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Record W3094313113

A meditação como área de conhecimento: estudo cientométrico

2020· article· pt· W3094313113 on OpenAlexaboutno aff
Jane Rodrigues Guirado

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2020
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesWeb of scienceScopusPhilosophyPolitical scienceMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

This study aims to analyze the insertion of the theme Meditation in the core of scientific journals in the medical field to identify the most productive countries in research results and their communication in medical scientific journals from 2009 to 2018, indexed in the Web of Science and SCOPUS databases. The motivation for selecting the meditation theme was because this theme has grown and has been presented as one of the most widely used Complementary Therapies worldwide. The choice of the cited bases was due to its multidisciplinary coverage and to index high impact journals.The time frame of 10 was adopted because it makes possible to assess the evolution of this theme in recent years. The theoretical foundation covers authors and concepts of scientific communication, metric studies and the field of Complementary Therapies. This is a descriptive, Scientometric study with a quantitative approach. Data analysis and systematization tools were: Web of Science – Main Collection and SCOPUS (databases), Journal Citation Reports and SCImago Journal & Country Rank; Periodical Portal CAPES, Excel program and Wordsift tool. The follow categories were analyzed: Scientific production by country; Nucleus of journals from the five countries; Co-authorship network; Theme representativeness / Keywords; and Scientific production X Citation.In the Scientific production by country, the ranking of leading countries in the research related to the topic under study was identified: in the Web of Science database (1st position: United States; 2nd position: England; 3rd position: Australia; 4th position: Canada; and 5th position: India); in the SCOPUS base (1st position: United States; 2nd position: United Kingdom; 3rd position: India; 4th position: Australia; and 5th position: Canada). In the Core category of journals, it was identified that most of the journals' titles are of high impact and come from countries in North America and Europe, in both bases. It was also identified that the journals are classified in several categories in the medical field.In the Representativeness of the theme / Keywords it was noticed that the keywords cited in the articles by the author and by the databases refer to the most varied medical specialties. With regard to Co-authorship, the United States was the country that stood out as the largest partner of the four countries in the two databases, except with Australia (SCOPUS). Most of these partnerships took place between universities in the five countries, in both databases. In most studies, multiple authorship occurred in the five countries. Scientific Production X Citation showed that the Elite of producers from the five countries under study, on both bases, is formed by a small group of researchers. This group corresponds to one or at most two authors who published between 26 and 70 articles on the topic. The Front of research showed that the big producers have published their studies, mostly in English and in journals indexed in the two bases. It is understood that this study may contribute to the knowledge of important dimensions of the studies carried out by five leading countries on this subject.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.292
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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