountability, or respect. When unprofessional reviews are communicated without editorial intervention, they undermine trust, distort scientific dialogue, and disproportionately harm early-career and underrepresented researchers. This article combines a detailed case study with evidence from the literature to illustrate how reviewer misconduct can escalate into editorial failure, and why such outcomes are avoidable. Mechanisms already exist to prevent them, including pre-screening, structured review forms, training, appeals processes, and reviewer tracking, but require consistent application. The central problem is not the absence of guidance, but the lack of enforcement. Restoring credibility in peer review depends on editors treating oversight as a duty of stewardship, ensuring that critique remains rigorous, constructive, and respectful.

Publications doi: 10.3390/publications13040047

Authors: Franko O. Garcia-Solorzano Yolanda Angulo-Bazán Sofia Soriano-Martinez Olenka Farfan-Zapata Leonid Lecca

Background: Focusing scientific research on the health needs of the population could ensure the development of context-specific solutions. In Peru, prioritization has been proposed as a strategy to address this issue. However, the alignment of Peruvian scientific production on tuberculosis (TB) with the national TB research priorities (TBprios) has not been evaluated. Methods: We conducted a bibliometric analysis in Web of Science, Scopus, LILACS, SciELO, and PubMed to identify original articles focused on TB, with at least one author with Peruvian affiliation. Then, we reviewed the general objectives of each study included and verified their alignment with any TBprios. Results: We found that 73% of Peruvian scientific articles were aligned with some of the national research priorities on TB, especially those related to epidemiology and diagnostics, although no increased trends in alignment were identified across the study period. In addition, in an exploratory analysis we found that fewer than 20% of aligned studies reported receiving national funding. Conclusion: Substantial alignment was observed between the research outputs identified and TBprios. Nonetheless, this high level of alignment could also reflect the significance of TB within the social and public health agenda of Peru.

Publications doi: 10.3390/publications13040046

Authors: George Peppas Leonidas Papachristopoulos Giannis Tsakonas

We are living in an era where the demand for Open Access to knowledge is growing and the need for transparency in scientific publishing is becoming imperative. The question that arises at this stage is whether openness in knowledge constitutes the Achilles heel of the once profitable legacy publishing industry or whether it is the Trojan horse of the latter for increasing its revenues. At the same time, the question of whether Open Access publishers can ensure their sustainability through this model remains unanswered. This study implements a multi-year analysis (2019–2023) comparing the performance of Open Access and legacy publishers. Using a set of financial ratios—grouped by profitability, liquidity, efficiency, and solvency, as well as data on firm size (revenues, assets, and employee counts), we assess their financial performance. The results indicate that legacy publishers have enormous scale, stable profitability, and high leverage, but low liquidity and return on equity. On the other hand, OA publishers, although smaller, have higher returns, better liquidity, and almost zero borrowing, but with greater annual volatility. The study discusses that OA publishers, despite their small size, can be as profitable as or even more profitable than traditional publishers, thanks to flexible structures and fast cash flows, but remain vulnerable due to limited resources and the risk of acquisition. Furthermore, legacy publishers maintain their dominance by leveraging their scale, strong brands, and investment capacity while adopting or acquiring OA models, creating a competitive environment where scale and strategic differentiation are decisive.

Publications doi: 10.3390/publications13030045

Authors: Yutainten Engkus Kuswarno Uud Wahyudin Ira Mirawati

In governmental agencies, science communication often focuses on one-way knowledge transfer, even on digital platforms designed for interaction and engagement. This study examines the strategies used by Indonesia’s National Research and Innovation Agency (BRIN) across four science communication models—deficit, dialogue, participatory, and scientific agency—to identify shortcomings and opportunities for more inclusive public engagement. Using a qualitative case study approach, we analyzed digital content produced by BRIN, conducted 25 semi-structured interviews, held focus group discussions, and observed digital data. The data were thematically coded using NVivo software 12. Our findings show that BRIN mainly adopts the deficit model, using digital platforms primarily for broadcasting rather than genuine engagement. While some dialogue occurs, it often takes the form of “Controlled Dialogue”—a performative use of interactive tools limited by institutional and bureaucratic obstacles. These barriers impede genuine participation. We recommend a strategic hybrid model that aligns communication methods with specific objectives, offering actionable strategies for public research institutions in the Global South to enhance meaningful public engagement.

Publications doi: 10.3390/publications13030044

Authors: Marta Irene Flores Polanco Carlos Alberto Echeverría Mayorga

This article presents a comprehensive bibliometric analysis of scientific production in Central America between 1996 and 2023, based on data indexed in the Scopus database. The study frames the investigation within the broader context of scientific visibility and regional development, aiming to evaluate trends in research productivity, thematic specialization, and patterns of scientific collaboration across Belize, Guatemala, Honduras, El Salvador, Nicaragua, Costa Rica, and Panama. A total of 35,146 articles authored by researchers affiliated with institutions in Central America were analyzed using indicators such as publication volume, subject areas, journal impact and co-authorship data provided by Scopus. The findings reveal a consistent annual growth rate of 7%, yet with marked disparities among countries. Costa Rica, Panama, and Guatemala account for 82% of the total scientific output, while the remaining countries contribute only 18%. Research activity is primarily concentrated in the medical, agricultural, biological, and environmental sciences. Over 80% of publications involve international collaboration, predominantly with the United States, Spain, and Mexico, whereas intraregional cooperation remains limited. The analysis underscores the region’s reliance on global research networks and reveals persistent internal asymmetries in scientific development. The results suggest the need for increased investment in national research systems, stronger regional collaboration, and targeted strategies to balance scientific production across countries.

Publications doi: 10.3390/publications13030043

Authors: Jiwei Zhang Jiafu Liu

AI technology is reshaping the knowledge ecosystem, bringing both challenges and opportunities to libraries. This article examines the transformation of librarians from “knowledge guardians” to “intelligent collaborators.” It discusses the professional challenges and practical dilemmas introduced by AI through the lenses of value reorientation and paradigm shift. The paper argues that librarians should actively adopt new technologies, engage in ongoing learning, and develop more resilient knowledge service systems, while also identifying their key roles and potential pathways for transformation within smart library frameworks.

Publications doi: 10.3390/publications13030042

Authors: Reyner Pérez-Campdesuñer Alexander Sánchez-Rodríguez Rodobaldo Martínez-Vivar Margarita De Miguel-Guzmán Gelmar García-Vidal

The volume of scientific publications has increased exponentially over the past decades across virtually all academic disciplines. In this landscape of information overload, objective criteria are needed to identify high-impact research. Citation counts have traditionally served as a primary indicator of scientific relevance; however, questions remain as to whether they truly reflect the intrinsic quality of a publication. This study investigates the relationship between citation frequency and a wide range of editorial, authorship, and contextual variables. A dataset of 339,609 articles indexed in Scopus was analyzed, retrieved using the search query TITLE-ABS-KEY (management) AND LIMIT-TO (subarea, “Busi”). The research employed a descriptive analysis followed by two predictive modeling approaches: a Random Forest algorithm to assess variable importance, and a binary logistic regression to estimate the probability of a paper being cited. Results indicate that factors such as journal quartile, country of affiliation, number of authors, open access availability, and keyword usage significantly influence citation outcomes. The Random Forest model explained 94.9% of the variance, while the logistic model achieved an AUC of 0.669, allowing the formulation of a predictive citation equation. Findings suggest that multiple determinants beyond content quality drive citation behavior, and that citation probability can be predicted with reasonable accuracy, though inherent model limitations must be acknowledged.

Publications doi: 10.3390/publications13030041

Authors: Shaoxiong Brian Xu Guangwei Hu

China’s retraction crisis has raised concerns about research integrity and accountability within its scientific community and beyond. To address this issue, we proposed in an earlier publication that Chinese research funders incorporate retraction records into the evaluation of research funding applications by establishing a retraction-based review system. This review system would debar researchers with retraction records from applying for funding for a specified period. However, our earlier proposal lacked practical guidance on how to operationalize such a review system. In this article, we expand on our proposal by fleshing out the proposed ten debarment determinants and offering a framework for quantifying the duration of funding ineligibility. Additionally, we outline the critical steps for implementing the retraction-based review system, address the major challenges to its effective and sustainable adoption, and propose viable solutions to these challenges. Finally, we discuss the benefits of implementing the review system, emphasizing its potential to strengthen research integrity and foster a culture of accountability in the Chinese academic community.

Publications doi: 10.3390/publications13030040

Authors: Altyeb Ali Abaker Omer Yajie Dong

The growing use of bibliometric methods in literature reviews has intensified concerns about methodological transparency and consistency. This study compares English-language reviews authored by China-affiliated and non-China-affiliated researchers between 2015 and 2024. Through bibliometric content analysis and co-word network mapping, it evaluates the following: (1) the use and purposes of bibliometric software; (2) the clarity of methodological reporting, including software versions, threshold settings, data preprocessing, and database selection; (3) the extent to which limitations are acknowledged and recommendations proposed; and (4) the dominant conceptual themes shaping research practices. The analysis covers 50 highly cited reviews (25 per group) and 4000 additional papers for thematic mapping. Findings show both convergence and divergence: while tools such as VOSviewer, CiteSpace, Gephi, and Bibliometrix are widely adopted, non-China-affiliated studies exhibit greater transparency and reflexivity, whereas China-affiliated research often emphasizes output metrics and underreports methodological challenges. These contrasts reflect broader epistemological norms and research cultures. This study underscores the need for unified reporting standards and contributes to meta-research by offering practical guidance to improve the transparency, comparability, and rigor of bibliometric-supported literature reviews.

Publications doi: 10.3390/publications13030039

Authors: Fernando Sánchez-Pita Mario Benito-Cabello Belén Puebla-Martínez

The editorial policies of science journals have an impact on access to scientific knowledge. One of the most effective ways to share knowledge with the entire society is to offer it free of charge. Considering the international recognition of Scopus and Web of Science, this study analyses 28 scientific journals in the field of communication that are indexed under the “Communication” category in both databases in order to review their editorial decisions regarding the dissemination of articles they publish. By taking a descriptive approach, the authors have examined the inner workings and design, as well as aspects related to ethics and transparency, as key components of this policy. The findings indicate that most journals are influenced by digital publishing platforms and that various features examined in this study are offered by these platforms by default. This is especially true in terms of design, which simultaneously enables yet influences each journal’s editorial policy. Together with the need for financial support and adequate human resources, this situation makes it difficult to implement an editorial policy free of external encroachment. This article concludes by emphasising the importance of establishing editorial policies that promote open access as a standard practice, thereby reinforcing the democratisation of access to scientific knowledge. It is recommended to strengthen institutional support for journals operating under the diamond model, promote their visibility and thematic specialisation, enhance technical and visual aspects, and clearly articulate ethical commitments within their editorial policies. In short, this analysis provides a comprehensive overview of both strengths and areas of improvement, offering recommendations to help these journals optimise their contribution to the global academic ecosystem.

Publications doi: 10.3390/publications13030038

Authors: Yaqin Li Jinyuan Shi Yuequan Yang

In the era of data elements, it is extremely necessary and practically important to analyze network characteristics and evolutionary trends in academic research collaboration in the field of data assets research, which can provide valuable insights for promoting deep cooperation of scholars and enhancing their collaborative efficiency. However, existing studies on data assets research rarely delve into key differentiating characteristics and core thematic priorities between Chinese and international samples of collaboration networks. Based on bibliometric methods and social network analysis, a systematic comparative analysis between Chinese collaboration networks and international collaboration networks is conducted via CiteSpace software by using core literature from the China National Knowledge Infrastructure (CNKI) and Web of Science Core Collection, developed by Clarivate Analytics (WoS). Through observation, we find that the number of publications in this field has reached a preliminary scale with distinct differences in research focus and collaborative features between cooperation networks in China (CNCs) and international cooperation networks (ICNs). In recent years, Chinese samples have primarily focused upon research themes related to data value realization, such as data rights confirmation, data assets accounting, and data trusts. The overall connectivity of CNCs seems relatively weak, and a stable core author group has not formed, while collaborations in CNCs are predominantly localized and short-term. In contrast, international samples in recent years have mainly addressed the contextual application of data assets, exhibiting a collaboration network characterized by multi-center, interdisciplinary, and cross-institutional synergy, while core authors in ICNs are closely interconnected and their connectivity and structure are generally stronger than those of CNCs.

Publications doi: 10.3390/publications13030037

Authors: Junic Kim

This study investigates how generative artificial intelligence (AI) is reshaping academic libraries from passive information providers into proactive knowledge facilitators. Drawing on the qualitative case study of a South Korean university library that implemented an AI-powered chatbot, the study examines its impact on service personalization, user engagement, and research efficiency. The thematic analysis of interviews with users and staff reveals how AI integration transforms the user experience and redefines professional roles. Findings contribute to scholarly discussions on library innovation, demonstrating how generative AI enables adaptive, anticipatory knowledge services in academic environments shaped by digital transformation.

Publications doi: 10.3390/publications13030036

Authors: Muhammad Iqhrammullah Derren D. C. H. Rampengan Muhammad Fadhlal Maula Ikhwan Amri

The Research Integrity Risk Index (RI2), introduced as a tool to identify universities at risk of compromised research integrity, adopts an overly reductive methodology by combining retraction rates and delisted journal proportions into a single, equally weighted composite score. While its stated aim is to promote accountability, this commentary critiques the RI2 index for its flawed assumptions, lack of empirical validation, and disproportionate penalization of institutions in low- and middle-income countries. We examine how RI2 misinterprets retractions, misuses delisting data, and fails to account for diverse academic publishing environments, particularly in Indonesia, where many high-performing universities are unfairly categorized as “high risk” or “red flag.” The index’s uncritical reliance on opaque delisting decisions, combined with its fixed equal-weighting formula, produces volatile and context-insensitive scores that do not accurately reflect the presence or severity of research misconduct. Moreover, RI2 has gained significant media attention and policy influence despite being based on an unreviewed preprint, with no transparent mechanism for institutional rebuttal or contextual adjustment. By comparing RI2 classifications with established benchmarks such as the Scimago Institution Rankings and drawing from lessons in global development metrics, we argue that RI2, although conceptually innovative, should remain an exploratory framework. It requires rigorous scientific validation before being adopted as a global standard. We also propose flexible weighting schemes, regional calibration, and transparent engagement processes to improve the fairness and reliability of institutional research integrity assessments.

Publications doi: 10.3390/publications13030035

Authors: Timur Narbaev Diana Amirbekova Aknar Bakdaulet

Higher education and science (HES) is one of the key drivers of a country’s economic growth. In this study, we examine national projects and research capacity in HES in Kazakhstan from 2014 to 2024. We conducted a content review and scientometric analysis with network and temporal visualizations. Our data sources included policy documents, statistical reports, and the Scopus database. Our findings suggest that, while Kazakhstan aligns with global trends in the field (e.g., digitalization, scientometrics monitoring, and internationalization), these are achieved through a state-led, policy-driven approach shaped by its post-Soviet context. Additionally, we note a dual structure in Kazakhstan’s HES sector, characterized by a strong top-down direction and increasing institutional engagement. In terms of the thematic trends from the temporal analysis, the country experienced a three-staged evolution: foundational reforms and system modernization (2014–2017), capacity building and evaluation (2018–2021), and, most recently, strategic expansion, inclusivity, and globalization (2022–2024). Throughout the analyzed period, low R&D intensity, disciplinary imbalances, and structural barriers still undermine desired development efforts in HES. The analyzed case of Kazakhstan can serve as “lessons learned” for policymakers and researchers working in the science evaluation and scholarly communication area in similar emerging or transition countries.

Publications doi: 10.3390/publications13030034

Authors: Gergely Ferenc Lendvai Petra Aczél Péter Sasvári

This study investigates how differing national research governance models impact academic performance by comparing European Research Council (ERC) grant winners in the social sciences and humanities from France and the Netherlands. Situated within the broader context of centralized versus decentralized research systems, the analysis aims to understand how these structures shape publication trends, thematic diversity, and collaboration patterns. Drawing on Scopus and SciVal data covering 9996 publications by 305 ERC winners between 2019 and 2023, we employed a multi-method approach, including latent Dirichlet allocation for topic modeling, compound annual growth rate analysis, and co-authorship network analysis. The results show that neuroscience, climate change, and psychology are dominant domains, with language and linguistics particularly prevalent in France and law and political science in the Netherlands. French ERC winners are more likely to be affiliated with national or sectoral institutions, whereas in the Netherlands, elite universities dominate. Collaboration emerged as a key success factor, with an average of four co-authors per publication and network analyses revealing central figures who bridge topical clusters. International collaborations were consistently linked with higher visibility, while single-authored publications showed limited impact. These findings suggest that institutional context and collaborative practices significantly shape research performance in both countries.

Publications doi: 10.3390/publications13030033

Authors: Alexandre López-Borrull Carlos Lopezosa

This article presents a scoping review of the academic literature published between 2021 and 2024 on the intersection of generative artificial intelligence (AI) and disinformation. Drawing from 64 peer-reviewed studies, the review examines the current research landscape and identifies six key thematic areas: political disinformation and propaganda; scientific disinformation; fact-checking; journalism and the media; media literacy and education; and deepfakes. The findings reveal that generative AI plays a dual role: it enables the rapid creation and targeted dissemination of synthetic content but also offers new opportunities for detection, verification, and public education. Beyond summarizing research trends, this review highlights the broader societal and practical implications of generative AI in the context of information disorder. It outlines how AI tools are already reshaping journalism, challenging scientific communication, and transforming strategies for media literacy and fact-checking. The analysis also identifies key policy and governance challenges, particularly the need for coordinated responses from governments, platforms, educators, and civil society actors. By offering a structured overview of the field, the article enhances our understanding of how generative AI can both exacerbate and help mitigate disinformation, and proposes directions for research, regulation, and public engagement.

Publications doi: 10.3390/publications13030032

Authors: Faisal Kalota Benedicta Frema Boamah Hesham Allam Tyler Schisler Grace Witty

This research aims to understand the evolving role of academic libraries, focusing on student perceptions of current services and their vision for the future. Data was collected using a survey at a midwestern research university in the United States. The survey contained both quantitative and qualitative questions. The objective of the survey was to understand the current utilization of library services and students’ future visions for academic libraries. Qualitative and quantitative analysis techniques were utilized as part of the study. Thematic analysis was employed as part of the qualitative analysis, while descriptive and inferential analysis techniques were utilized in the quantitative analysis. The findings reveal that many students use libraries for traditional functions such as studying and accessing resources. There is also an inclination toward digitalization due to convenience, accessibility, and environmental sustainability; however, print materials remain relevant as well. Another finding was a lack of awareness among some students regarding available library services, indicating a need for better marketing and communication strategies. Students envision future libraries as technology-driven spaces integrating artificial intelligence (AI), augmented reality (AR), virtual reality (VR), and innovative collaborative environments. Ethical considerations surrounding AI, including privacy, bias, and transparency, are crucial factors that must be addressed. Some of the actionable recommendations include integrating ethical AI, implementing digital literacy initiatives, conducting ongoing usability and user experience (UX) research within the library, and fostering cross-functional collaboration to enhance library services and student learning.

Publications doi: 10.3390/publications13030031

Authors: Marcelo Pereira Duarte Fernando Manuel Pereira de Oliveira Carvalho

The purpose of this review is to synthesise the accumulated knowledge on Global Innovation Index (GII) research. We utilised a corpus from the Web of Science Core Collection to systematically examine the antecedents, consequences, and relationships among the GII’s dimensions. Additionally, we employed the bibliometric techniques of bibliographic coupling and co-citation analysis to identify the leading areas of GII research and the foundational literature in this field. Our systematic review of GII empirical research allowed us to graphically represent the significant relationships among its dimensions. The findings from the bibliographic coupling revealed five recent lines of investigation in GII research: configurational methods; innovation efficiency and policy; competitiveness, entrepreneurship, and sustainable development; innovation rankings; and culture. Furthermore, the co-citation analysis highlighted four clusters of literature that have contributed to GII research. We aim to enhance the field of Innovation Studies by showcasing the current state of research on the GII, one of the most promising tools for measuring innovation activity, and to provide insights into potential future research avenues to further develop this area of study.

Publications doi: 10.3390/publications13030030

Authors: Xiaoting Chen Abdelghani Maddi Yanyan Wang

This article investigates the architecture and institutional distribution of policy tools supporting open science (OS) in China. Based on a corpus of 199 policy documents comprising 25,885 policy statements, we apply an AI-assisted classification to analyze how the Chinese government mobilizes different types of tools. Using Qwen-plus, a large language model developed by Alibaba Cloud and fine-tuned for OS-related content, each policy statement is categorized into one of fifteen subcategories under three main types: supply-oriented, environment-oriented, and demand-oriented tools. Our findings reveal a strong dominance of supply-oriented tools (63%), especially investments in infrastructure, education, and public services. Demand-oriented tools remain marginal (11%), with little use of economic incentives or regulatory obligations. Environment-oriented tools show more balance but still underrepresent key components like incentive systems and legal mandates for open access. To deepen the analysis, we introduce a normalized indicator of institutional focus, which captures the relative emphasis of each policy type across administrative levels. Results show that supply-oriented tools are concentrated at top-level institutions, reflecting a top-down governance model. Demand tools are localized at lower levels, highlighting limited strategic commitment. Overall, China’s OS policy mix prioritizes infrastructure over incentives, limiting systemic transformation toward a more sustainable open science ecosystem.

Publications doi: 10.3390/publications13020029

Authors: Pablo Dorta-González Emilio Gómez-Déniz

This work aims to use a suitable regression model to study a count response random variable, namely, the number of citations of a research paper, that is affected by some explanatory variables. The count variable exhibits substantial variation, as the sample variance is larger than the sample mean; thus, the classical Poisson regression model seems not to be appropriate. We concentrate our attention on the negative binomial regression model, which allows the variance of each measurement to be a function of its predicted value. Nevertheless, the process of citations of papers may be divided into two parts. In the first stage, the paper has no citations, while the second part provides the intensity of the citations. A hurdle model for separating documents with citations and those without citations is considered. The dataset for empirical application consisted of 43,190 research papers in the Economics and Business field from 2014–2021, which were obtained from The Lens database. Citation counts and social attention scores for each article were gathered from the Altmetric database. The main findings indicate that both collaboration and funding have positive impacts on citation counts and reduce the likelihood of receiving zero citations. Open access (OA) via repositories (green OA) correlates with higher citation counts and a lower probability of zero citations. In contrast, OA via the publisher’s website without an explicit open license (bronze OA) is associated with higher citation counts but also with a higher probability of zero citations. In addition, open access in subscription-based journals (hybrid OA) increases citation counts, although the effect is modest. There are clear disciplinary differences, with the prestige of the journal playing a significant role in citation counts. Articles with lower expert ratings tend to be cited less frequently and are more likely to be cited zero times. Meanwhile, news and blog mentions boost citations and reduce the likelihood of receiving no citations, while policy mentions also enhance citation counts and significantly lower the risk of being cited zero times. In contrast, patent mentions have a negative impact on citations. The influence of social media varies: X/Twitter and Wikipedia mentions increase citations and reduce the likelihood of being uncited, whereas Facebook and video mentions negatively impact citation counts.

Publications doi: 10.3390/publications13020028

Authors: Mojca Tancer Verboten Dean Korošak

This article examines the resilience and volatility of academic publishing at the University of Maribor (UM) from 2004 to 2023, a period marked by significant economic and policy shifts in Slovenia. Using employment data from UM’s internal records and publication data from OpenAlex, we analyze the relationship between employed researchers and publishing authors. Despite a significant drop in researcher employment during the economic recession (2009–2013), the number of unique authors publishing under the UM affiliation surprisingly increased. Analysis of author turnover reveals a striking pattern: high short-term volatility (annual churn ~40–50%) contrasted with significant mid-term stability (5-year churn ~8–10%). Survival analysis confirms this pattern, revealing high initial attrition among publishing authors followed by long-term persistence for a core group of researchers. Network analysis of co-authorship patterns shows increasing resilience to the targeted removal of influential authors over time. Most significantly, we identify a fundamental shift in network structure around 2016, when the co-authorship network transitioned from dissassortative to assortative mixing patterns, coinciding with recovery in employment growth. This shift suggests a profound change in collaboration dynamics, from a system where highly connected researchers primarily collaborated with less-connected ones to one where highly connected researchers increasingly collaborate with each other. We discuss the implications for research policy and university management, emphasizing the need to balance short-term performance metrics with long-term stability and resilience.

Publications doi: 10.3390/publications13020027

Authors: Akira Muto

Innovation in science and technology arises from balanced supports for basic research, applied research, and societal implementation. However, changes in Japanese science policy that shifts toward top–down, evaluation-based, and competitive funding practices appear to have undermined Japan’s long-term research sustainability and innovation potential. The “selection and concentration” strategy (prioritization of specific research areas) and “competition principle”, combined with persistent reduction in Management Expenses Grants, have significantly altered Japan’s research environment for the worse. Together with these policy changes, the introduction of fixed-term contracts in academia has increased instability at both the institutional and the individual levels and has diminished the time and resources available for long-term basic research. Academic careers in science have become less attractive, as evidenced by declining doctoral student enrollment. These changes threaten the potential for scientific discoveries that lead to innovation. Although initiatives such as the introduction of University Research Administrators (URAs) have been implemented to support researchers, such efforts remain insufficient to counterbalance the systemic challenges faced by Japan’s research ecosystem. To re-establish a stable research environment, rethinking the strategy may be necessary, including restoration of stable institutional funding, sustainable career pathways, and balanced funding allocation to basic science that foster seeds for future innovation.

Publications doi: 10.3390/publications13020026

Authors: Elizabeth de Sousa Vieira Jorge Cerdeira

The literature has shown that neonatal deaths contribute largely to the total number of deaths in children under 5 years of age worldwide and that 39% of all neonatal deaths recorded in 2019 were in Africa. Neonatal conditions (NCs) are the main cause of these losses. Therefore, NC research is critical to improve the ability to prevent, predict, detect, treat, and manage neonatal problems. However, this research must be properly funded to arrive at outcomes of interest. Regarding the funding of NC research, no study has addressed this issue. In this regard, a bibliometric analysis of the funding information reported in publications can assist scientists in seeking funds for ongoing or new NC research and those involved in developing and implementing strategies to improve NC funding. Using a bibliometric analysis, this study identified the African and non-African funders mentioned in articles on NC research in Africa published between 1990 and 2019. A set of indicators gives an initial picture of funding activities. The results show that the involvement of African and non-African funders in NC research has increased; NC research is highly dependent on foreign funders, especially from the United States of America (USA) and the United Kingdom (UK); and the funding comes from few funders. Strategies are necessary to reduce the fragility of the funding structure of NC research due to its high dependence on foreign funders and concentration on few funders.

Publications doi: 10.3390/publications13020025

Authors: Antonia Pilic Louise Henaff Christoph A. Steffen Hanna Helene Linß Antonia Isabelle Dreyer Madeleine Batke Ole Wichmann Vanessa Piechotta Thomas Harder

Systematic reviews (SRs) reflect the best available evidence for informing vaccination recommendations. This study presents a bibliometric analysis of vaccination-related SRs aiming to uncover research trends. Vaccination-related SRs published from 2011 to 2023 in MEDLINE, Embase, the Cochrane Library and the Living Overview of Evidence database were considered. Trends over time, disease/pathogen, topic, population, geographical location, accessibility, methodological quality, and overlap were descriptively analyzed using R. A total of 2275 SRs were identified, most of which were freely accessible (n = 2083, 91.7%). The annual number of published SRs increased more than twelvefold from 2011 to 2023. COVID-19 (n = 861, 37.8%), influenza (n = 328, 14.4%), Human papillomavirus (n = 248, 10.9%), and pneumococcal disease (n = 152, 6.7%) were the most frequently addressed diseases/pathogens. Efficacy/effectiveness (n = 1066, 46.9%) and safety of vaccines (n = 812, 35.7%) were the most common topics. The methodological quality of SRs on intervention topics (n = 1376) was mostly critically low (n = 1155, 84.0%). Several SRs were identified that covered similar diseases/pathogens, topics and populations, indicating duplication and overlap, particularly for COVID-19. Our analysis showed a large increase in the number of published vaccination-related SRs. The results provide a basis for understanding the current state and priorities in vaccination research and decrease the overlap potential in newly developed SRs.

Publications doi: 10.3390/publications13020024

Authors: Andrea Tomassi Andrea Falegnami Elpidio Romano

Scientific disinformation has emerged as a critical challenge at the interface of science and society. This paper examines how false or misleading scientific content proliferates across both social media and traditional media and evaluates strategies to counteract its spread. We conducted a comprehensive literature review of research on scientific misinformation across disciplines and regions, with particular focus on climate change and public health as exemplars. Our findings indicate that social media algorithms and user dynamics can amplify false scientific claims, as seen in case studies of viral misinformation campaigns on vaccines and climate change. Traditional media, meanwhile, are not immune to spreading inaccuracies—journalistic practices such as sensationalism or “false balance” in reporting have at times distorted scientific facts, impacting public understanding. We review efforts to fight disinformation, including technological tools for detection, the application of inoculation theory and prebunking techniques, and collaborative approaches that bridge scientists and journalists. To empower individuals, we propose practical guidelines for critically evaluating scientific information sources and emphasize the importance of digital and scientific literacy. Finally, we discuss methods to quantify the prevalence and impact of scientific disinformation—ranging from social network analysis to surveys of public belief—and compare trends across regions and scientific domains. Our results underscore that combating scientific disinformation requires an interdisciplinary, multi-pronged approach, combining improvements in science communication, education, and policy. We conducted a scoping review of 85 open-access studies focused on climate-related misinformation and disinformation, selected through a systematic screening process based on PRISMA criteria. This approach was chosen to address the lack of comprehensive mappings that synthesize key themes and identify research gaps in this fast-growing field. The analysis classified the literature into 17 thematic clusters, highlighting key trends, gaps, and emerging challenges in the field. Our results reveal a strong dominance of studies centered on social media amplification, political denialism, and cognitive inoculation strategies, while underlining a lack of research on fact-checking mechanisms and non-Western contexts. We conclude with recommendations for strengthening the resilience of both the public and information ecosystems against the spread of false scientific claims.

Publications doi: 10.3390/publications13020023

Authors: Andy Wai Kan Yeung

The Global Quality Score (GQS) is one of the most frequently used tools to evaluate the content quality of online health information. To the author’s knowledge, it is frequently misnamed as the Global Quality Scale, and occasionally secondary sources are cited as the original source of the tool. This work aimed to reveal the current situation especially regarding the citations among published studies. Web of Science, Scopus, and PubMed were queried to identify papers that mentioned the use of the GQS. Among a total of 411 analyzed papers, 45.0% misnamed it as Global Quality Scale, and 46.5% did not cite the primary source published in 2007 to credit it as the original source. Another 80 references were also cited from time to time as the source of the GQS, led by a secondary source published in 2012. There was a decreasing trend in citing the primary source when using the GQS. Among the 12 papers that claimed that the GQS was validated, half of them cited the primary source to justify the claim, but in fact the original publication did not mention anything about its validation. To conclude, future studies should name and cite the GQS properly to minimize confusion.

Publications doi: 10.3390/publications13020022

Authors: Ueric José Borges de Souza Beni Jequicene Mussengue Chaúque Evgeni Evgeniev Gabev Fernando Rosado Spilki Fabrício Souza Campos

This manuscript introduces the Scientific Peer Review Index (SPR-index), a novel metric designed to enhance the H-index by incorporating verified peer review records from the Web of Science database. The SPR-index aims to provide a more comprehensive assessment of researchers by considering not only their publication record but also their contributions to the peer review system—an essential yet often overlooked aspect of academic work. Given the increasing difficulty in finding qualified reviewers, this metric aims to recognize and incentivize peer review efforts. The SPR-index is calculated as the product of a researcher’s H-index, normalized by their number of publications, and the total number of verified peer reviews, offering a more nuanced measure of their academic impact. Additionally, we propose factoring in review length to acknowledge researchers who provide in-depth evaluations that exceed the average word count. However, its successful implementation depends on improvements in Clarivate’s peer review data collection, particularly in enhancing the accuracy and completeness of verified review records. Researchers must also ensure their reviews are visible in the Web of Science by selecting appropriate visibility settings. The further refinement and validation of this metric are needed to support its widespread adoption in the academic community.

Publications doi: 10.3390/publications13020021

Authors: Jianping Wang Senqiang Wang Yanan Liu

In the context of the rapid evolution of digital technology and the growing demand for user-centered services, the question of how to effectively implement marketing strategies in libraries has become important in research. This article introduces the theoretical background and development process of domestic and international research on library marketing in the digital era, systematically combs through the current situation of domestic library marketing research, and puts forward the existing deficiencies and problems. Based on the discovery of library marketing strategy research insufficiency and other problems, this paper uses STP theory (segmentation, targeting, and positioning) to conduct a systematic strategy analysis of library operation and management and puts forward countermeasure suggestions for the cross-integration of disciplines, the improvement and optimization of the new theory of library marketing, the integration of STP theory and public library strategy, and the innovation of the research direction.

Publications doi: 10.3390/publications13020020

Authors: Shlomit Hadad Daphne Raban Noa Aharony

This bibliometric study investigates Open Access (OA) publication and citation trends in Austria, Israel, and Mexico from 2010 to 2020—three countries with comparable research output but differing OA infrastructures. (1) Background: The study examines how national OA policies, funding mechanisms, and transformative agreements (TAs) shape publication and citation patterns across disciplines. (2) Methods: Using Scopus data, the analysis focuses on four broad subject areas (health, physical, life, and social sciences), applying both three-way ANOVA and a Weighted OA Citation Impact index that adjusts citation shares based on the proportional representation of each subject area in national research output. An OA Engagement Score was also developed to assess each country’s policy and infrastructure support. (3) Results: OA publications consistently receive more citations than closed-access ones, confirming a robust OA citation advantage. Austria leads in both OA publication volume and weighted impact, reflecting its strong policy frameworks and TA coverage. Israel, while publishing fewer OA articles, achieves high citation visibility in specific disciplines. Mexico demonstrates strengths in repositories and Diamond OA journals but lags in transformative agreements. (4) Conclusions: National differences in OA policy maturity, infrastructure, and publishing models shape both visibility and citation impact. Structural limitations and indexing disparities may further affect how research from different regions and disciplines is represented globally, emphasizing the need for inclusive and context-sensitive frameworks for evaluating OA engagement.

Publications doi: 10.3390/publications13020019

Authors: Assaf Botzer

Numerous papers have demonstrated that by using a varying coefficients model (VCM), researchers can unveil patterns of interactions between variables that could otherwise remain hidden if using the more popular regression model with an interaction term. Hence, one would expect high acceptance of the VCM as a tool for studying statistical interactions in datasets. Yet, the current paper shows that the VCM is still struggling to migrate from journals in which methods are presented to journals in which methods are utilized. First, a search in Google Scholar with the phrase “varying coefficients” returned ~79,200 results in comparison to returning ~2,710,000 results with the phrase “interaction term”. Second, a bibliometric analysis of publications with the VCM showed that in many research domains, there were more publications with the VCM in journals on methods than publications with the VCM in journals for empirical investigations. Economics and environmental studies stood out with many more publications with the VCM in empirical journals than in journals on statistical methods. The gap between the high acclaims of the VCM in the statistical literature and its low utilization rate in practice should be of concern to the research community. The possible reasons for this gap and its potential remedies are discussed.

Publications doi: 10.3390/publications13020018

Authors: Anna Małgorzata Kamińska

The scientific literature is expanding at an unprecedented pace, making it increasingly difficult for researchers, students, and professionals to extract relevant insights efficiently. Traditional academic publishing offers static, one-size-fits-all content that does not cater to the diverse backgrounds, expertise levels, and interests of readers. This paper explores how generative AI can dynamically personalize scholarly content by tailoring summaries and key takeaways to individual user profiles. Nine scientific articles from a single journal issue were used to create the dataset, and prompt engineering was applied to generate tailored insights for exemplary personas: a digital humanities and open science researcher, and a mining and raw materials industry specialist. The effectiveness of AI-generated content modifications in enhancing readability, comprehension, and relevance was evaluated. The results indicate that generative AI can successfully emphasize different aspects of an article, making it more accessible and engaging to specific audiences. However, challenges such as content oversimplification, potential biases, and ethical considerations remain. The implications of AI-powered personalization in scholarly communication are discussed, and future research directions are proposed to refine and optimize AI-driven adaptive reading experiences.