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Background: Reviewers rarely comment on the same aspects of a manuscript, making it difficult to properly assess manuscripts’ quality and the quality of the peer review process. The goal of this pilot study was to evaluate structured peer review implementation by: 1) exploring whether and how reviewers answered structured peer review questions, 2) analysing reviewer agreement, 3) comparing that agreement to agreement before implementation of structured peer review, and 4) further enhancing the piloted set of structured peer review questions. Methods: Structured peer review consisting of nine questions was piloted in August 2022 in 220 Elsevier journals. We randomly selected 10% of these journals across all fields and IF quartiles and included manuscripts that received two review reports in the first 2 months of the pilot, leaving us with 107 manuscripts belonging to 23 journals. Eight questions had open-ended fields, while the ninth question (on language editing) had only a yes/no option. The reviews could also leave Comments-to-Author and Comments-to-Editor. Answers were independently analysed by two raters, using qualitative methods. Results: Almost all the reviewers (n = 196, 92%) provided answers to all questions even though these questions were not mandatory in the system. The longest answer (Md 27 words, IQR 11 to 68) was for reporting methods with sufficient details for replicability or reproducibility. The reviewers had the highest (partial) agreement (of 72%) for assessing the flow and structure of the manuscript, and the lowest (of 53%) for assessing whether interpretation of the results was supported by data, and for assessing whether the statistical analyses were appropriate and reported in sufficient detail (52%). Two thirds of the reviewers (n = 145, 68%) filled out the Comments-to-Author section, of which 105 (49%) resembled traditional peer review reports. These reports contained a Md of 4 (IQR 3 to 5) topics covered by the structured questions. Absolute agreement regarding final recommendations (exact match of recommendation choice) was 41%, which was higher than what those journals had in the period from 2019 to 2021 (31% agreement, P = 0.0275). Conclusions: Our preliminary results indicate that reviewers successfully adapted to the new review format, and that they covered more topics than in their traditional reports. Individual question analysis indicated the greatest disagreement regarding the interpretation of the results and the conducting and the reporting of statistical analyses. While structured peer review did lead to improvement in reviewer final recommendation agreements, this was not a randomized trial, and further studies should be performed to corroborate this. Further research is also needed to determine whether structured peer review leads to greater knowledge transfer or better improvement of manuscripts.

 

 

Objectives: Development of search queries for systematic reviews (SRs) is time-consuming. In this work, we capitalize on recent advances in large language models (LLMs) and a relatively large dataset of natural language descriptions of reviews and corresponding Boolean searches to generate Boolean search queries from SR titles and key questions. Materials and Methods: We curated a training dataset of 10 346 SR search queries registered in PROSPERO. We used this dataset to fine-tune a set of models to generate search queries based on Mistral-Instruct-7b. We evaluated the models quantitatively using an evaluation dataset of 57 SRs and qualitatively through semi-structured interviews with 8 experienced medical librarians. Results: The model-generated search queries had median sensitivity of 85% (interquartile range [IQR] 40%-100%) and number needed to read of 1206 citations (IQR 205-5810). The interviews suggested that the models lack both the necessary sensitivity and precision to be used without scrutiny but could be useful for topic scoping or as initial queries to be refined. Discussion: Future research should focus on improving the dataset with more high-quality search queries, assessing whether fine-tuning the model on other fields, such as the population and intervention, improves performance, and exploring the addition of interactivity to the interface. Conclusions: The datasets developed for this project can be used to train and evaluate LLMs that map review descriptions to Boolean search queries. The models cannot replace thoughtful search query design but may be useful in providing suggestions for key words and the framework for the query.

 

 

Psychosociology theories indicate that individual evaluation is integral to the recognition of professional activities. Building upon Christophe Dejours’ contributions, this recognition is influenced by two complementary judgments: the “utility” judgment from those in hierarchy and the “beauty” judgment from the peers. The aim of this paper is to elucidate how at INRAE individual assessment of scientists is conducted. This process follows a qualitative and multicriteria-based approach by peers, providing both appreciations and advice to the evaluated scientists (the “beauty” judgment). Furthermore, we expound on how INRAE regularly adapts this process to the evolving landscape of research practices, such as interdisciplinary collaboration or open science, assuring that assessments align with the current approaches of research activities.

 

 

Bibliometric analysis has recently become a popular and rigorous technique used for exploring and analyzing the literature in business and management. Prior studies principally focused on ‘how to do bibliometric analysis’, presenting an overview of the bibliometric methodology along with various techniques and step-by-step guidelines that can be relied on to rigorously conduct bibliometric analysis. However, the current body of evidence is limited in its ability to provide practical knowledge that can enhance the design and performance of bibliometric research. This claim is supported even by the fact that relevant studies refer to their work as ‘bibliometric analysis’ rather than ‘bibliometric research’. Accordingly, we endeavor to offer a more functional framework for researchers who wish to design/conduct bibliometric research on any field of research, especially business and management. To do this, we followed a twofold way. We first outlined the main stages and steps of typical bibliometric research. Then, we proposed a comprehensive framework for specifying how to design/conduct the research and under what headings the relevant stages (step-by-step) will be used and/or presented. Thus, the current paper is expected to be a useful source to gain insights into the available techniques and guide researchers in designing/conducting bibliometric research.

 

 

The past 20 years has seen a significant increase in articles with 500 or more authors. This increase has presented problems in terms of determining true authorship versus other types of contribution, issues with database metadata and data output, and publication length. Using items with 500+ authors deemed as mega-author titles, a total of 5,533 mega-author items were identified using InCites. Metadata about the items was then gathered from Web of Science and Scopus. Close examination of these items found that the vast majority of these covered physics topics, with medicine a far distant second place and only minor representation from other science fields. This mega-authorship saw significant events that appear to correspond to similar events in the Large Hadron Collider’s timeline, indicating that the projects for the collider are driving this heavy output. Some solutions are offered for the problems resulting from this phenomenon, partially driven by recommendations from the International Committee of Medical Journal Editors.

 

 

Biodiversity conservation and ecosystem management are imperative for sustaining life on Earth. Despite the growing recognition of its importance outside the field of environmental sciences, biodiversity has been polemically criticized as a fad, arguing that it has become a passing trend in sustainable finance. To foster a comprehensive understanding, we provide a bibliometric analysis of 334 articles in accounting, economics, and finance (AEF) journals retrieved from the Web of Science database. We conduct science mapping and a co-citation analysis to portrait the scientific landscape and research foci. Consistent with previous studies, we find that mainstream AEF journals are largely silent on biodiversity. In addition, research from Asia is severely underrepresented.

 

 

Literature reviews summarize existing literature, uncover research gaps, and offer future research directions, thus aiding in theoretical and methodological development. Informetric research including bibliometric, scientometric, webometric, cybermetric, patentometric, and altmetric methods are becoming increasingly prevalent in conducting literature review studies. Looking at the common informetric literature review methods—citation, co-citation, co-author, bibliographic coupling, and content co-occurrence analyses, this study aims to serve as a guide in using content co-occurrence also known as co-word analysis to conduct literature reviews. This study outlines a variety of informetric research methods and how they are utilized to conduct review and evidence-based conceptual studies. In addition to the analyses, the study highlights different informetric software packages like Bibliometrix, Biblioshiny, Leximancer, NVivo, and CiteSpace including their comparison. The study further discusses contributions of algorithm-based content analyses including offering taxonomies, definitions, classifications, typologies, comparisons, and theoretical development to constitute integrative literature reviews. Finally, this study offers step-by-step guidelines for conducting a review study using VOSviewer content co-occurrence analysis while providing a systems view of informetric research in social science. The study also notes the emergence of generative artificial intelligence (AI) like Open AI’s ChatGPT, Google’s Bard, Elicit, Scite, Research Rabbit, and ChatPDF among others, and its potential in contributing to the literature review methods and, as such, being an interesting direction for future research.

 

 

Background: The reporting and data system (RADS) has been researched across the world since it was first developed. This study used bibliometrics to analyze the research trends and current status of this field over the past almost 23 years and explored possible future research hotspots. Methods: We searched the Web of Science (WOS) literature on RADSs from January 1, 2000, to November 1, 2022, and evaluated the findings visually with VOSviewer (1.6.18), CiteSpace (6.1.3), and the “bibliometrix” package in R version 4.2.1. Results: We included 6,239 publications from 88 countries and regions. The number of published has shown an overall growth trend, especially since 2016. The United States was the country with the highest number of publications and citations. The top 10 most productive institutions in RADS research were mainly from South Korea and the United States. Kim EK was the most published author, and Turkbey B had the most cited publication. European Radiology had the most publications on the subject, while Radiology was the most influential journal. Magnetic resonance imaging, carcinoma, ultrasound, RADS, mammography, breast neoplasms, and diagnosis were the most common keywords. Artificial intelligence (AI) appears to be an emerging hotspot in the research of RADS. Conclusions: This study provides an overview of the development status of research into RADSs over the past 23 years. Research into RADSs has included various systems of the body, with the most studied being the breast, prostate, liver, and thyroid. In terms of auxiliary diagnosis, there is an increasing amount of research into the application of AI in RADSs, which along with the interpretability of AI, will be a hotspot of research in the following years.

 

 

The academic landscape has witnessed significant transformations in recent years, primarily attributed to advancements in IT tools, which have advantages and drawbacks in the world of publications. The transition from traditional university library searches to the digital era, with access to various information sources such as Pubmed, Scopus, Web of Science and Google Scholar, has revolutionized research practices. Thanks to technology, researchers, academics and students now enjoy rapid and vast information access, facilitating quicker manuscript preparation and boosting bibliometric parameters. To identify authors “self-distorted” bibliometric parameters, different indices following the Hirsch index (h-index) (based on citations) have been proposed. The new “fi-score” evaluates the reliability of citation counts for individual authors and validates the accuracy of their h-index, comparing the number of citations to the h-index value to highlight value that is not within the norm and probably influenced or distorted by authors themselves. It examines how authors’ citations impact their h-index, although they are not self-citing. The study calculated the fi-score on a sample of 194,983 researchers. It shows that the average value of the fi-score is 25.03 and that a maximum value admissible as good must not exceed 32. The fi-score complements existing indexes, shedding light on the actual scientific impact of researchers. In conclusion, bibliometric parameters have evolved significantly, offering valuable insights into researchers’ contributions. The fi-score emerges as a promising new metric, providing a more comprehensive and unbiased evaluation of scholarly impact. By accounting for the influence of citations and self-citations, the fi-score addresses the limitations of traditional indices, empowering academic communities to recognize better and acknowledge individual contributions.

 

 

There seems to be increasing interest in publication practices amongst philosophers of science, as they recognize the important role that publication plays in their professional lives and the responsibilities they have for maintaining some control over the process and practices.The increase in interest is manifested in two ways.First, philosophers of science are talking about publication practices more-practices such as open access, transformative journals, and predatory publishing-and they are talking about how these practices impact on our community, authors and readers.Recently, for example, David Teira, Chiara Lisciandra, and Sophia Cruwell organized an online conference on open access and transformative journals.The session included a roundtable discussion involving four editors of journals who serve the history and philosophy of science community, broadly conceived.The discussion made it clear that there are at least two ways of approaching this issue.On the one hand, the publishers have their plans about where journal publishing is going.And open access fits into their vision in a certain way.On the other hand, the various editors have their own ideas about the role of open access in the future of our profession.To be clear, the various editors involved were not all of one mind, nor did they share the same concerns and hopes.But concerns were expressed that the interests of the publishers may not always align with the interests of the community of researchers whose work is being published in these journals.A recent development that was not discussed at the conference, but one deserving the attention of philosophers of science, is the marked rise in predatory publishers.I will not name names, but each week I receive numerous invitations to publish in journals that promise very quick review times, and equally quick production times.So, if I were a scholar in need of a quick publication, say, in one month from now, the opportunities appear to be almost endless.How do I know these are predatory journals?The invitation letters often begin with something like “Dear Esteemed Scholar”, or they express an urgency that is quite foreign to the slow pace of the publication norms in philosophy.