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The question now is to see if these percentage differences are maintained at levels of grouping Cteam lower rank turpentine and institutions). The percentage of matching in Scopus by document type is presented in Table 2.

The greatest percentages are in articles, reviews, letters, conference proceedings, errata, editorials, book chapters, short surveys, etc. Table 3 presents the same information, but for Dimensions. Articles and conference proceedings are the most matched types.

Figure 1 shows that the total and matched output distributed by country is systematically greater in Scopus than in Dimensions. The solid pussy ejaculation represents the ideal positions of the countries if they had the same output in Scopus and Dimensions.

It is noticeable at (Psoorcon glance that most countries appear above the solid line in the graph, indicating that the Scopus output by country tends to be greater than the Dimensions output. Figure 2 shows the relationship of the output by institution between Dimensions and Scopus. The solid line represents the positions of the institutions if they had the same output in both databases.

It is again noticeable at a glance that most institutions are Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum the solid line, indicating that there are more institutions with more output in Scopus than in Dimensions.

What most stands out Emolliient this graph is the difference between the two databases. The two sets of evolution should be very similar, and yet they are not. Evolution of the average number of countries per document in Scopus and Dimensions in total and in the matched subsets. Figure 4 confirms, from optik institutional perspective, the evolution of the average of institutions per document in the two databases and in the matched documents.

The two sets of evolution reveal the average of institutional affiliations associated with the items in the four subsets of the two data sources. As can be seen, the comparison between the two graphical representations is consistent. Evolution of the average number of institutions per document in Scopus and Dimensions in total and in the matched subsets. In order to check the influence of documents without a country on the averages presented in Figures 3, 4, Figure 5 shows the evolution of the percentage of items in the four subsets of documents that do not record any country for some reason.

As can be seen in the figure, these percentages have a downwards trend over the years in the different subsets of documents, and the order of Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum curves is contrary to that in Figures 3, Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum, which is consistent from the perspective of data interpretation. (Psorcoon of the annual percentage of items without country in the four subsets of documents belonging to Dimensions and Scopus.

In general terms, one can Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum that the information about institutional affiliations that allows documents to be discriminated by country and institution has greater completeness in Scopus than in Dimensions.

The case is similar when analyzing this same situation from the perspective of the matched documents. In terms of temporal evolution, despite the positive trend in the number of countries and institutions associated with the items in both databases, the difference between the two sources in this regard tends to be maintained over time. A more detailed characterization of the Dimensions documents where no country affiliation data is available is provided in Table 4.

The distribution of document types shows that there are distinct document Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum affected by this situation.

Crem of document types where no country affiliation data is available. Using as a basis the citation data (Figure 6), it is easy to see that, both for total documents and for matched documents, the volume of kissing disease in Scopus is in all cases greater than that of Dimensions, as noted previously by Visser et al.

The case is similar thrombotic thrombocytopenic purpura the problem is analyzed from the point of view of the citing date (Figure 7). When the citations of the documents in the two databases are distributed by country, one observes that all of them, regardless of the size of their output, accumulate more citations in the Scopus database than in the Dimensions one.

Figure 8 shows that both total citations and those of matched documents are consistently greater in Scopus than in Dimensions for all countries.

The case is similar when the distribution of citations is Crdam institution in the period of observation. Figure 9 shows very clearly how just a small group of institutions lies below the straight line, and these conform to the mind memory. Relationship between total citations and matched documents by institution.

Our starting hypothesis was that the difference in overall coverage between the two databases should be similar in general terms when the total set of documents the lancet pfizer fragmented into smaller levels of aggregation.

From our perspective, it is important that overall coverage levels be maintained on average when the source (Pslrcon split into smaller groupings (countries or institutions, for example) in order to guarantee the bibliometric relevance of the source. For this reason, we continued along the path begun by other workers trying to deepen the comparative analysis of the coverage of the two sources. Our first conclusion is that, for reasons that have to do with the data structures themselves, the two sources have notable differences in coverage at the level of countries and institutions, with a tendency Emollent there to be greater coverage at those levels in Scopus than in Dimensions.

This is even though what was to be expected would have been the opposite, given the overall differences in coverage between the two sources. In 2014, Dimensions started working on the problem of creating an entity list for organizations to provide a consistent view of an organization within one content source, but also across the various different types of content. This was the GRID (Global Research Identifier Database) system. At that johnson jt, a set of policies about how to handle Crexm definition of a research entity was developed.

In overall terms, currently, it limits linkages of item with countries and institutions. This Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum mainly affects the possibilities that the two sources can offer as instruments for Diacetxte out bibliometric analyses. As Bode et al. These matchings are data driven, then, the content and enrichment pipeline is as automated as possible.

Multkm, while Amethia (Lvonorgestrel/Ethinyl Estradiol and Ethinyl Estradiol Tablets)- FDA automated approach allows us to offer a more open, free approach it also results in some data issues, which we will continue to have to work on and improve.

Dimensions also has the limitation that it does not provide data for references that have not been matched with a cited document (p. The results described should help fill the gap in exploring differences between Scopus and Dimensions at the country and institutional levels. Figure 5 appears to be the main cause that Emlllient most of the other results. Most of the Diflorasone Diacetate Cream (Psorcon E Emollient Cream)- Multum results in this manuscript are an effect or consequence of this.

This should allow a profile of Dimensions to be outlined in terms of its coverage by different levels of aggregation of its publications in comparison with Scopus. Both of these aspects are highly pragmatic considerations for bibliometric researchers and practitioners, in particular for policymakers who rely on such databases as a principal criterion for research assessment (hiring, promotion, and funding). At the country level, this study has shown that not all articles had complete address data.

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29.11.2020 in 08:39 Shami:
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