scholarly journals Publication rate and citation counts for preprints released during the COVID-19 pandemic: the good, the bad and the ugly

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10927
Author(s):  
Diego Añazco ◽  
Bryan Nicolalde ◽  
Isabel Espinosa ◽  
Jose Camacho ◽  
Mariam Mushtaq ◽  
...  
Keyword(s):  
Citation Count ◽  
Publication Rate ◽  
Scientific Production ◽  
Scholarly Journal ◽  
Time Interval ◽  
Scholarly Journals ◽  
Scientific Impact ◽  
Peer Reviewing ◽  
Citation Counts ◽  
Novel Coronavirus

Background Preprints are preliminary reports that have not been peer-reviewed. In December 2019, a novel coronavirus appeared in China, and since then, scientific production, including preprints, has drastically increased. In this study, we intend to evaluate how often preprints about COVID-19 were published in scholarly journals and cited. Methods We searched the iSearch COVID-19 portfolio to identify all preprints related to COVID-19 posted on bioRxiv, medRxiv, and Research Square from January 1, 2020, to May 31, 2020. We used a custom-designed program to obtain metadata using the Crossref public API. After that, we determined the publication rate and made comparisons based on citation counts using non-parametric methods. Also, we compared the publication rate, citation counts, and time interval from posting on a preprint server to publication in a scholarly journal among the three different preprint servers. Results Our sample included 5,061 preprints, out of which 288 were published in scholarly journals and 4,773 remained unpublished (publication rate of 5.7%). We found that articles published in scholarly journals had a significantly higher total citation count than unpublished preprints within our sample (p < 0.001), and that preprints that were eventually published had a higher citation count as preprints when compared to unpublished preprints (p < 0.001). As well, we found that published preprints had a significantly higher citation count after publication in a scholarly journal compared to as a preprint (p < 0.001). Our results also show that medRxiv had the highest publication rate, while bioRxiv had the highest citation count and shortest time interval from posting on a preprint server to publication in a scholarly journal. Conclusions We found a remarkably low publication rate for preprints within our sample, despite accelerated time to publication by multiple scholarly journals. These findings could be partially attributed to the unprecedented surge in scientific production observed during the COVID-19 pandemic, which might saturate reviewing and editing processes in scholarly journals. However, our findings show that preprints had a significantly lower scientific impact, which might suggest that some preprints have lower quality and will not be able to endure peer-reviewing processes to be published in a peer-reviewed journal.

scholarly journals Citations and publication rate of preprints on pharmacological interventions for COVID-19: The good, the bad and, the ugly.

2020 ◽  
Author(s):  
Bryan Nicolalde ◽  
Diego Añazco ◽  
Mariam Mushtaq ◽  
Isabel Espinosa ◽  
Jimena Gimenez ◽  
...  
Keyword(s):  
Case Series ◽  
Science Research ◽  
Publication Rate ◽  
Pharmacological Interventions ◽  
Result Section ◽  
Scholarly Journals ◽  
Novel Coronavirus ◽  
Reported Data ◽  
Study Type ◽  
Number Of Citations

Abstract Background: Preprints are preliminary reports that have not been peer-reviewed. On December 2019, a novel coronavirus appeared in China, and since then, scientific production, including preprints, has drastically increased. In this study, we intend to evaluate how often preprints regarding pharmacological interventions against COVID-19 were cited, in spite of the fact that some of these preprints remained unpublished.Methods: We conducted a search on medRxiv and bioRxiv to identify preprints related to pharmacological interventions against SARS-CoV-2 from January 1, 2020 to March 31, 2020. We included any study type that addressed or reported data on pharmacological interventions. We gathered metadata on June 26, 2020 of included preprints and identified if they had been published in a scholarly journal. We performed Mann-Whitney U tests to evaluate if published articles had differences in citation counts or metrics, as defined by PDF downloads and abstract reads, when compared to unpublished preprints.Results: Our sample included 97 preprints, of which 23 were published on scholarly journals and 74 remained unpublished (Publication rate of 23,7%). The most common study designs we found among preprints were basic science research and case series. The number of citations in our sample ranged from 0 to 1409 for published articles, and ranged from 0 to 175 citations for unpublished preprints. Published articles had a significantly higher number of citations when compared to unpublished preprints (p=0,000013). We did not find a statistical difference in PDF download (p=0,167) and abstract reads (p= 0,181). In the published articles, the time from posting on a preprint server to publication on a journal ranged from 0 to 98 days (median: 42.0 days). The time period from date of submission to a journal to date of acceptance in our sample ranged from 1 to 228 days (median: 23 days). Almost half of the preprints that were subsequently published (47,8%) had modifications made to the result section after peer-review.Conclusions: The publication rate of the preprints in this sample was low (1 in 4), although review times in scholarly journals seems to be accelerated. However, there was no difference in the number of views or downloads between preprints already published in scholarly journals and those not yet.

scholarly journals Citation Counts as a Measure for Scientific Impact

2019 ◽  
Author(s):  
Jari Burgers
Keyword(s):  
Rank Order ◽  
Citation Count ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Scientific Impact ◽  
Total Citation ◽  
Citation Counts ◽  
The Difference ◽  
Lower Correlation ◽  
Ranked List

This thesis presents a look into citation counts as a measure for scientific impact which in turn is used to determine the replication value (RV). first, by comparing citation sources (WoS, Crossref, Scopus and Scite) from which citation counts can be retrieved. Secondly, by removing contradicting citations from the citation count, and comparing this new citation count without contradicting citations with the original total citation count. In both cases, based on the citation count, rank order lists are formed which are compared with the use of two tests. First, Kendall’s tau is calculated to see how well the compared pairs of lists correlate. Second, the rank biased overlap (RBO) is calculated to see how well pairs of lists overlap. The RBO is different than Kendall’s tau because it is able to give more weight to citation counts at the top of the list emphasizing the importance of high ranked articles as opposed to low ranked articles. Both measures indicate a significant correlation and overlap between ranked lists originating from Scopus and Crossref and WoS, and a lower correlation and overlap between Scite and all other sources. Based on the difference between Scite and all other sources, Scite is not yet the best choice as a citation source for determining scientific impact. Both measures also indicate a strong correlation and overlap between the ranked list formed from the total citation counts and the ranked list formed from the total citation count minus the contradicting citations. Based on this high correlation and overlap, taking out contradicting citations is not needed when determining scientific impact.

Publication and Impact of Preprints Included in the First 100 Editions of the CDC COVID-19 Science Update (Preprint)

2021 ◽  
Author(s):  
Jeremy Otridge ◽  
Cynthia Ogden ◽  
Kyle Bernstein ◽  
Martha Knuth ◽  
Julie Fishman ◽  
...  
Keyword(s):  
Citation Count ◽  
Relevant Information ◽  
Publication Rate ◽  
Time Interval ◽  
Public Health Decision ◽  
Health Decision Making ◽  
Publication Rates ◽  
Health Decision ◽  
Update Process ◽  
Article Impact

BACKGROUND Preprints are publicly available manuscripts posted to various servers that have not been peer-reviewed. Although preprints have existed since 1961, they have gained increased popularity and credibility during the COVID-19 pandemic due to the need for immediate, relevant information. OBJECTIVE The inclusion of preprints in the CDC COVID-19 Science Update, a weekly publication that provides brief summaries of new COVID-19-related studies, is an opportunity to evaluate the publication rate and impact (Altmetric Attention Score and citation count) of selected preprints and assess the performance of the Science Update to select impactful preprints. METHODS All preprints in the first 100 editions (April 1, 2020 – July 30, 2021) of the Science Update were included in the study. Preprints that were not published were categorized as “unpublished preprints”. Preprints that were subsequently published exist in two versions (in a peer-reviewed journal and on the original preprint server) which were analyzed separately and referred to as “peer-reviewed preprint” and “original preprint”, respectively. Time-to-publish was the time interval between the date on which a preprint was first posted to the date on which it was first available as a peer-reviewed article. Impact was quantified by Altmetric Attention Score and citation count for all available manuscripts on August 6, 2021. Preprints were analyzed by publication status, rate, and time to publication. RESULTS Among 275 preprints included in the CDC COVID-19 Science Update during the study period, most came from three servers: medRxiv (n=201), bioRxiv (n=41), and SSRN (n=25), with eight coming from other sources. More than half (55.3%) were eventually published. The median time-to-publish was 2.31 months (IQR 1.38-3.73). When preprints posted in the last 2.31 months were excluded (to account for the time-to-publish), the publication rate was to 67.8%. Seventy-six journals published at least one preprint from the CDC COVID-19 Science Update and 18 journals published at least three. The median Altmetric Attention Score for unpublished preprints (n=123) was 146 (IQR 22-552) and median citation count of 2 (IQR 0-8); for original preprints (n=152) these values were 212 (IQR 22-1164) and 14 (IQR 2-40), respectively. For peer-review preprints, these values were 265 (IQR 29-1896) 19 (IQR 3-101), respectively. CONCLUSIONS Prior studies of COVID-19 preprints found publication rates between 5.4% and 21.1%. Preprints included in the CDC COVID-19 Science Update were published at a higher rate than overall COVID-19 preprints, and those that were ultimately published were published within months and received higher attention scores than unpublished preprints. These findings indicate that the Science Update process for selecting preprints appears have done so with high fidelity in terms of their likelihood to be published and impactful. Incorporation of high-quality preprints into the CDC COVID-19 Science Update improves this activity’s capacity to inform meaningful public health decision making.

scholarly journals Pharmacological interventions for the COVID-19 pandemic and the use of preprint articles: The good, the bad and the ugly

2020 ◽  
Author(s):  
Bryan Nicolalde ◽  
Diego Añazco ◽  
Mariam Mushtaq ◽  
Isabel Espinosa ◽  
Jimena Gimenez ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Scientific Community ◽  
Case Series ◽  
Science Research ◽  
Publication Rate ◽  
Scientific Production ◽  
Pharmacological Interventions ◽  
Novel Coronavirus ◽  
Study Designs ◽  
Number Of Citations

Abstract Background: Preprints are preliminary reports that have not been peer-reviewed. On Dec 2019, a novel coronavirus appeared in China, and since then, scientific production, including preprints, has drastically increased. In this study, we intend to evaluate how often preprints regarding pharmacological interventions against COVID-19 were cited, in spite of the fact that some of these preprints remained unpublished.Methods: We conducted a search on medRxiv and bioRxiv to identify preprints related to pharmacological interventions against SARS-CoV-2 from Jan 1st to Mar 31, 2020. We gathered metadata on included preprints and identified if they had been published in a peer-reviewed journal. We performed Mann-Whitney U tests to evaluate if published articles had differences in citation numbers or usage, as defined by PDF downloads and abstract views, when compared to preprints that were not published.Results: Our sample included 97 preprints, of which only 14 were published on peer-reviewed journals and 83 remained unpublished. The most common study designs we found among preprints were basic science research and case series. Published articles had a significantly higher number of citations and metrics (PDF and abstract downloads) when compared to unpublished preprints.Conclusions: The use of preprints during this pandemic has been higher than in previous outbreaks, however, the publication rate in peer-reviewed journals in our sample was low. Preprints should be used as a mean to display preliminary data rapidly in order to obtain feedback by the scientific community, or to guide further research. However, due to the lack of peer-review, and potentially flawed data analysis, preprints alone should not be used to guide clinical practice, as the risk of unwarranted modifications to management is concerning.

Citation Metrics in Psychological Science

2021 ◽  
pp. 174569162096412
Author(s):  
Nina Radosic ◽  
Ed Diener
Keyword(s):  
Citation Count ◽  
National Research Council ◽  
The United States ◽  
Early Career ◽  
Faculty Members ◽  
Psychological Science ◽  
Enormous Variation ◽  
Citation Counts ◽  
Citation Metrics ◽  
Number Of Citations

We present norms for faculty citation counts based on 811 faculty members at 30 PhD-granting psychology departments in the United States across the range of the National Research Council rankings. The metrics were highly skewed, with most scientists having a low to moderate number of citations of their work and a few scientists having extremely high numbers. However, the median per-year citation count was 149, showing widespread scientific contributions across scholars. Some individuals in lower ranked departments are more highly cited than the average scholar in higher ranked departments, with enormous variation in citation counts in both the low- and high-ranking departments. Citation counts overall have risen in recent years, and the citations of early-career scholars are increasing at a faster rate than their senior colleagues did at the same point in their careers. We found that citation counts at the beginning of scientists’ careers substantially predict lifetime citation success. Young scholars’ citation counts are associated with obtaining positions at higher ranked universities. Finally, we found no significant differences for subfields of psychology. In sum, although a few highly productive scientists have a very large influence, trends reveal that contributions to psychological science are growing over time, widespread, and not limited to a few stars and elite departments.

scholarly journals Online Resources for Scholarly Journal Publishing

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Larissa Wodtke
Keyword(s):  
Scholarly Journal ◽  
Online Resources ◽  
Scholarly Journals ◽  
Journal Publishing ◽  
Environmental Scan ◽  
Software Companies

This paper describes an environmental scan of online resources for editors and publishers of scholarly journals that was conducted from March to June 2017. The resources in this scan take the form of archived webinars, reports, publications, infographics, and conference presentation videos supplied by other associations and societies, as well as libraries, software companies, and commercial publishers.

scholarly journals Early Transmission Dynamics of Novel Coronavirus (COVID-19) in Nigeria

2020 ◽  
Vol 17 (9) ◽  
pp. 3054 ◽  
Author(s):  
Oyelola A. Adegboye ◽  
Adeshina I. Adekunle ◽  
Ezra Gayawan
Keyword(s):  
Doubling Time ◽  
Reproduction Number ◽  
Infected Individual ◽  
Credible Interval ◽  
World Health ◽  
Time Interval ◽  
Serial Interval ◽  
Imported Cases ◽  
Novel Coronavirus ◽  
Health Organization

On 31 December 2019, the World Health Organization (WHO) was notified of a novel coronavirus disease in China that was later named COVID-19. On 11 March 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on 27 February 2020. This study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria. We estimated the early transmissibility via time-varying reproduction number based on the Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector), and adjusted for disease importation. By 11 April 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% confidence interval (CI): 0.05–0.10) with a doubling time of 9.84 days (95% CI: 7.28–15.18). Separately for imported cases (travel-related) and local cases, the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using a three-weekly window while adjusting for imported cases. The estimated reproduction number was 4.98 (95% CrI: 2.65–8.41) at day 22 (19 March 2020), peaking at 5.61 (95% credible interval (CrI): 3.83–7.88) at day 25 (22 March 2020). The median reproduction number over the study period was 2.71 and the latest value on 11 April 2020, was 1.42 (95% CrI: 1.26–1.58). These 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.

scholarly journals The Political Science 400: With Citation Counts by Cohort, Gender, and Subfield

2019 ◽  
Vol 52 (2) ◽  
pp. 296-311
Author(s):  
Hannah June Kim ◽  
Bernard Grofman
Keyword(s):  
Political Science ◽  
Citation Count ◽  
The United States ◽  
The Political ◽  
Tenure Track ◽  
Full List ◽  
Online Appendix ◽  
Women Scholars ◽  
Citation Counts ◽  
And Gender

ABSTRACTThis article updates the Masuoka, Grofman, and Feld 2002 dataset that identified the then-3,719 faculty in political science PhD-granting departments in the United States. That dataset contained information about each faculty member, including date and PhD-granting department, lifetime citation counts, fields of interest, and school of employment. We similarly create a database with the 4,089 currently tenured or tenure-track faculty, along with emeritus faculty, at US PhD-granting departments ca. 2017–2018. Using Google Scholar Profiles, along with manual counts for those who do not have a profile, we sort the dataset by citation count, PhD cohort, field of interest, and gender. This article identifies the 100 currently most-cited scholars, the 25 most-cited in each PhD cohort and subfield, the 40 most-cited women scholars, and the 25 most-cited emeriti. The full list of The Political Science 400 is available in an online appendix.

Symposium on peer reviewing in scholarly journals

1995 ◽  
Vol 13 (2) ◽  
pp. 237-272
Author(s):  
Richard C. Gebhardt ◽  
Carol Berkenkotter ◽  
Phillip Arrington ◽  
Douglas Hesse ◽  
Sheryl I. Fontaine ◽  
...  
Keyword(s):  
Scholarly Journals ◽  
Peer Reviewing
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