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Record W3082532411

Análise cientométrica sobre a produção científica em meditação nos periódicos da Medicina

2020· article· en· W3082532411 on OpenAlexaboutno aff
Jane Rodrigues Guirado, Marlene Oliveira, Rubens Lene Carvalho Tavares

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2020
Typearticle
Languageen
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsnot available
Fundersnot available
KeywordsScopusHumanitiesWeb of sciencePolitical scienceLibrary sciencePhilosophyMEDLINEComputer science
DOInot available

Abstract

fetched live from OpenAlex

The general objective of this study was to analyze the insertion of the theme Meditation at the core in scientific journals of the medical area, referring to the six countries (United States, United Kingdom, (SCOPUS) and England (Web of Science); India, Australia and Canada) that lead the ranking of that scientific production is indexed in the Web of Science and SCOPUS 
\ndatabases. This is a scientometric study, descriptive, with a quantitative approach, in the period from 2009 to 2018.The search analyzed the core in scientific journals with regard to the impact, origin, the subject category and the identification of the 15 titles that most published about the theme. The result of the research showed that the core consists of journals classified in different subjects in the medical field, in both databases. The specialties they highlighted were: Neurology (Web of Science) and Psychiatry, (SCOPUS). In reference to the impact, it was found that the majority of the titles are high impact and from countries in North America and Europe. This study can contribute to reveal patterns of behavior through metric studies, concerning to the formal channel used by that scientifical community to publish your search results.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0010.002
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 head0.040
GPT teacher head0.278
Teacher spread0.238 · 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; a candidate call from one teacher head, not a consensus.

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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Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicHealthcare during COVID-19 PandemicFrench-language works237,207