====== Reviewer ======

A **reviewer** is a person who evaluates and provides [[feedback]] on a work, such as a [[scientific article]], [[book]], [[research paper]], or [[product]]. In the context of [[academic publishing]], a reviewer plays a critical [[role]] in the **[[peer review process]]**, where experts in a specific field assess the [[quality]], [[validity]], and significance of a [[research paper]] before it is published in a [[journal]].

===== Types of Reviewers =====

1. **Academic/Scientific Reviewer** – Evaluates research papers for journals, conferences, or grant proposals.

2. **[[Peer Reviewer]]** – A subject-matter expert who provides anonymous or open reviews of scientific articles.

3. **Editorial Reviewer** – Works for journals or publishers to assess the quality of submitted manuscripts.

4. **Book/Media Reviewer** – Reviews books, films, or products for magazines, blogs, or websites.

===== Responsibilities of a Scientific Reviewer =====

- Assess the **[[clarity]], [[accuracy]], and [[originality]]** of the [[research]].

- Evaluate the **[[methodology]] and [[validity]]** of the results.

- Provide **constructive [[feedback]]** to help improve the [[manuscript]].

- Identify **[[flaw]]s, [[bias]]es, or ethical concerns**.

- Recommend whether the [[paper]] should be **accepted, revised, or rejected**.


see [[Peer reviewer]].

A study aims to analyze the accuracy of human [[reviewer]]s in identifying scientific abstracts generated by [[ChatGPT]] compared to the original abstracts. [[Participant]]s completed an [[online survey]] presenting two research abstracts: one generated by ChatGPT and one original abstract. They had to identify which abstract was generated by AI and provide [[feedback]] on their preference and perceptions of AI technology in academic [[writing]]. This observational cross-sectional study involved surgical [[trainee]]s and [[faculty]] at the University of British Columbia. The survey was distributed to all surgeons and trainees affiliated with the University of British Columbia, which includes general surgery, orthopedic surgery, thoracic surgery, plastic surgery, cardiovascular surgery, vascular surgery, neurosurgery, urology, otolaryngology, pediatric surgery, and obstetrics and gynecology. A total of 41 participants completed the [[survey]]. 41 participants responded, comprising 10 (23.3%) surgeons. Eighteen (40.0%) participants correctly identified the original abstract. Twenty-six (63.4%) participants preferred the ChatGPT abstract (p = 0.0001). On multivariate analysis, preferring the original abstract was associated with correct identification of the original abstract [OR 7.46, 95% CI (1.78, 31.4), p = 0.006]. Results suggest that human reviewers cannot accurately distinguish between human and AI-generated abstracts, and overall, there was a trend toward a preference for AI-generated abstracts. The findings contributed to understanding the implications of AI in manuscript production, including its benefits and ethical considerations
((Nabata KJ, AlShehri Y, Mashat A, Wiseman SM. Evaluating human ability to distinguish between ChatGPT-generated and original scientific abstracts. Updates Surg. 2025 Jan 24. doi: 10.1007/s13304-025-02106-3. Epub ahead of print. PMID: 39853655.))