dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2021)  that was used in this study. Therefore, to extend these studies, we performed a bibliometric analysis based on the enhanced version of the GASEMT database  (Borrelli et al. , 2021). The main goal of this paper was to investigate how soil erosion modelling study characteristics (i. e. , study scale, mathematical model used, validation/calibration etc. ) and related bibliometric characteristics (number of co-authors, country of affiliation, book chapter vs. journal paper, etc. ) influence the impact of a given publication measured by the number of citations. Moreover, potential bibliometric networks (i. e. , journals, countries) that are part of the constructed database were also analysed. Specifically, we evaluated the following questions: a) How is the number and geographic origin of the authors and the publication's CiteScore related to the number of citations? b) Which mathematical models are widely applied and used as a reference when cited in the literature, and how do the other modelling framework characteristics affect the impact of the publication as measured by the number of citations? c) How can a study of citation patterns and clusters help recognize interrelated countries and determine who the leading countries and leading journals are that publish research results in the soil erosion modelling field?.
Methods Bibliometric analyses require extensive datasets that contain sufficient number of records and period covered. To gain a better understanding of the global application of soil erosion prediction models, a group of more than 60 soil erosion scientists from more than 20 countries all around the world comprehensively reviewed relevant peerreviewed research literature on soil erosion prediction modelling in the 1994-2018 period  (Borrelli et al. , 2021). As a result, the 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)' database was created  (Borrelli et al. , 2021). Additional information about the constructed database and results of the study can be found in  Borrelli et al. (2021). GASEMT database is available to users as part of the publication  (Borrelli et al. , 2021).
GASEMT database enhancement In this study, the analysis of the GASEMT database was enhanced by investigating the relationship between soil erosion modelling and bibliometric characteristics. For this purpose, for the 1697 publication entries (3030 modelling records) that are included in the GASEMT database, the number of citations from the Scopus database was added. The number of citations indicates the citation status in September when they were downloaded. Additionally, the Scopus CiteScore was added to the database for all sources with a CiteScore in 2018; CiteScore 2018 = Citations 2017 + Citations 2016 + Citations 2015 Publications 2017 + Publications 2016 + Publications 2015 , (1) where "citations" and "publications" mean the number of citations and citable items published in a specific year, respectively.
Additionally, the number of authors of each publication was also added to the database. Moreover, for each document type (i. e. , journal, conference proceeding or book series), the main (i. e. , listed first) sub-subject area from the Scopus database was extracted. This, information was semiautomatically extracted from the Scopus database based on matching paper titles in the GASEMT and Scopus. The GASEMT database includes studies published between 1994 and 2018. To account for the impact of the different number of years from the publishing date, the decision was made to use the normalized number of citations, which was calculated for each publication as:.
Normalized citations= Total number of citations Number of years from the year when study was published. (2) Therefore, we have added the following attributes to GASEMT: CiteScore 2018 , total number of citations, number of authors, normalized citations, document type and the main Scopus sub-subject area. The enhanced GASEMT database including the bibliographic data is available in the European Soil Data Centre (ESDAC;  Panagos et al. , 2012).
The BRT modelling was conducted using the 'gmb' package  (Greenwell et al. , 2019)  in the statistical software R (R Core Team, 2017). In our case, the target variable was the normalized number of citations, which was calculated using Eq. (  2 ). The following variables were used as an input for the BRT model: number of authors, publication's CiteScore in 2018, publication type, Scopus sub-subject category, and from the GASEMT database: -erosion agent (e. g. , water, wind, water and wind, etc. ), -name of the soil erosion model used, modelled period (e. g. , present, past, future), -time resolution (e. g. , daily, monthly, annually), -continent of model application, -modelled area (e. g. , forest, arable land), -scale of the study (e. g. , plot, hillslope, catchment), -type of field soil sampling, model calibration and model validation.
Bibliometric networks To analyse the bibliometric networks, the VOSviewer software was used  (Van Eck et al. , 2010; van Eck and Waltman, 2010; VOSviewer, 2019; Waltman et al. , 2010). VOSviewer is a freely available software that can be used for visualizing bibliometric networks that include journals, individual publications, authors affiliations, etc. (VOSviewer, 2019). To visualize bibliometric networks, part of the GASEMT database, which also appears in the Clarivate Analytics Web of Science database (i. e. , the overlap between Scopus and Web of Science was approx. 70%) was used. Moreover,  Schillaci et al. (2018)  also found approximately 60% agreement between Scopus and the Web of Science as a result of the systematic search. The reason for selecting part of the GASEMT database was to take into consideration only more eminent publications since Scopus also covers journals that are not indexed in Web of Science and other document types such as conference proceedings.
Results and discussion Using the enhanced GASEMT database and the methodology described in section 2, the impact of different variables on the total and the normalized number of citations was investigated. In section 3. 1, the differences among different document types, the Scopus sub-subject categories, and the relationship between the number of authors and the publication's (i. e. , source) CiteScore is discussed. In the section 3. 2, the relative impact of the different variables on the normalized number of citations is estimated using the BRT model. In section 3. 3, a detailed evaluation of the most cited papers is performed and in the last section various characteristics of the bibliometric networks are visualized and discussed (section 3. 4).
Publication type, journal selection and number of author's impact It is evident that most (i. e. 89%) of the soil erosion modelling papers that are included in the Scopus database were published in peerreviewed journals (Table  1 ). Moreover, journal publications also receive, on average, a considerably larger number of citations than book series and conference proceedings (Table  1 ). Accordingly, the average normalized number of citations for journal publications, book series and conference proceedings is 2. 78, 0. 42 and 0. 22, respectively. The mean number of citations of the journal articles was 5. 4-fold that of book series and 11. 2-fold that of conference proceedings and similarly, but slightly more pronounced was the variation for the normalized citations (6. 6-fold and 12. 6-fold, respectively).
Furthermore, Scopus also relates journals with primary Scopus sub-subject categories. Fig. 1  shows Scopus sub-subject categories where more than 50 publications (per category) were found in the database. There are ten categories and most of the papers were published in the "Water Science and Technology" (e. g. , Journal of Hydrology, Hydrological Processes) and "Earth-Surface Processes" categories (e. g. , CATENA, Geomorphology). These two categories had approximately 200 publications each, the "Geography, Planning and Development" category had approximately 130 publications and the remaining categories had from 50 to 90 papers each. Fig. 1  also shows the relationship between the mean number of normalized citations per publication and the mean CiteScore in 2018 of the category where the mean was calculated considering CiteScores for all journals in a specific category.
This observation is partly due to the higher visibility of a published paper in a more focused journal than in a general one. Researchers that publish their papers in SOIL journal focus on other aspects of soil erosion and not purely on modelling. Thus, such papers are not included in the GASEMT since the focus of the database is on the modelling  (Borrelli et al. , 2021)  (i. e. this journal has less than 10 entries in the database). It is also true that the average CiteScores for these categories are relatively similar and range between 1. 2 and 1. 8. Similarly, Mikoš (2017) performed a comparison between the top 20 journals in 2016 from the SCI-expanded category "Engineering, geological" and their ranking in the CiteScore metrics in the category "Geotechnical Engineering and Engineering Geology".
For the majority of scientific disciplines, the citability of publications increases with the number of co-authors (e. g. ,  Abramo and D'Angelo, 2015). Therefore, the relationship between the number of publication authors and the normalized number of citations according to the Scopus database was investigated (Fig. 3 ). In general, studies on soil erosion modelling are typically conducted in groups of 2-6 co-authors (Fig. 3 ). Moreover, only a few papers were co-authored by more than ten researchers (Fig. 3 ). It seems that in the soil erosion modelling field, a large number of authors does not necessarily guarantee a large number of citations, and no clear relationship between the number of authors and citations per year could be found (Fig. 3 ). More specifically, the mean normalized number of citations per number of authors gradually increases from one to eight co-authors and then decreases again in case that only studies with 1-12 co-authors were taken into account (there are only few studies with more than 12 co-authors).
The maximum number of mean normalized citations was found in publications with co-authors (i. e. on average such publication received 4. 6 citations per year). While much smaller values can be seen for publications with one or two authors: 1. 4 and 1. 9, respectively. Furthermore, the 7 highly cited publications with more than 30 citations per year had between 2 and authors (i. e. ,  Borrelli et al. , 2017; Cerdan et al. , 2010; Fu et al. , 2011; Panagos et al. , 2015; Quinton et al. , 2010; Syvitski and Milliman, 2007; Van Oost et al. , 2007). All other publications included in the database received less than 20 normalized citations per year (Fig. 3 ). Moreover, for the 30 most cited studies in GASEMT the number of authors range from 2 to 19 with a mean of 5. 7. All single-authored articles have less than ten normalized citations per year (Fig.
3 ). In addition, 8. 5% of the papers included in the GASEMT database  (Borrelli et al. , 2021)  have not yet received any citation. This value is close to the value report by Van Noorden (2017) that showed that approximately 10% of all published papers are uncited. Moreover,  Ioannidis et al. (2019)  and Van Noorden and Singh Chawla (2019) pointed out that the median self-citation rate in their global database was approximately 12. 7%. According to the GASEMT and the Web of Science (WoS) database, 12% of the citations were attributed to self-citations, which corresponds well to the median self-citation rate of 12. 7%  (Ioannidis et al. (2019) ; Van Noorden and Singh Chawla (  2019 )). Therefore, both the non-citing papers and the self-citations of soil erosion modelling studies are close to the overall statistics of all papers published in the WoS.
Confounding factors for the number of citations in soil erosion modelling The impact of different variables included in the enhanced GASEMT database  (Borrelli et al. , 2021)  on the normalized number of citations was also studied. For this purpose, the boosted regression trees (BRT) model was applied. The variables that were included in the BRT model are listed in section 2. Quite surprisingly, the soil erosion model selection clearly has the largest relative impact on the normalized number of citations. Model selection is followed by the soil erosion modelling scale, publication's CiteScore, Scopus sub-subject category, continent and number of authors (Table  2 ). Other considered variables have, according to the results of the BRT model, no significant impact on the normalized number of citations (Table  2 ).
Soil erosion model It is evident that the largest maximum number of citations include studies with RUSLE, WaTEM/SEDEM and USLE applications. However, Fig. 2. Relationship between publication name CiteScore for the year 2018 and total and normalized number of citations for GASEMT database entries including best-fit linear regression functions models. Fig. 3. Relationship between the number of authors and total and normalized number of citations for soil erosion modelling GASEMT database entries.
Moreover, the maximum number of normalized citations for the RUSLE and USLE models is also high. Therefore, many studies apply these models, but in many cases these studies are not very well cited. Therefore, the mean normalized number of citations is lower as in case of some other models. Additionally,  Borrelli et al. (2021)  concluded that the number of RUSLE model applications is increasing. The same also applies for the total number of studies in the GASEMT database as the number of soil erosion model studies in the post-2010 is increasing. It should also be noted that some of the highest erosion rated were predicted by the RUSLE and USLE models  (Borrelli et al. , 2021). Additionally, the median erosion rates predicted by these two models are also larger than for some other model (e.
, 2021). Therefore, the calculated erosion rate obviously does not have a direct impact on the normalized number of citations. It should also be noted that the GASEMT database  (Borrelli et al. , 2021)  only included publications that were written in English. Thus, the actual number of soil erosion studies focusing on Asia is probably even higher (i. e. publications written in Chinese language). Quite interestingly, studies that focused on a regional and national scale do not, on average, receive more citations than studies that focused on a specific watershed or even those with a plot or hillslope scale (Table  5 ). It should be noted that the percentage of database records could impact the mean normalized number of citations in cases when these percentages are low.
Other variables with negligible impact according to the BRT model Several other variables were also used as an input to the BRT model, but according to the model results, these variables do not have an impact on the normalized number of citations (Table  2 ). It is evident that papers focused on tillage and harvest erosion, on average, have slightly more citations than studies focused on water or wind erosion (Table  6 ). Multiple examples of highly cited papers focused on these two erosion agents can be found  (De Alba et al. , 2004; Quinton et al. , 2010; Verstraeten et al. , 2002). However, it is also true that tillage and harvest erosion are only investigated in less than 2% of the publications included in the database, and this limits the information that is needed to establish efficient management factors in agriculture, that preserve soil, yield and profit at the same time.
e. , 241 in 1990, 2655 in 2000, 11,630 in 2010 and 33,814 in 2018). A similar trend can also be found with the search "future projections" in the Web of Science. However, in the field of soil erosion modelling, focusing on future projections is obviously something that does not yield, on average, more citations than focusing on the past or present (Table  7 ). Surprisingly, additional field activity or soil sampling does not have a significant impact on the mean number of normalized citations of publications included in the database according to the BRT model (Fig. 4 ). Although, the mean normalized number of citations is about 15% higher in case that soil sampling activities were conducted. As discussed by  Borrelli et al. (2021)  in-situ soil erosion measurements are the most common field activity related to modelling.
This of course also applies to all other environmental models (e. g. ,  Beven and Young, 2013). However,  since model validation is terminology still used in the field, this was included in the global review and statistical analysis performed by  Borrelli et al. (2021). One could argue that model validation does not have a significant impact on the mean number of normalized citations (Fig. 4 ). Moreover, validation is performed in about half of the studies included in the GASEMT database  (Borrelli et al. , 2021). Plot-scale studies show higher level of validation (evaluation) and calibration  (Borrelli et al. , 2021). Therefore, the focus should always be on model validation and in-depth discussion of the results, as the incorrect use of model parameters can also lead to incorrect conclusions.
Most cited papers The 20 most cited papers (i. e. top 1%) included in the database were analysed in more detail  (Bakker et al. , 2008; Benavides-Solorio and MacDonald, 2001; Betrie et al. , 2011; Borrelli et al. , 2017; Cerdan et al. , 2010; Fu et al. , 2011; Ganasri and Ramesh, 2016; Gessesse et al. , 2015; Haregeweyn et al. , 2017; Leh et al. , 2013; Panagos et al. , 2015; Parras-Alcántara et al. , 2016; Prasannakumar et al. , 2012; Quinton et al. , 2010; Syvitski and Milliman, 2007; Van Oost et al, 2000 , 2007; Van Rompaey et al. , 2005; Viglizzo et al. , 2011; Yang et al. , 2003). The threshold for the 1% top cited paper in the soil erosion modelling is normalized citation. The most cited papers were selected based on the normalized number of citations. These papers were published in an almost 20-year time window.
Hot papers, by definition, are papers that have been published in the past two years that received enough citations in May/June 2019 to put them in the top 0. 1% of papers in each of the 22 academic fields. On the other hand, highly cited papers received enough citations as of May/June 2019 to be in the top 1% of the specific academic field based on the field threshold and publication year. Moreover, it should also be noted that there are some differences in these thresholds for different fields  (Mikoš, 2017). Borrelli et al. (2017)  is defined as hot paper by the above definition. Moreover, there are five highly cited papers included in the list of the 20 most cited papers in the soil erosion GASEMT database  (Borrelli et al. , 2021). These are  Borrelli et al. (2017) ,  Panagos et al. (2015) ,  Cerdan et al.
(2010) ,  Fu et al. (2011)  and  Quinton et al. (2010)  in the Environment/Ecology, Environment/Ecology, Geosciences, Environment/Ecology and Geosciences fields, respectively. Moreover,  Wang et al. (2012)  is a highly cited paper in the field of Agricultural Sciences, and according to the soil erosion modelling database is in the top 30 most cited papers based on the normalized number of citations. This indicates that papers focusing on soil erosion modelling are among the most highly cited and top papers in these fields, which shows the relevance of this topic for the wider scientific community (e. g. agriculture, ecology, geosciences).
Investigation of the relationship among papers about soil erosion modelling (VOS viewer) Additionally, bibliometric networks using the methodology described in section 2. 3 were analysed. The next two sub-sections present bibliometric networks from the perspective of journals and "Yes" means that specific step was done, "No" means that this step was not carried out and "Unknown" means that it was not possible to determine if the step was done or not based on the information provided in the article. countries. As mentioned in section 2. 3, only part of the database that is included in the Web of Science database was used as an input for the VOS Viewer software.
Journals A citation analysis of the journals that are included in the soil erosion modelling GASEMT database indicates the relatedness of journals based on the number of times that they cite each other  (Fig. 5; VOSviewer, 2019). It is evident that six different clusters have been identified (i. e. , indicated by different colours in Fig. 5 ). Quite surprisingly, CATENA, where most of the papers included in the database are published, is on the edge of the central soil erosion cluster and more towards Climatic Change and Agricultural and Forest Meteorology. This observation confirms assumptions made in the section 3. 3 that soil erosion modelling papers are also cited in other fields since these two journals are not among the 23 journals mentioned in section 3. 1. Furthermore, at the same time this also means that articles published in CATENA often cite papers published by these two journals.
Countries Bibliographic coupling of countries with more than 12 documents in the database was investigated for their relatedness of shared references (Fig. 8 ). It is evident that three clusters have been identified, whereas one of the clusters only includes two members (i. e. , Japan and Ethiopia). Quite interestingly, all European countries, except Turkey, which is partly in Europe and partly in Asia, are clustered together. This means that authors from Europe usually cite similar references, and these are at least to some extent different than the ones that authors from other countries are citing. Moreover, some regional European patterns can also be seen (i. e. , position of the countries in the plot). For example, Italy and Greece or Belgium and the Netherlands are located close together.
Conclusions We evaluated 3030 model applications published in 1697 articles included in the GASEMT database  (Borrelli et al. , 2021)  in a rigorous bibliometric investigation. This study can be used as a metric benchmark for future erosion modelling studies as potential authors can measure the impact of their paper comparing with the proposed metrics here. However, it should be noted that the results presented in the scope of this paper should not be regarded as a guideline to prepare a highly-cited paper or to propose specific journals, models or other practices related to soil erosion modelling. These should be selected based on the aims of the study. The largest percentage of studies (i. e. around 13% per category) were published in the Scopus categories "Earth-Surface Processes" and "Water Science and Technology" and these papers have, on average, higher number of normalized citations (i.
3 of USLE and 2. 8 of WEPP). However, WaTEM/SEDEM is applied only to the 4. 7% of the studies in GASEMT database compared to 17. 1% of RUSLE, 13. 9% of USLE and 6. 4% of WEPP. The insights emerging from our investigation suggested that studies using more empirically based (e. g. , USLE) and more physically based models (e. g. , WEPP) are not citing each other and use different references. Furthermore, the WaTEM/SEDEM model is clustered into a different group than the remaining most frequently used soil erosion models. Regarding the scale, papers evaluating the global scale generally receive considerably more citations than papers focused on a continental, national, or smaller scale. However, we also observed that national scale studies, on average, do not receive more citations compared to local or watershed ones.