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Record W7120776663

Scientometrics analysis on scientific production about meditation in medical journals

2020· article· pt· W7120776663 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2020
Typearticle
Languagept
FieldComputer Science
TopicScientific Research and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsScientometricsScopusMeditationBibliometricsSubject (documents)Web of scienceRanking (information retrieval)Identification (biology)Theme (computing)Scientific literature
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 databases. 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.

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)0.008
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.040
Science and technology studies0.0010.000
Scholarly communication0.0030.002
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 head0.054
GPT teacher head0.312
Teacher spread0.258 · 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