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Optimizing peer review: the JNIS approach
  1. Michael Chen1,
  2. Joshua A Hirsch2,
  3. Reade De Leacy3,
  4. Felipe C Albuquerque4
  1. 1 Department of Neurological Surgery, Rush University Medical Center, Chicago, IL, USA
  2. 2 Department of NeuroEndovascular Program, Massachusetts General Hospital, Boston, Massachusetts, USA
  3. 3 Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, New York, USA
  4. 4 Division of Neurological Surgery, Barrow Neurological Institute, Phoenix, Arizona, USA
  1. Correspondence to Dr Michael Chen, Department of Neurological Surgery Rush University Medical Center1725 West Harrison Street Suite 855 Chicago, IL 60612; michael_chen{at}rush.edu

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Overview

As JNIS approaches its 10  year anniversary, there has been consistent yearly growth in the number of manuscript submissions both nationally and internationally. As such, there is a corresponding need to grow and develop the peer review process. As stated by Proto: “The quality of a scientific journal is, in a major way, a reflection of the quality and dedication of its reviewers”.1 The purpose of this editorial commentary is to reinforce critical concepts that define the peer review process, particularly for younger physician scientists in our field. A sustainable, constructive, and robust peer review process affirms the integrity and rigor that our authors deserve. A literature exists that defines components of an outstanding review of scholarly articles.2–5 The present commentary highlights process elements that are unique to JNIS.

How reviewers are chosen

The ScholarOne manuscripts system is the peer review tool used by JNIS and serves as one resource for reviewer selection. Initially, the Editor in Chief (EIC) receives all manuscripts and assigns submissions to individual Associate Editors (AEs). The AE is tasked with selecting and inviting reviewers to a particular manuscript. Thomson Reuters Reviewer Locater works by comparing new manuscript submissions against Web of ScienceTM Core Collection content to generate a list of experts as potential reviewers. This helps widen the reviewer pool beyond those contacts already known to the AE. This program displays reviewers with a known publication record in Web of Science. The Reviewer Locator uses a proprietary platform called ATLAS to parse and extract research metadata such as author names, title, abstract, keywords, and journal of publication from the Web of Science Core Collection. The actual database covers 12 000 high impact journals with 7.3 million potential reviewers with email addresses, institutional affiliations and ORCID ID records. Reviewer requests are automatically generated on each manuscript submission and …

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