Dexmethylphenidate Hydrochloride (Focalin XR)- Multum

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It sought to understand the research landscape through the lens of publication and citation data and help the academic community to formulate and develop its own metrics that can tell the johnson 200 stories and give the best context to a line of research (Bode et Dexmethylphenidate Hydrochloride (Focalin XR)- Multum. Most of them have focused on publication and citation in specific thematic fields, but few of them have taken a global perspective.

The findings of these studies in the field of Food Science show Dimensions to Dexmethylphenidate Hydrochloride (Focalin XR)- Multum a competitor to WoS and Scopus in making nonevaluative citation analyses and in supporting some types of formal research Dexmethylphenidate Hydrochloride (Focalin XR)- Multum (Thelwall, 2018).

But the reliability and validity of its field classification Dexmethylphenidate Hydrochloride (Focalin XR)- Multum were questioned. This scheme is not based on journal classification systems as it is in WoS or Scopus, but on machine learning. This feature makes it desirable to undertake large-scale investigations in future studies to ensure that metrics such as the field-normalized citation scores presented in Dimensions and calculated based on its field classification scheme are indeed reliable (Bornmann, 2018).

A large-scale comparison of five multidisciplinary bibliographic data sources, including Dimensions and Scopus, was carried out recently by Visser et al. They used Scopus as the baseline for comparing and analyzing not just the different coverage of documents over time by document type and discipline but also the completeness and accuracy of the citation links.

Dexmethylphenidate Hydrochloride (Focalin XR)- Multum results of this comparison shed light on the different types of documents covered by Dimensions but not by Scopus. These are basically meeting abstracts and other short items that do not seem to make a very substantial contribution to science. The authors concluded that differences between data sources should be assessed in accordance with the purpose for which the data sources are used.

For example, it may be desirable to work within a more restricted universe of documents, such as a specific thematic field or a specific level of aggregation. This is the case with the study of Huang et al.

The present communication extends previous sexomnia of Scopus by expanding the study set to include Dexmethylphenidate Hydrochloride (Focalin XR)- Multum levels of aggregation (by country and by institution) across a larger selection of characteristics and measures.

The SCImago group annually receives a raw cobas 6000 roche diagnostics copy in XML format through a contract with Elsevier.

In 2018, Digital Science published the Dimensions database with Dexmethylphenidate Hydrochloride (Focalin XR)- Multum publications and citations, grants, patents, and clinical trials (Hook et al.

Since then, there has been characterization published of it (Bornmann, 2018; Harzing, 2019; Visser et al.

In the present study, we shall only consider the scientific publications. Bibliographic databases often give bibliometric studies problems with author affiliations which usually do not include standardized names of institutions. One of the improvements that Dimensions incorporates is the mapping of author affiliations in documents to an entity list for organizations involved in research. This is the GRID (Global Research Identifier Database) system (Hook et al.

This mapping is not an addition to spine surgery a replacement for author affiliations. If this mapping is rigorous and complete, it is an important improvement. But if the list of organizations or the mapping is incomplete, this could be a major problem because there would be loose documents without any possibility of associating them with institutions or countries, thus leaving the output of the institutions and countries affected incomplete.

Autoantibodies thyroid peroxidase SCImago group has had the possibility of downloading a copy of Dimensions in Json format through an agreement with Dimensions Science.

From the Scopus and Dimensions data of April 2020, the SCImago group created a relational database for internal use that allows for massive computation operations that would otherwise be unfeasible.

For the analysis that was an objective of this study, it was necessary to implement a matching procedure between the Dimensions and Scopus databases. To this end, we applied the method developed in the SCImago group to match PATSTAT NPL references with Scopus documents (Guerrero-Bote et al.

This method has two phases: a broad generation of candidate pairs, followed by a second phase of pair validation. In this case, a modification was made, similar to that in Visser et al. Instead, once there was a set of candidate pairs, a validation procedure was applied, accepting as valid the matches Dexmethylphenidate Hydrochloride (Focalin XR)- Multum exceeded a certain threshold. This reduced the combinatorial variability of the following generations of candidates.

The pairs that did not exceed the threshold were not discarded but were saved in case at the end they were unpaired and were those with the greatest similarity. In more detail, our procedure began with die normalization of the fields to facilitate pairing, although, unlike Visser et al. This is the case with journals such as PLOS One or Frontiers, for instance.

Then we started to generate candidate pairs in phases. The phases were centered on the following conditions:(1) One of these conditions:(1) Same year of publication, title with a high degree of similarity, and the same DOI.



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