Related papers: Journal Impact Factor and Peer Review Thoroughness…
Time spent by academics on research quality assessment might be reduced if automated approaches can help. Whilst citation-based indicators have been extensively developed and evaluated for this, they have substantial limitations and Large…
The purpose of this study is to analyze the research article publishing with special reference to preparing to publish and peer reviewing. Peer reviewing is the process required for standardizing any publications. Manuscript writing is an…
We analysed 580 articles (original articles only) published in Medical Journal of Malaysia between 2004 and 2008, the resources referenced by the articles and the citations and impact received. Our aim was to examine article and author…
Peer review is a critical process for ensuring the integrity of published scientific research. Confidence in this process is predicated on the assumption that experts in the relevant domain give careful consideration to the merits of…
With the spread of false and misleading information in current news, many algorithmic tools have been introduced with the aim of assessing bias and reliability in written content. However, there has been little work exploring how effective…
Text generated by artificial intelligence (AI) chatbots is increasingly used in English as a foreign language (EFL) writing contexts, yet its impact on students' expository writing process and compositions remains understudied. This…
Some research now suggests that ChatGPT can estimate the quality of journal articles from their titles and abstracts. This has created the possibility to use ChatGPT quality scores, perhaps alongside citation-based formulae, to support peer…
We support scientific writers in determining whether a written sentence is scientific, to which section it belongs, and suggest paraphrasings to improve the sentence. Firstly, we propose a regression model trained on a corpus of scientific…
Context: Pre-publication peer review of scientific articles is considered a key element of the research process in software engineering, yet it is often perceived as not to work fully well. Objective: We aim at understanding the perceptions…
This study is a preliminary exploration of the concept of informativeness -how much information a sentence gives about a word it contains- and its potential benefits to building quality word representations from scarce data. We propose…
This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject…
With the rise of Wikipedia as a first-stop source for scientific knowledge, it is important to compare its representation of that knowledge to that of the academic literature. Here we identify the 250 most heavily used journals in each of…
While previous studies have demonstrated that Large Language Models (LLMs) can predict peer review outcomes to some extent, this paper builds on that by introducing two new contexts and employing a more robust method - averaging multiple…
National research evaluation initiatives and incentive schemes have previously chosen between simplistic quantitative indicators and time-consuming peer review, sometimes supported by bibliometrics. Here we assess whether artificial…
Purpose The purpose of this paper is to explore which structures of academic articles referees would pay more attention to, what specific content referees focus on, and whether the distribution of PRC is related to the citations.…
In computer science, students could benefit from more opportunities to learn important, high-level concepts and to improve their learning skills. Peer review is one method to encourage this by providing students with the opportunity to…
The rapid advancement of large language models (LLMs) has inspired researchers to integrate them extensively into the academic workflow, potentially reshaping how research is practiced and reviewed. While previous studies highlight the…
This study examines the potential of large language models (LLMs) to augment the academic peer review process by reliably evaluating the quality of economics research without introducing systematic bias. We conduct one of the first…
Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, existing applications are primarily limited to static review…
Peer review remains the central quality-control mechanism of science, yet its ability to fulfill this role is increasingly strained. Empirical studies document serious shortcomings: long publication delays, escalating reviewer burden…