Purpose In scientific notation, “a.u.” denotes atomic units, but in figure labels it is also widely used to mean arbitrary units. This technically incompatible dual usage motivated this study, which examined the prevalence, disciplinary distribution, and editorial handling of the use of “a.u.” to denote arbitrary units of intensity in peer-reviewed publications. Methods A cross-sectional bibliometric content analysis was conducted using 1,915 research articles published between 2020 and 2024 in six representative high-impact journals. Articles with intensity axes labeled “a.u.” were identified and coded by field, context, and whether the intended meaning was explicitly defined. Results Of the 1,915 articles sampled, 1,140 (59.5%) contained at least one figure with “a.u.” on an intensity axis. Among these articles, only 14.3% explicitly clarified that the label denoted arbitrary rather than atomic units. Significant inter-journal variation was observed: Optics Express had the highest prevalence of “a.u.” intensity axis labeling (71.1%) and the lowest clarification rate (8.1%), whereas PLOS One had the lowest prevalence (41.9%) and the highest clarification rate (25.7%). Conclusion The conflation of “a.u.” as atomic units with “a.u.” as arbitrary units is a pervasive, editorially tolerated notational ambiguity that can undermine scientific precision and reproducibility. The unambiguous alternative “arb. units” should be adopted, and explicit editorial guidelines should be implemented.
Purpose Universities increasingly issue institutional artificial intelligence (AI) guidance, but it remains unclear whether university-linked journals translate such guidance into publicly visible and usable editorial instructions. This study audited generative AI governance in Asian university-linked journals indexed in Scopus and traceable in SCImago and examined how core policy requirements co-occurred. Methods This cross-sectional policy audit examined 75 unique university-linked Asian journals. Two trained coders independently coded the original 80-record journal-field frame. Across 11 paired pre-adjudication variables, reliability was substantial to almost perfect: Cohen κ=0.747–0.945, quadratic weighted κ=0.944 for the maturity index using 77 valid 0–4 pairs, and Krippendorff α=0.748–0.966. Journal-level analyses included latent class analysis and Firth penalized logistic regression. Results Forty-two journals (56.0%) permitted AI use with disclosure and author accountability, 15 (20.0%) had no explicit AI statement, and 1 (1.3%) had a dedicated AI policy page. Disclosure and accountability signals were common (73%–76%), whereas the six operational requirements were less visible (24%–32%). The count of operational elements per journal was strongly bimodal, and latent class analysis separated journals into operationally nonarticulated (n=49) and operationally articulated (n=26) configurations. Firth regression identified positive associations with articulated configuration membership for health sciences and West Asia, although the estimates were imprecise; the confidence intervals for the other field, region, and ranking estimates included the null. Conclusion The journals showed polarized public articulation of AI policy rather than a gradual continuum. Policy visibility did not necessarily translate into policy usability. The configurations should be interpreted as exploratory patterns, not as a maturity taxonomy.
Purpose Medical education research has expanded rapidly, yet no study has comprehensively mapped its intellectual structure across publications with available reference data. We conducted a reference co-citation analysis to identify the foundational works, intellectual communities, and structural trends within this subset of publications. Methods We analyzed 174,729 medical education publications with reference data, representing 28.1% of 622,407 records from four bibliographic databases for 2000–2025. After deduplicating reference identifiers, we constructed a co-citation network of 7,203 frequently cited references, applied Louvain community detection, tracked the citation trajectories of 15 key theoretical frameworks, and examined structural evolution across four time periods using size-invariant network metrics. Results The co-citation network was organized into 13 major intellectual communities, the largest of which were Learning Theory and Qualitative Methods, Assessment and Competency-Based Education, and Simulation and Patient Safety. Theoretical frameworks exhibited three trajectory patterns: sustained growth, peak-then-decline, and rapid policy-contemporaneous rise. Cross-community connectivity declined over 25 years, as reflected by a decrease in intercommunity edge fraction from 25% to 17% and an increase in modularity from 0.71 to 0.78; these trends were confirmed in uniform downsampling and multiseed analyses. Conclusion Among medical education publications with available reference data, the knowledge structure was organized into distinct intellectual communities that showed progressive specialization. These findings provide an empirical foundation for promoting integrative scholarship and informing curriculum design for medical education scholars.
Purpose After rejection, resubmission often requires journal-specific reformatting. We compared systematic review submission policies across high-impact ophthalmology journals and quantified policy similarity to support data-informed resubmission planning. Methods We conducted a cross-sectional policy analysis of the top 50 ophthalmology journals by 2024 SCImago Journal Rank that publish systematic reviews and are not invite-only. In January 2026, policies were extracted from public author instructions using an a priori data dictionary. Pairwise similarity was calculated on a scale from 0 to 1 using the Gower coefficient across mixed policy variables. Results Policies were heterogeneous and often unstated. Main-text word limits were stated by 29 of 50 journals (58%); among journals with numeric limits (n=23), the median was 4,000 words (interquartile range, 3,500–5,500). Compliance with the PRISMA guidelines was explicitly required by 35 journals (70%), and prospective registration was explicitly required by 6 journals (12%). Across 1,225 journal pairs, the median similarity was 0.64 (interquartile range, 0.57–0.71; range, 0.05–0.98). Similarity among the top five highest-ranking journals ranged from 0.62 to 0.90 (median, 0.75). Conclusion Systematic review submission policies vary widely across high-impact ophthalmology journals, and most journal pairs show only modest similarity. Similarity-based guidance may help authors identify policy-aligned resubmission targets and anticipate potential reformatting requirements.
Purpose This study aimed to define key research ethics and publication policy areas and assess policy disclosure among journals hosted on the Korea Institute of Science and Technology Information (KISTI) academic publishing platform. Methods We conducted a cross-sectional content analysis of journal policy documents. Fifteen policy areas were identified based on international guidelines, domestic reports, prior studies, and publisher policies related to artificial intelligence (AI) and data sharing. Policies from 181 journals were collected on July 10, 2025, and each journal was coded according to whether each policy area was disclosed. Descriptive statistics were used to summarize disclosure overall and according to subject field, access model, and indexing status. Results Journals disclosed a mean of 8.29 policy areas out of 15. Five journals disclosed none of the areas, whereas three disclosed all 15. The most frequently disclosed areas were copyright (158 of 181, 87.3%) and duplicate publication (157 of 181, 86.7%), followed by plagiarism, authorship, and sanctions for misconduct. Emerging governance policies were uncommon: only 5 journals disclosed an AI policy, and 29 disclosed a data sharing policy. When present, AI policies addressed non-authorship, disclosure requirements, scope limitations, accountability, and restrictions on reviewer use. Disclosure rates varied across disciplines, with medicine and pharmacy journals showing the highest rates overall. Open access journals generally disclosed more policy areas than subscription journals, whereas indexing status showed no consistent pattern. Conclusion Policy disclosure among journals hosted on the KISTI academic publishing platform remains incomplete and uneven, particularly with respect to AI and data sharing. To address these gaps, journals should adopt standardized policy templates and receive targeted platform-supported guidance to strengthen research ethics and publication governance in Korea.
Purpose This study used journals selected for the High Starting Point New Journal Project as the research sample to systematically compare changes in core development indicators before and after funding and to clarify Chinese authorities’ main journal-development priorities and requirements for newly founded journals. Methods Journal data were retrieved from the Journal Citation Reports (JCR), Web of Science (WoS), and World Journal Clout Index (WJCI) databases. Wilcoxon signed rank tests with Benjamini-Hochberg false discovery rate corrections were applied to 14 bibliometric indicators. Results After the funding period, the sample journals showed significant increases in article volume and the number of highly cited papers, indicating expanded publication scale and greater capacity to attract high-quality academic output. The Journal Impact Factor did not change significantly, whereas the average Journal Impact Factor percentile increased significantly; the Journal Citation Indicator showed a nominal increase that did not remain statistically significant after false discovery rate correction. The proportion of articles with non-Chinese authors decreased significantly. The number of author-origin countries or regions increased significantly, whereas the number of articles with non-Chinese authors did not change significantly. Conclusion Chinese authorities’ primary expectation for newly founded journals appears to be that they serve the national scientific innovation system by consolidating their domestic development foundation, increasing their relative disciplinary influence and local service capacity, and then pursuing gradual, high-quality internationalization through steady expansion of global reach after stronger local development has been established. These findings provide empirical evidence that global publishers can use to refine development strategies for the Chinese market and that government agencies and academic organizations can use when launching new journals and designing supporting funding policies.
Purpose As generative artificial intelligence (AI) capabilities continue to advance, academic journals are strengthening research ethics requirements. This study examined the status and core components of generative AI policies in nursing journals indexed in MEDLINE and PubMed Central (PMC) and identified journal characteristics associated with policy adoption. Methods A descriptive analysis was conducted of 154 nursing journals as of October 2025. Journal guidelines were systematically reviewed to assess AI-related policies and their alignment with the recommendations of the International Committee of Medical Journal Editors. Data were analyzed using descriptive statistics and multivariable binary logistic regression. Results Of the 154 journals, 108 (70.1%) had established AI-related policies. All journals with policies mandated disclosure of AI use and affirmed sole human responsibility for authorship. However, only 88.0% explicitly prohibited listing AI as an author, and only 15.7% specified sanctions for policy violations. Multivariable logistic regression showed that PMC indexing (odds ratio [OR], 10.419; P=0.008) and possession of a Journal Impact Factor (OR, 6.671; P=0.004) were significant predictors of policy adoption. Conclusion Although 70.1% of nursing journals have established AI policies, a gap remains between global ethical standards and their practical enforcement. While disclosure and accountability requirements are universally stated, specific sanctions and review procedures remain limited. To safeguard research integrity, journals should implement rigorous, field-specific policies and transparent disclosure systems.
Purpose This study aimed to help researchers improve the quality of their manuscripts and facilitate effective academic communication. Methods The general principles for responding to peer review comments were generated through a systematic review of textual evidence. A systematic literature search was conducted in the PubMed database to identify eligible studies. Two researchers independently performed literature screening, data extraction, and analysis. In addition, based on the identified general principles, we further developed specific strategies for responding to peer review comments by incorporating the authors’ practical experience in manuscript revision. Results Twenty-five articles were included in this review, and eight general principles were identified through thematic analysis. Peer review comments were categorized into three types: (1) agree and address; (2) agree but cannot fully address; and (3) disagree and cannot address. Specific response strategies were developed for each category. Conclusion This study systematically summarizes the general principles and specific strategies for responding to peer review comments and provides practical guidance for authors. These strategies may help authors respond more effectively to reviewer comments, promote constructive communication between authors and reviewers, and improve both manuscript quality and the efficiency of academic communication.
Purpose Open science is a phenomenon that promotes transparency and collaboration in knowledge generation. However, its adoption remains uneven, and the field is still undergoing consolidation. The objective of this bibliometric study was to map trends in scientific production related to open science and open access. Methods The PRISMA statement was applied, and predefined inclusion and exclusion criteria were used to guide study selection. A total of 1,826 documents published between 2015 and 2024 were retrieved from the Scopus database. Data processing and analysis were conducted using the Biblioshiny interface. Results Scientific output demonstrated an annual growth rate of 24.1%. Articles, conference papers, and reviews were identified as the preferred publication formats. Canada, Italy, and the United States emerged as leading countries in the promotion of collaborative research networks. The most frequently occurring keywords included open science, open access, open data, data sharing, reproducibility, and scholarly communication. A thematic evolution was observed, shifting from an initial educational focus toward increased emphasis on technological applications. Conclusion Over the past decade, scientific output related to open science and open access has increased steadily and has been disseminated through multidisciplinary sources. This trend reflects the ongoing transformation of scientific communication and highlights opportunities for publishers to implement policies that support open knowledge dissemination. Publications appearing in Q1 Scopus journals demonstrated strong reliability in knowledge dissemination.
Peer review is the cornerstone of scientific publishing, with its main objective being to enhance the quality and reliability of manuscripts. After an initial editorial review, meritorious manuscripts typically undergo external peer review, which assists editors in deciding whether to accept, reject, or request revisions. Authors must accurately interpret the type and extent of revisions requested-whether minor or major-and tailor their responses accordingly. A systematic approach is recommended, classifying comments as favorable, minor, or major, and addressing each with clarity, diligence, and appreciation. All responses should comply with the journal's instructions and formatting guidelines. They should be concise, clear, and gender-neutral. When major revisions are requested, authors should balance the feasibility of completing the revisions against the likelihood of acceptance. If specific comments cannot be implemented or addressed, authors must provide well-reasoned explanations for refuting the reviewer's requests. Special circumstances, such as unclear, rude, or ethically concerning comments, should be handled carefully, ideally with editorial guidance. Questions concerning data accuracy or study novelty must be addressed meticulously. A respectful, transparent, and well-organized response to reviewers ultimately increases the likelihood of manuscript acceptance.
Purpose: This study analyzed retraction patterns and regional nuances in the five African countries with the highest scientific output-South Africa, Egypt, Nigeria, Tunisia, and Morocco- to inform integrity policies. Methods: Retraction dynamics were examined using data from Scopus, SciVal, and the Retraction Watch Database. Results: Substantial variation was observed in retraction rates, with Egypt showing an exceptionally high rate, nearly eight times that of South Africa, and reaching a peak of 35 retractions per 10,000 publications in 2022. This increase was strongly associated with collaborations with Saudi Arabia, as 75% of Egypt's retractions involved co-authorship with Saudi researchers. Unreliable or fraudulent content remained the most common retraction reason across all countries, with paper mills and randomly generated content being major contributors. Although falsification and manipulation occurred, they were less frequent overall. Plagiarism was particularly prominent in research from Tunisia (29.6%) and Morocco (30.3%), while duplication was most common in research from Egypt (25.5%) and Morocco (24.2%). Fake peer review constituted a major problem in Tunisia (34.6%) and Egypt (31.1%). Authorship issues were most frequently observed in studies from Nigeria (19.0%) and Tunisia (21.0%), and ethical issues appeared to be relatively infrequent across the region. Retractions disproportionately affected Q1 and Q2 journals and spanned a wide range of disciplines, with medicine and engineering being the most impacted. Notably, retracted articles continue to accumulate citations after retraction, indicating persistent challenges in research integrity. Conclusion: The findings underscore the need for strengthened research oversight and expanded ethics training to address the concerning retraction trends observed, particularly in Egypt and in collaborative research with Saudi Arabia.
Purpose: Scientific research is intended to be a transparent and reproducible process. However, scientific misconduct distorts reality and presents fraudulent findings as truth. This bibliometric study aimed to map trends in scientific output and to identify the leading authors, journals, keywords, and documents addressing scientific misconduct between 2000 and 2024. Methods: Scientific production indexed in the Scopus database was analyzed. After applying inclusion and exclusion criteria, a total of 3,536 documents were selected. The data were processed using Biblioshiny and Microsoft Excel. Results: The annual growth rate of publications on scientific misconduct was estimated at 5.33%, with 2024 recording the highest number of indexed documents in Scopus. Collaboration networks were led by the United States, the United Kingdom, and China. The most frequently used keywords were research integrity and scientific misconduct. Retraction was identified as a key control mechanism adopted by journals to uphold research ethics. Conclusion: Over the past 4 years, scientific output on scientific misconduct has increased, with Q1 Scopus journals playing a central role in establishing international standards for detecting and eliminating research fraud.
Purpose This study aimed to analyze how government policies shape the governance of scientific journals in Indonesia through regulatory frameworks, quality assurance instruments, publication ethics, and digital systems that structure national journal management. Methods A thematic analysis was employed to examine policy documents, including laws and regulations, administrative policies, ethical codes, and operational guidelines governing scientific journals. Documents were systematically analyzed using a coding process to identify regulatory objectives, governance mechanisms, quality assurance instruments, publication ethics arrangements, and modes of policy implementation through digital systems. Results Scientific journals in Indonesia have been institutionalized as instruments of public governance rather than solely as platforms for academic communication. Journal governance is characterized by standardized accreditation, performance-based evaluation, integrated quality assurance, and administratively enforced publication ethics. Digital systems play a central role in translating regulatory standards into routine, data-driven practices, thereby enabling continuous monitoring, verification, and auditability. Conclusion Government policies have strengthened accountability, transparency, and systemic integration in Indonesian scientific publishing. At the same time, the consolidation of standards-based governance and digital oversight presents challenges in maintaining an appropriate balance between administrative compliance and the substantive epistemic quality of scientific publications.
Purpose Reliable bibliometric analysis requires the accurate linkage of heterogeneous affiliation strings to persistent organizational identifiers. Generic natural language processing tools frequently fail at this task because they tend to prioritize coverage rather than precision. This study evaluated whether anchoring an entity-linking model to the Research Organization Registry improved precision relative to generic tools. Methods We developed a conservative, two-stage model. First, using a normalized registry corpus, we applied rule-based exact matching with geographic validation. Second, selective fuzzy matching was applied only to the remaining nonmatched affiliations. We evaluated model performance against an off-the-shelf spaCy named entity recognition baseline using a manually adjudicated gold standard dataset derived from PubMed Digital Health records. Finally, we assessed the comparative advantage of our model using nonparametric paired comparison tests and bootstrap methods. Results Our two-stage approach achieved substantially higher precision (0.97) and recall (0.93) than both the generic baseline (precision, 0.75; recall, 0.47) and unconstrained fuzzy matching models (precision, 0.77; recall, 0.83). This balanced improvement in precision and recall resulted in the highest F1 score (0.95). The ablation study further confirmed that the “exact matching first” strategy was structurally necessary to prevent the inflation of false positives observed when unconstrained fuzzy matching was applied. Conclusion Anchoring entity resolution to a canonical registry using a tiered matching strategy substantially enhances the precision of institutional attribution. This approach provides a robust method for correcting metadata quality in editorial and repository workflows.
