scholarly journals Ckj consolidation among Q1 Urology and Nephrology journals

2020 ◽  
Vol 13 (5) ◽  
pp. 723-727
Author(s):  
Alberto Ortiz
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Impact Factor ◽  
Cost Efficiency ◽  
Journal Impact Factor ◽  
Outcome Prediction ◽  
Web Of Science ◽  
Sglt2 Inhibitors ◽  
The Impact ◽  
Journal Impact

Abstract The Clinical Kidney Journal (ckj) impact factor from Clarivate’s Web of Science for 2019 was 3.388. This consolidates ckj among journals in the top 25% (first quartile, Q1) in the Urology and Nephrology field according to the journal impact factor. The manuscripts contributing the most to the impact factor focused on chronic kidney disease (CKD) epidemiology and evaluation, CKD complications and their management, cost-efficiency of renal replacement therapy, pathogenesis of CKD, familial kidney disease and the environment–genetics interface, onconephrology, technology, SGLT2 inhibitors and outcome prediction. We provide here an overview of the hottest and most impactful topics for 2017–19.

scholarly journals Modeling and Prediction of the Impact Factor of Journals Using Open-Access Databases

2020 ◽  
Vol 49 (5) ◽  
pp. 35-58
Author(s):  
Matthias Templ
Keyword(s):  
Open Access ◽  
Impact Factor ◽  
Journal Impact Factor ◽  
Web Of Science ◽  
Functional Relationships ◽  
Modeling And Prediction ◽  
Novel Approach ◽  
The Impact ◽  
Journal Impact ◽  
The Web

This article is motivated by the work as editor-in-chief of the Austrian Journal of Statistics and contains detailed analyses about the impact of the Austrian Journal of Statistics. The impact of a journal is typically expressed by journal metrics indicators. One of the important ones, the journal impact factor is calculated from the Web of Science (WoS) database by Clarivate Analytics. It is known that newly established journals or journals without membership in big publishers often face difficulties to be included, e.g., in the Science Citation Index (SCI) and thus they do not receive a WoS journal impact factor, as it is the case for example, for the Austrian Journal of Statistics. In this study, a novel approach is pursued modeling and predicting the WoS impact factor of journals using open access or partly open-access databases, like Google Scholar, ResearchGate, and Scopus. I hypothesize a functional linear dependency between citation counts in these databases and the journal impact factor. These functional relationships enable the development of a model that may allow estimating the impact factor for new, small, and independent journals not listed in SCI. However, only good results could be achieved with robust linear regression and well-chosen models. In addition, this study demonstrates that the WoS impact factor of SCI listed journals can be successfully estimated without using the Web of Science database and therefore the dependency of researchers and institutions to this popular database can be minimized. These results suggest that the statistical model developed here can be well applied to predict the WoS impact factor using alternative open-access databases. 

Analysis of the journal impact factor and related bibliometric indicators in education and educational research category

2021 ◽  
pp. 1-22
Author(s):  
Metin Orbay ◽  
Orhan Karamustafaoğlu ◽  
Ruben Miranda
Keyword(s):  
Impact Factor ◽  
Educational Research ◽  
Journal Impact Factor ◽  
Impact Factors ◽  
Bibliometric Indicators ◽  
Strongly Correlated ◽  
Starting Point ◽  
Consistent Assessment ◽  
The Impact ◽  
Journal Impact

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.

scholarly journals Comparison of the Impact Factors of the Most-Cited Cardiovascular Journals

2019 ◽  
Vol 124 (12) ◽  
pp. 1718-1724 ◽  
Author(s):  
Tobias Opthof
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
European Heart Journal ◽  
The Other ◽  
Impact Factors ◽  
Additional Advantage ◽  
The Right ◽  
Number Of Classes ◽  
The Impact ◽  
Journal Impact

In this article, I show that the distribution of citations to papers published by the top 30 journals in the category Cardiac & Cardiovascular Systems of the Web of Science is extremely skewed. This skewness is to the right, which means that there is a long tail of papers that are cited much more frequently than the other papers of the same journal. The consequence is that there is a large difference between the mean and the median of the citation of the papers published by the journals. I further found that there are no differences between the citation distributions of the top 4 journals European Heart Journal , Circulation , Journal of the American College of Cardiology , and Circulation Research . Despite the fact that the journal impact factor (IF) varied between 23.425 for Eur Heart J and 15.211 for Circ Res with the other 2 journals in between, the median citation of their articles plus reviews (IF Median) was 10 for all 4 journals. Given the fact that their citation distributions were similar, it is obvious that an indicator (IF Median) that reflects this similarity must be superior to the classical journal impact factor, which may indicate a nonexisting difference. It is underscored that the IF Median is substantially lower than the journal impact factor for all 30 journals under consideration in this article. Finally, the IF Median has the additional advantage that there is no artificial ranking of 128 journals in the category but rather an attribution of journals to a limited number of classes with comparable impact.

scholarly journals In praise of the impact factor

2020 ◽  
Author(s):  
John Antonakis ◽  
Nicolas Bastardoz ◽  
Philippe Jacquart
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Journal Articles ◽  
Good Proxy ◽  
Number Of Citations ◽  
The Impact ◽  
Journal Impact ◽  
Article Quality

The impact factor has been criticized on several fronts, including that the distribution of citations to journal articles is heavily skewed. We nuance these critiques and show that the number of citations an article receives is significantly predicted by journal impact factor. Thus, impact factor can be used as a reasonably good proxy of article quality.

scholarly journals Modeling and Simulation Analysis of Journal Impact Factor Dynamics Based on Submission and Citation Rules

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jian Zhou ◽  
Lin Feng ◽  
Ning Cai ◽  
Jie Yang
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Simulation Analysis ◽  
Impact Factors ◽  
Model Parameters ◽  
Review Time ◽  
Citation Window ◽  
Sociological Factors ◽  
The Impact ◽  
Journal Impact

The variation of the journal impact factor is affected by many statistical and sociological factors such as the size of citation window and subject difference. In this work, we develop an impact factor dynamics model based on the parallel system, which can be used to analyze the correlation between the impact factor and certain elements. The parallel model aims to simulate the submission and citation behaviors of the papers in journals belonging to a similar subject, in a distributed manner. We perform Monte Carlo simulations to show how the model parameters influence the impact factor dynamics. Through extensive simulations, we reveal the important role that certain statistics elements and behaviors play to affect impact factors. The experimental results and analysis on actual data demonstrate that the value of the JIF is comprehensively influenced by the average review time, average number of references, and aging distribution of citation.

scholarly journals Metrics: Measuring importance

2012 ◽  
Vol 34 (1) ◽  
pp. 38-41
Author(s):  
Caroline Black
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Academic Literature ◽  
Research Article ◽  
The Impact ◽  
Published Research ◽  
Journal Impact ◽  
Quality Of Research

Bibliometrics is the term used to describe various approaches to analysing measures of the use of academic literature, in particular articles in peer-reviewed journals. More broadly, the topic addresses the validity or otherwise of these measures as indicators of the impact, influence or value of the research being reported. These measures, and in particular the journal Impact Factor, are used as evidence for the quality of research, to make decisions about appointments, to judge a journal editor's success, and (it is assumed) to make funding decisions. Until recently, bibliometrics was mainly about citations, but now it is increasingly common to measure online usage, and even tweets, blogging and user star-ratings when assessing the contribution of a published research article.

scholarly journals Use of the journal impact factor for assessing individual articles: Statistically flawed or not?

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 366
Author(s):  
Ludo Waltman ◽  
Vincent A. Traag
Keyword(s):  
Impact Factor ◽  
San Francisco ◽  
Journal Impact Factor ◽  
Dominant Role ◽  
Research Assessment ◽  
Primary Focus ◽  
Number Of Citations ◽  
The Impact ◽  
Journal Impact ◽  
Accurate Indicator

Most scientometricians reject the use of the journal impact factor for assessing individual articles and their authors. The well-known San Francisco Declaration on Research Assessment also strongly objects against this way of using the impact factor. Arguments against the use of the impact factor at the level of individual articles are often based on statistical considerations. The skewness of journal citation distributions typically plays a central role in these arguments. We present a theoretical analysis of statistical arguments against the use of the impact factor at the level of individual articles. Our analysis shows that these arguments do not support the conclusion that the impact factor should not be used for assessing individual articles. Using computer simulations, we demonstrate that under certain conditions the number of citations an article has received is a more accurate indicator of the value of the article than the impact factor. However, under other conditions, the impact factor is a more accurate indicator. It is important to critically discuss the dominant role of the impact factor in research evaluations, but the discussion should not be based on misplaced statistical arguments. Instead, the primary focus should be on the socio-technical implications of the use of the impact factor.

scholarly journals How Good Is Good Enough? - The Value of Impact Factor in Determining the Quality of Biomedical Research: A Review of Perspectives

2020 ◽  
Author(s):  
Mir Ibrahim Sajid ◽  
Hafsa Khan Tareen ◽  
Samira Shabbir Balouch ◽  
Syed Muhammad Awais
Keyword(s):  
Impact Factor ◽  
Biomedical Research ◽  
Journal Impact Factor ◽  
Citation Index ◽  
Surrogate Marker ◽  
Job Security ◽  
Mathematical Equation ◽  
The Impact ◽  
Journal Impact

The Journal Impact Factor is a Science Citation Index developed metric to evaluate the citations an article receives over a period of two years and serves as a surrogate marker to evaluate the quality of biomedical research. However, even though the calculation seems to be a straightforward mathematical equation, multiple confounders artificially impact the score- such as citing behavior, the region and language the journal is published in, and the ‘tip of the iceberg’ phenomenon. Despite an increase in metrics developed to alternatively gauge the prestige of research and the researcher- such as Eigenfactor Score, Article Influence Score and Google PageRank, the impact factor remains an essential instrument in dictating the scientist’s future in terms of job security, tenure extension, grant approval, and acquiring bonus, both hierarchical and monetary

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