TEXTO & CONTEXTO ENFERMAGEM JOURNAL: A BIBLIOMETRIC STUDY
Bibliographic record
Abstract
ABSTRACT Objective: To analyze scientific production of Texto & Contexto Enfermagem journal available on Scopus. Method: This is a bibliometric study, with a search carried out in November 2024, using the ISSN “0104-0707”. Descriptive statistics were applied using the bibliometrix R software and the Biblioshiny application. Results: A total of 2,038 papers were indexed between 2009 and 2024, with a predominance of original articles (1,882; 92.3%) and 90 (4.4%) literature reviews. Brazil produced the largest number (1,864; 91.5%), followed by Portugal, Canada and the United States of America. The most frequent keywords were “Nursing”, “Nursing Care”, “Primary Health Care”, “Family” and “Patient Safety”. A total of 5,418 authors were identified, with an average of 4.5 per document and international co-authorship of 16.7%. Cite Score increased from 0.5 in 2011 to 1.8 in 2023. The most cited articles were theoretical-methodological, evidencing that methodological rigor is essential to drive scientific and technological progress. Conclusion: The growth and visibility of scientific production of Texto & Contexto Enfermagem journal, which comes from university institutions, at national and international level, was identified. There is a wide range of topics and the authors have formed international collaboration networks.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.082 | 0.136 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.013 | 0.007 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".