Mapping the Iranian Research Literature in the Field of Traditional Medicine in Scopus Database 2010-2014.
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.
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to provide research and collaboration overview of Iranian research efforts in the field of traditional medicine during 2010-2014. METHODS: This is a bibliometric study using the Scopus database as data source, using search affiliation address relevant to traditional medicine and Iran as the search strategy. Subject and geographical overlay maps were also applied to visualize the network activities of the Iranian authors. Highly cited articles (citations >10) were further explored to highlight the impact of research domains more specifically. RESULTS: About 3,683 articles were published by Iranian authors in Scopus database. The compound annual growth rate of Iranian publications was 0.14% during 2010-2014. Tehran University of Medical Sciences (932 articles), Shiraz University of Medical Sciences (404 articles) and Tabriz Islamic Medical University (391 articles), were the leading institutions in the field of traditional medicine. Medicinal plants (72%), digestive system's disease (21%), basics of traditional medicine (13%), mental disorders (8%) were the major research topics. United States (7%), Netherlands (3%), and Canada (2.6%) were the most important collaborators of Iranian authors. CONCLUSION: Iranian research efforts in the field of traditional medicine have been increased slightly over the last years. Yet, joint multi-disciplinary collaborations are needed to cover inadequately described areas of traditional medicine in the country.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it