A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts

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Belikov" }, { "@type": "Person", "name": "Vitaly V. Belikov" } ], "publisher": { "@type": "Organization", "name": "F1000Research", "logo": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 480, "width": 60 } }, "image": { "@type": "ImageObject", "url": "https://f1000research.com/img/AMP/F1000Research_image.png", "height": 1200, "width": 150 }, "description": "The use of citation metrics for evaluation of individual researchers has dramatically increased over the last decade. However, currently existing indices either are based on misleading premises or are cumbersome to implement. This leads to poor assessment of researchers and creates dangerous trends in science, such as overproduction of low quality articles. Here we propose an index (namely, the L-index) that does not depend on the number of publications, accounts for different co-author contributions and age of publications, and scales from 0.0 to 9.9. Moreover, it can be calculated with the help of freely available software." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/4-884/v2", "name": "A citation-based, author- and age-normalized, logarithmic index for..." } } ] } Home Browse A citation-based, author- and age-normalized, logarithmic index for... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Belikov AV and Belikov VV. A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.12688/f1000research.7070.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Method Article Revised A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] Aleksey V. Belikov https://orcid.org/0000-0002-4261-1024 1 , Vitaly V. Belikov 2 Aleksey V. Belikov https://orcid.org/0000-0002-4261-1024 1 , Vitaly V. Belikov 2 PUBLISHED 02 Jun 2025 Author details Author details 1 Otto-von-Guericke-Universität, Magdeburg, Germany 2 Water Problems Institute, Russian Academy of Sciences, Moscow, Russian Federation Aleksey V. Belikov Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Vitaly V. Belikov Roles: Conceptualization, Methodology, Validation, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract The use of citation metrics for evaluation of individual researchers has dramatically increased over the last decade. However, currently existing indices either are based on misleading premises or are cumbersome to implement. This leads to poor assessment of researchers and creates dangerous trends in science, such as overproduction of low quality articles. Here we propose an index (namely, the L-index) that does not depend on the number of publications, accounts for different co-author contributions and age of publications, and scales from 0.0 to 9.9. Moreover, it can be calculated with the help of freely available software. READ ALL READ LESS Keywords Research, scientific, metrics, impact, weighted, bibliometric, scientometric, Publish or Perish Corresponding Author(s) Aleksey V. Belikov ( [email protected] ) Close Corresponding author: Aleksey V. Belikov Competing interests: The authors are active researchers and hence are affected by current research evaluation practices. The authors have no professional or personal connections to Harzing.com, Google Scholar or any other citation database or citation analysis software developers. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Belikov AV and Belikov VV. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Belikov AV and Belikov VV. A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.12688/f1000research.7070.2 ) First published: 22 Sep 2015, 4 :884 ( https://doi.org/10.12688/f1000research.7070.1 ) Latest published: 02 Jun 2025, 4 :884 ( https://doi.org/10.12688/f1000research.7070.2 ) Revised Amendments from Version 1 We corrected the L-index formula to completely prevent the appearance of negative values; wrote a Python script allowing to fully automatically get the data from a scientist's Google Scholar profile and produce a report with the L-index and the list of the scientist's publications sorted by the L-index contribution score (deposited on Github and Zenodo); calculated L-indices and reports for 45 prominent scientists in biomedicine, neuroscience, physics and computer science (updated Figure 2); demonstrated that 100 most cited publications are sufficient to capture the bulk of the L-index value (new Figure 3); We corrected the L-index formula to completely prevent the appearance of negative values; wrote a Python script allowing to fully automatically get the data from a scientist's Google Scholar profile and produce a report with the L-index and the list of the scientist's publications sorted by the L-index contribution score (deposited on Github and Zenodo); calculated L-indices and reports for 45 prominent scientists in biomedicine, neuroscience, physics and computer science (updated Figure 2); demonstrated that 100 most cited publications are sufficient to capture the bulk of the L-index value (new Figure 3); To read any peer review reports and author responses for this article, follow the "read" links in the Open Peer Review table. READ REVIEWER RESPONSES Introduction There is an ever-present need to evaluate researchers’ performance, because resources are limited and contenders are numerous. Before the advent of journal impact factors (JIFs, 1 ), all evaluations were performed via peer review. Although JIFs were intended for librarians to decide which journals to subscribe to, they have become a commonly used proxy for the quality of journal articles 2 . However, the distribution of citations to individual articles within a journal is highly skewed. Twenty five percent of the most highly cited articles can account for 90% of a journal’s IF 3 . The rest of the articles receive a few citations each, if any. Thus, using JIFs for assessing the quality of individual articles and, further, for evaluating researchers is categorically not recommended 4 . The rapid development of the internet and electronic citation databases, such as PubMed , Google Scholar , Web of Science , Scopus , CiteSeer and others, has made it easier to count citations of individual articles. It is now possible to automatically calculate the total number of citations that the publications of a given researcher have accumulated. However, these numbers can range from 1 to 100,000 and, obviously, do not represent the equal variation in researchers’ capabilities. For example, human IQ scores vary only about 2–4 fold 5 . There are two main reasons why the total number of citations cannot be used to adequately compare individual researchers. First, there is usually more than one author for each publication. Some of the most highly cited articles, such as reports from experiments on particle accelerators 6 or from genome sequencings 7 , and guidelines for medical practitioners 8 , have from tens to hundreds of co-authors, usually listed in alphabetical order. Thus, it is inadequate to assign all the thousands of citations to each of those authors. A similar situation is when a researcher operates some very expensive and thus rare equipment, and is listed on papers of all other researchers who perform experiments on that equipment 9 . It is clear that the researcher also does not deserve all citations of those papers, as his contribution is purely technical. Many ways to divide citations between co-authors have been proposed 10 , 11 , but the only practical way is to split them equally, i.e. to assign each co-author 1/ n of the citations, where n is the total number of co-authors. Another factor is that citations accumulate with time. A researcher who started his career 30 years ago will undoubtedly have more citations than a young postdoc, but this does not necessarily mean that the former is a better scientist. Moreover, a paper that has been highly cited is likely to be cited even more in the future 12 . Thus, citations exhibit the behavior of preferential attachment, which results in their distribution according to the power law 13 . These considerations make it necessary to adjust for the age of each publication, in order to properly assess current capabilities and impact of researchers, not their past successes, and to partially compensate for the preferential attachment. Dividing the number of citations by the age of the publication in years seems to be an adequate measure, as it mirrors the power law distribution that citations have. Finally, a large variety of individual citation metrics have been proposed 14 , the most widely disseminated of which is the h-index 15 . The drawback of the majority of these metrics is that they take into consideration the number of publications. For example, the h-index can never exceed the total number of publications a scientist has. However, several researchers of undisputed scientific merit, such as Sir Isaac Newton, Gregor Mendel or Peter Higgs, have published only a few, however significant, works. This lack in the number of publications leads them to have h-indices of 4, 1 and 9, respectively, which are disparagingly low. All other derivatives of the h-index, as well as all indices that take into account publication counts, suffer from the same drawback and hence should never be used for evaluation purposes. However, they are used, promoting a grueling and futile quest for quantity of publications, at the expense of quality, reflected in the infamous “publish or perish” catchphrase 16 . Fortunately, this issue has been recently called to public attention, most notably in the form of the San Francisco Declaration on Research Assessment , and some measures have been proposed 17 . Overall, there is an immense need for a simple but reliable indicator for individual researcher assessment. Here, we propose such an index, which accounts for different co-author contributions and age of publications, and does not depend on the number of publications. Moreover, it conveniently ranges from 0.0 to 9.9, and can be calculated with the help of freely available software. Methods To address the concerns highlighted in the introduction of this article, we have set out to construct an index that accounts for different co-author contributions and age of publications. This has initially led us to the following formula: I = ∑ i = 1 N c i a i y i ( 1 ) where I – preliminary index, c i – number of citations to i -th publication, a i – number of authors of i -th publication, y i – age in years of i -th publication, N – number of publications. We then decided to estimate the range of values that our preliminary index can have. First, we calculated I for a hypothetical PhD student who recently received the first citation to his first paper, with 5 authors: I = 1 5 × 1 = 0.2. Next, we calculated I for Geoffrey Hinton , a British-Canadian computer scientist, cognitive scientist, and Nobel laureate in physics, known for his work on artificial neural networks, with almost a million citations. To this aim, we utilized the freely available software Publish or Perish . This program imports citation data from Google Scholar author profiles. The parameter AWCRpA (age-weighted citation rate per author) can be obtained from this program, and is roughly equivalent to our preliminary index. The AWCRpA value for Hinton, as calculated by Publish or Perish on 8 th of May 2025, was 23875. Thus, even upon correcting for multiple authorship and age, the sum of citations varies by approximately 100000 fold. As it is unlikely that the human brain can exhibit such a tremendous difference in its efficiency or talents, the preliminary index should be mapped to a more appropriate scale, in order to make it more useful in meaningfully comparing researchers. It seems that a 1–10 scale is optimal, because it is closer to the true variation in human intellectual or other capabilities 5 , and is widely used in various metrics, thus being more intuitive. The natural logarithm function appears to be ideal for this scaling purpose. Compared to the square root or the cube root, the natural logarithm allows better resolution of differences between the majority of scientists, with the exception of the most prominent ones ( Figure 1 ). To prevent the L-index from getting into the negative values when the preliminary index is less than one, the preliminary index is increased by one point before taking the logarithm. Figure 1. The natural logarithm function increases evenly across the citation range. The natural logarithm (ln c n ), cube root ( c n 3 ) and square root ( c n ) functions of normalized citations ( c n ) are shown. Finally, the formula for the Logarithm index (L-index) became: L = ln ( ∑ i = 1 N c i a i y i + 1 ) ( 2 ) where c i – number of citations to i -th publication, a i – number of authors of i -th publication, y i – age in years of i -th publication, N – number of publications. When ∑ i = 1 N c i a i y i is calculated as AWCRpA in Publish or Peris h , formula (2) takes the form: L = ln ( A W C R p A + 1 ) ( 3 ) Publish or Perish , while being an excellent piece of software, relies on scraping the Google Scholar profile publication lists, which display truncated lists of coauthors for many publications. This prevents calculation of the correct number of coauthors and hence the correct L-index. To allow precise L-index calculation, we created a Python script 18 that retrieves every publication from Google Scholar individually, each containing the full unabridged list of coauthors. It then counts the number of coauthors for each publication and calculates the L-index. Results and discussion Figure 2 shows the typical scale of the L-index with the values for 45 prominent scientists in biomedicine, neuroscience, physics and computer science, as well as the typical values for a PhD student, a postdoc and a principal investigator (PI). The L-index values were calculated on the 8 th of May 2025 using the L-index Calculator 18 based on 100 most cited publications from publicly available Google Scholar profiles. The reports for each scientist, containing top publications sorted by their contribution to the L-index, are available as an external dataset 19 . To estimate typical L-indices for a PhD student, a postdoc and a principal investigator (PI), we averaged the L-index values for 5 PhD students, 10 postdocs and 15 PIs that we personally know. Figure 2. The L-index scale and notable examples. The typical range of the L-index is shown. L-index values of 45 prominent scientists in biomedicine, neuroscience, physics and computer science are shown. Nobel Prize laureates are indicated in gold. Approximate positions of a typical PhD student, postdoc and principal investigator (PI) are also displayed. The L-index values were calculated on the 8 th of May 2025 using the L-index Calculator 18 based on 100 most cited publications from publicly available Google Scholar profiles. The reports for each scientist containing top publications sorted by their contribution to the L-index are available as an external dataset 19 . It can be seen from this figure that the L-index adequately captures the intuitive ranking, i.e. PhD student < Postdoc < PI < … < Nobel Laureates. Moreover, it allows an objective (or, at least, statistically averaged collective subjective) quantitative assessment of researchers, which is a virtue that traditional peer review cannot accomplish. However, in cases where L-indices of the applicants are equal up to one decimal place, we strongly suggest the use of peer review, involving thorough examination of their publications, rather than differentiation of scientists based on the second decimal place, to avoid false precision and statistical bias. In case of young researchers that have only a few citations, it is also advisable to use peer review, as the limited data do not allow for the statistically robust calculation of the citation index. The L-index can increase or decrease with time, as it depends on the age of publications. Thus, it favors the impact of recent publications and gives a much needed advantage to younger researchers. However, if a scientist has made such a significant discovery that its impact only increases with time, his L-index will stay high regardless of the age of the publication. Perfect examples of this are John von Neumann, Albert Einstein, Lev Landau, Alan Turing, Charles Darwin, Richard Feynman and Werner Heisenberg. Despite them ceasing to publish original work decades ago, their L-indices are still higher than those of the majority of current researchers ( Figure 2 ). It has to be noted that reprints of their seminal works or even full collections of works in modern journals contribute significantly to their L-indices because the age of the paper in the denominator is dramatically reduced whereas the original work is already very well known in the scientific community, so the fresh reprint immediately attracts lots of citations. More importantly, as Google Scholar (or the curator of the scientist’s profile) often merges the reprints of the same work from different years into one, it sometimes assigns the year of the latest reprint instead of the year of the original publication to the merged entity. This can dramatically affect the L-index, as all citations accumulated over decades are now divided by a very young age of the modern reprint. We had to exclude a few prominent scientists of the past from our analysis due to this issue. However, this is the problem of the database curation, not the L-index. To make sure that 100 most cited articles capture the bulk of the L-index value, we utilized our dataset of reports for 45 prominent scientists 19 , each containing top publications sorted by their contribution to the L-index which we called the score: s i = c i a i y i ( 4 ) where s i – the score of i -th publication, c i – number of citations to i -th publication, a i – number of authors of i -th publication, y i – age in years of i -th publication. For each scientist separately, we first normalized the scores for each paper relative to the highest scoring paper for that scientist (the first place in the report). Because each paper also has a citation value, we now sorted the papers by citations but kept the associated score values. We then averaged the normalized scores for all papers ranking 1 st by citations across all 45 scientists, for all papers ranking 2 nd etc. Finally, we plotted the averaged normalized scores vs paper rank by citations ( Figure 3 ). Figure 3. Average normalized score vs. citation rank. Scores and citations were calculated on the 8 th of May 2025 using the L-index Calculator 18 for 100 most cited publications from publicly available Google Scholar profiles of 45 prominent scientists in biomedicine, neuroscience, physics and computer science. The score of a publication is the number of citations divided by the number of authors and age in years. For each scientist separately, the scores for each paper were normalized relative to the highest scoring paper for that scientist. The papers were sorted by citations and the normalized scores averaged for all papers with the same citation rank. The reports for each scientist containing top publications sorted by scores are available as an external dataset 19 . It can be clearly seen that contribution to the L-index, which is essentially the logarithm of the sum of paper scores, drops rapidly with increasing citation rank, due to the power law distribution of citations 13 . Thus, using 100 most cited papers gives plenty of headroom to capture almost all of the important signal. Even top 50 papers are sufficient for most cases. Nevertheless, scientists should be compared based on the same number of top publications used for calculating their L-indices. The quantitative comparison of the L-index with other evaluation indices, such as the h-index and its derivatives, was purposefully avoided in this article, for the reason that those indices have been designed on different premises, such as to account for the number of publications. When evaluating the performance of a researcher, it should first be decided which parameter is considered adequate for the purpose – the number of publications, which does not tell anything about their quality, or the number of citations, which, however indirectly, indicates the impact that the publications have made. If the latter option is selected, the L-index can help to account for the effects of multiple co-authorship and publication age, and present the results in a simple and intuitive form. Data availability statement Analysis code available from: https://github.com/alekseybelikov/L-index Archived analysis code as at time of publication: Belikov A: L-index Calculator: A Python tool for academic citation analysis (v1.0) [Software]. Zenodo . 2025; https://doi.org/10.5281/zenodo.15356378 Analysis code license: GNU Affero General Public License v3.0 (AGPL-3.0) Analysis results available at: Belikov A: L-index reports for selected prominent scientists [Data set]. Zenodo . 2025; https://doi.org/10.5281/zenodo.15368429 • Analysis results license: Creative Commons Attribution 4.0 International (CC BY 4.0) Author contributions AVB created the first L-index formula, created the L-index Calculator, collected and analyzed the data, interpreted the results, prepared the figures and wrote the manuscript. VVB created the current L-index formula, interpreted the results and revised the manuscript. All authors have agreed to the final content. Acknowledgements The authors are grateful to Prof. A. Borthwick, Dr. A. Barmashov, and V. Hrubilov for the useful discussions. Google Gemini 2.5 Pro was used to assist in writing the code for the L-index Calculator and for rendering the Figure 3 . Faculty Opinions recommended References 1. Garfield E: Citation analysis as a tool in journal evaluation. Science. 1972; 178 (4060): 471–9. PubMed Abstract | Publisher Full Text 2. Adam D: The counting house. Nature. 2002; 415 (6873): 726–9. PubMed Abstract | Publisher Full Text 3. Not-so-deep impact. Nature. 2005; 435 (7045): 1003–4. PubMed Abstract | Publisher Full Text 4. Beware the impact factor. Nat Mater. 2013; 12 (2): 89. PubMed Abstract | Publisher Full Text 5. Hunt E: Human intelligence. Cambridge University Press, 2010. Reference Source 6. Aad G, Abajyan T, Abbott B, et al. : Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC. Phys Lett B. 2012; 716 (1): 1–29. 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Proc Natl Acad Sci U S A. 2014; 111 (34): 12325–30. PubMed Abstract | Publisher Full Text | Free Full Text 12. Merton RK: The Matthew effect in science: the reward and communication systems of science are considered. Science. 1968; 159 (3810): 56–63. PubMed Abstract | Publisher Full Text 13. Price DDS: A general theory of bibliometric and other cumulative advantage processes. J Am Soc Inf Sci. 1976; 27 (5): 292–306. Publisher Full Text 14. Van Noorden R: Metrics: a profusion of measures. Nature. 2010; 465 (7300): 864–6. PubMed Abstract | Publisher Full Text 15. Hirsch JE: An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A. 2005; 102 (46): 16569–72. PubMed Abstract | Publisher Full Text | Free Full Text 16. Garfield E: What is the primordial reference for the phrase ‘publish or perish’? Scientist. 1996; 10 (12): 11. Reference Source 17. Hicks D, Wouters P, Waltman L, et al. : Bibliometrics: the Leiden Manifesto for research metrics. Nature. 2015; 520 (7548): 429–31. PubMed Abstract | Publisher Full Text 18. Belikov A: L-index calculator: a python tool for academic citation analysis [Software]. Zenodo. 2025. http://www.doi.org/10.5281/zenodo.15356377 19. Belikov A: L-index reports for selected prominent scientists [Data set]. Zenodo. 2025. http://www.doi.org/10.5281/zenodo.15368429 Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 22 Sep 2015 ADD YOUR COMMENT Comment Author details Author details 1 Otto-von-Guericke-Universität, Magdeburg, Germany 2 Water Problems Institute, Russian Academy of Sciences, Moscow, Russian Federation Aleksey V. Belikov Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing Vitaly V. Belikov Roles: Conceptualization, Methodology, Validation, Writing – Review & Editing Competing interests The authors are active researchers and hence are affected by current research evaluation practices. The authors have no professional or personal connections to Harzing.com, Google Scholar or any other citation database or citation analysis software developers. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 02 Jun 2025, 4:884 https://doi.org/10.12688/f1000research.7070.2 version 1 Published: 22 Sep 2015, 4:884 https://doi.org/10.12688/f1000research.7070.1 Copyright © 2025 Belikov AV and Belikov VV. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. 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Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 1 VERSION 1 PUBLISHED 22 Sep 2015 Views 0 Cite How to cite this report: Colbert-Lewis DM. Reviewer Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10836 ) The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10836 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 17 Nov 2015 Danielle M. Colbert-Lewis , Department of James E. Shepard Memorial Library, North Carolina Central University, Durham, NC, USA Approved VIEWS 0 https://doi.org/10.5256/f1000research.7610.r10836 This title is appropriate for the content of the article and the abstract represents a suitable summary for the work. The design, methods and analysis used in the article represented a thorough approach to the subject. The conclusions are suitable, ... Continue reading READ ALL This title is appropriate for the content of the article and the abstract represents a suitable summary for the work. The design, methods and analysis used in the article represented a thorough approach to the subject. The conclusions are suitable, balanced and justified on the basis of the results of the study. The data represented allows enough information to replicate the experiment for further research. The data is usable with the structure that has been provided. Competing Interests: No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Colbert-Lewis DM. Reviewer Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10836 ) The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10836 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Jung Y. Reviewer Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10421 ) The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10421 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 16 Oct 2015 Youngim Jung , Korea Institute of Science and Technology Information, Daejeon, South Korea Approved VIEWS 0 https://doi.org/10.5256/f1000research.7610.r10421 This paper proposes a novel index based on the number of citations, normalized by the number of authors and the date of publication, which is then scaled from 0.0 to 9.9 using the natural logarithm. The index proposed is intuitively ... Continue reading READ ALL This paper proposes a novel index based on the number of citations, normalized by the number of authors and the date of publication, which is then scaled from 0.0 to 9.9 using the natural logarithm. The index proposed is intuitively designed in a simple way for readers to understand, with a fractional counting scheme adopted to normalize the number of citations, which appears reasonable. However, it will be necessary to adjust the index according to the relationship between the number of citations and the date of publication, since they are not precisely inversely proportional in every time window. Finally and fundamentally, whether the number of authors and the date of publication are truly indicative of publication quality remains open to speculation. Competing Interests: No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Jung Y. Reviewer Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10421 ) The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10421 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 22 Sep 2015 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 2 (revision) 02 Jun 25 Version 1 22 Sep 15 read read Youngim Jung , Korea Institute of Science and Technology Information, Daejeon, South Korea Danielle M. Colbert-Lewis , North Carolina Central University, Durham, USA Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2015 Colbert-Lewis D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 17 Nov 2015 | for Version 1 Danielle M. Colbert-Lewis , Department of James E. Shepard Memorial Library, North Carolina Central University, Durham, NC, USA 0 Views copyright © 2015 Colbert-Lewis D. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This title is appropriate for the content of the article and the abstract represents a suitable summary for the work. The design, methods and analysis used in the article represented a thorough approach to the subject. The conclusions are suitable, balanced and justified on the basis of the results of the study. The data represented allows enough information to replicate the experiment for further research. The data is usable with the structure that has been provided. Competing Interests No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Colbert-Lewis DM. Peer Review Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10836) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10836 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2015 Jung Y. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 16 Oct 2015 | for Version 1 Youngim Jung , Korea Institute of Science and Technology Information, Daejeon, South Korea 0 Views copyright © 2015 Jung Y. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This paper proposes a novel index based on the number of citations, normalized by the number of authors and the date of publication, which is then scaled from 0.0 to 9.9 using the natural logarithm. The index proposed is intuitively designed in a simple way for readers to understand, with a fractional counting scheme adopted to normalize the number of citations, which appears reasonable. However, it will be necessary to adjust the index according to the relationship between the number of citations and the date of publication, since they are not precisely inversely proportional in every time window. Finally and fundamentally, whether the number of authors and the date of publication are truly indicative of publication quality remains open to speculation. Competing Interests No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Jung Y. Peer Review Report For: A citation-based, author- and age-normalized, logarithmic index for evaluation of individual researchers independently of publication counts [version 2; peer review: 2 approved] . F1000Research 2025, 4 :884 ( https://doi.org/10.5256/f1000research.7610.r10421) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/4-884/v1#referee-response-10421 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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