In December 2019, an outbreak of pneumonia, which was named COVID-2019, emerged as a global health crisis. Scientists worldwide are engaged in attempts to elucidate the transmission and pathogenic mechanisms of the causative coronavirus. COVID-19 was declared a pandemic by the World Health Organization in March 2020, making it critical to track and review the state of research on COVID-19 to provide guidance for further investigations. Here, bibliometric and knowledge mapping analyses of studies on COVID-19 were performed, including more than 1,500 papers on COVID-19 available in the PubMed and China National Knowledge Infrastructure databases from January 1, 2020 to March 8, 2020. In this review, we found that because of the rapid response of researchers worldwide, the number of COVID-19-related publications showed a high growth trend in the first 10 days of February; among these, the largest number of studies originated in China, the country most affected by pandemic in its early stages. Our findings revealed that the epidemic situation and data accessibility of different research teams have caused obvious difference in emphases of the publications. Besides, there was an unprecedented level of close cooperation and information sharing within the global scientific community relative to previous coronavirus research. We combed and drew the knowledge map of the SARS-CoV-2 literature, explored early status of research on etiology, pathology, epidemiology, treatment, prevention, and control, and discussed knowledge gaps that remain to be urgently addressed. Future perspectives on treatment, prevention, and control are also presented to provide fundamental references for current and future coronavirus research.
Purpose: This paper proposes an expert assignment method for scientific project review that considers both accuracy and impartiality. As impartial and accurate peer review is extremely important to ensure the quality and feasibility of scientific projects, enhanced methods for managing the process are needed.Design/methodology/approach: To ensure both accuracy and impartiality, we design four criteria, the reviewers' fitness degree, research intensity, academic association, and potential conflict of interest, to express the characteristics of an appropriate peer review expert. We first formalize the expert assignment problem as an optimization problem based on the designed criteria, and then propose a randomized algorithm to solve the expert assignment problem of identifying reviewer adequacy.
Findings:Simulation results show that the proposed method is quite accurate and impartial during expert assignment.
Research limitations:Although the criteria used in this paper can properly show the characteristics of a good and appropriate peer review expert, more criteria/conditions can be included in the proposed scheme to further enhance accuracy and impartiality of the expert assignment.
Practical implications:The proposed method can help project funding agencies (e.g. the National Natural Science Foundation of China) find better experts for project peer review.
Originality/value:To the authors' knowledge, this is the first publication that proposes an algorithm that applies an impartial approach to the project review expert assignment process. The simulation results show the effectiveness of the proposed method.
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