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Historians of science attribute the concept of peer review—not the process itself—as a method for evaluating written works to ancient Greece (5th century BC) or Middle Eastern scholars (around 900 AD) (Al-Mousawi, 2020). Despite this, the principle of peer review has a long history, dating back to the publication of Philosophical Transactions by the Royal Society of London in 1665 (Moxham & Fyfe, 2018). Concurrently, some texts reference the Journal de scavant, published in Paris on January 5, 1665, as the first peer-reviewed scientific publication. However, according to the Merriam-Webster dictionary (n.d.), the term peer-review was introduced in 1969, and according to the Oxford English Dictionary (n.d.), the term entered the scientific lexicon in 1971. Additionally, the term referee was introduced in 1817 by George Greenough, a geologist who became familiar with this term early in his life as a law student (Al-Mousawi, 2020).
Exploring the evolution of peer review provides clear evidence of the direct relationship between peer review and the growth and development of scientific journals. Journals have consistently relied on peer reviewers to ensure they make informed decisions regarding the publication and accreditation of submitted articles. Despite this, the peer review process has continually evolved in response to the trends shaping technological advancements. With the development of peer review models that align with contemporary technologies and requirements, fresh opportunities have arisen for the stakeholders involved in the peer review process. In this context, although the Blind Peer Review model was once regarded as the most prevalent peer review method, other models have gradually gained acceptance among various journals. These include Single-blind peer review, Double-blind peer review, Signed peer review/Transparent peer review, and Open peer review which were welcomed by a variety of journals and developed over time. However, the development of peer review does not stop there. Influenced by advancements related to the open access movement and the phenomenon of open science, one of its latest innovations has emerged known as the Post-publication open peer review model. The Post-publication open peer review is a type of open review system in which articles and research works undergo the peer review process after being made publicly available as preprints. This model does not include an editor. To eliminate potential biases, peer reviewers are solely responsible for collectively determining the validity and suitability of articles for publication, effectively assuming the role of an editor.
Among the platforms that utilize post-publication open peer review and have introduced innovative approaches to scientific publishing and peer review, we can mention Qeios[1], Orvium[2], eLife[3], ScienceOpen[4], Octopus[5], and F1000Research[6]. In addition to benefiting from a rigorous peer review process, these platforms offer the opportunity for the free and rapid publication of high-quality articles and research. They also make the content accessible to the public through open access. Using the capabilities of artificial intelligence, along with the voluntary participation of other researchers as peer reviewers, these platforms integrate human expertise and AI to identify the most effective methods of peer review. In this model, artificial intelligence ensures the accuracy and reliability of peer review at every stage. Particularly during the initial review phase, before the work enters the peer review process, it plays a crucial role in filtering out non-scientific content and detecting scientific plagiarism. In addition, artificial intelligence facilitates the unbiased selection and identification of peer reviewers by analyzing their records and profiles. It also streamlines the process of sending review invitations and enables the verification of identities and review reports submitted by volunteer peer reviewers. This technology ensures transparency in the actions taken. Additionally, artificial intelligence enables more thorough evaluations before peer reviewers announce final approval. While AI offers the potential for a more favorable assessment of the work's language, it also clarifies the extent to which the principles and ethical standards of evaluation are upheld, including the WMA Declaration of Helsinki for human medical research and the ARRIVE guidelines for animal research (Qeios, 2024b).
The key features of the post-publication open peer review model are as follows:
-   The identities of authors and peer reviewers are evident not only to one another but also to the general readership.
-   All articles are screened for plagiarism, non-scientific content, and offensive material using artificial intelligence before being published as preprints.
-   The judging process is not restricted to two or three peer reviewers; it is possible to evaluate the work of dozens of peers within the same specialized field.
-   The gatekeeping role of the editor has been eliminated, increasing the speed of research publication.
-   Peer reviewers are positioned more constructively, acting as allies to authors rather than gatekeepers.
-   The visibility of identities allows peer reviewers to feel acknowledged for the significant contributions they make.
-   Peer reviewers can concentrate on assisting authors in enhancing their papers instead of aiding editors in making editorial decisions.
-   It facilitates a more honest evaluation of the work, prevents reviewers from pursuing their personal agendas, helps identify conflicts of interest, and enhances transparency in the manuscript evaluation process.
-   This significantly enhances the speed and accuracy of distinguishing between good and incomplete research.
-   It allows others to comment on the opinions of peer judges, and peers can cast positive or negative votes on the recorded opinions.
-   The knowledge that all users are publicly accountable for their actions serves as a deterrent to potential misconduct.
Considering the advantages and appeal of the post-publication open peer review model, the number of enthusiasts, platforms, and journals utilizing this approach to evaluate submitted articles and works will undoubtedly continue to grow each day. In this context, it is important to address the challenges faced by scientific journals, particularly the concerns of editors regarding the selection of appropriate referees for the accurate evaluation of articles by peer reviewers. The characteristics of the post-publication open peer review model warrant significant attention. Despite this, before entering this field, journals should ensure they have made the necessary preparations and carefully consider the issues that arise within it. The most important questions to address in this context, which should be examined through applied research to provide clear answers, are as follows: To what extent do the specialized and cultural conditions of the scientific community related to each scientific field, as well as the existing technical and human facilities and infrastructures, allow the implementation of the post-publication open peer review model to Iran's journal reviewing system? To what extent do specialized journals in Iran prefer to leave the assessment of issues, such as compliance with ethical standards and research guidelines in articles, to the post-publication open peer review model? Considering the unique characteristics of the Persian language, how can we assess aspects such as originality, innovation, quality, usefulness, effectiveness, and impact of research in articles utilizing the post-publication open peer review model, and with what level of confidence can these evaluations be made? What opportunities and challenges does the application of this model present for the beneficiaries of scientific arbitration in Iran? Do specialized journals in the fields of knowledge and information science possess the necessary resources to implement this peer-review model? If they choose to adopt it, what obstacles might they encounter? Furthermore, to what extent can reliance on this reviewing model benefit Iran's specialized journals and create opportunities for enhancing their quality? Undoubtedly, accurate answers to such questions from researchers in the field of Scientometrics can enhance decision-making at both micro and macro levels concerning the application of this peer-review model for editors, policymakers, and research and technology planners.
 
[1] . https://www.qeios.com
[2] . https://dapp.orvium.io
[3] . https://elifesciences.org
[4] . https://www.scienceopen.com
[5] . https://www.octopus.ac
[6] . https://f1000research.com