Global Trends and Collaborations in Dengue Virus Research: A Scientometric and Bibliometric Overview (1872–2019)
Bibliographic record
Abstract
Dengue virus, a paramount public health concern, prompts ample global research.This paper provides a comprehensive overview of global efforts in dengue research, applying bibliometric and scientometric procedures to examine the breadth and depth of this field.Drawing data from the Web of Science (WoS) and Scopus databases, 18,607 publications from 1872 to 2019 were meticulously analyzed using advanced tools such as Mendeley, Biblioshiny, and VoS-viewer for systematic visualization and examination.This research not only charts the trajectory of publication growth but also employs the AutoRegressive Integrated Moving Average (ARIMA) model to predict future trends.A focal point of the study is the geographical distribution of research, highlighting key activity regions.Besides, the collaborative networks amongst researchers, institutions, and countries are investigated in detail, showing noteworthy contributions from entities such as Mahidol University, the University of Malaya, and the National University of Singapore, with publications totaling 1,070, 505, and 443.The analysis further demonstrates that the mean citation count for the top 15 articles stands at 1,213, illustrating the high impact of these contributions.An essential finding is the prevalence of multi-authorship, with approximately one-fifth of the articles containing nine or more authors.The research highlights the strong interconnection between authors and institutions, reflected in coauthorship patterns.This comprehensive overview provides a valuable resource for researchers, offering insights into the evolution and current state of global dengue virus research and serving as a basis for future investigations.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.095 | 0.174 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".