Research Progress in Pediatric Lung Transplantation: A Bibliometric Analysis
Bibliographic record
Abstract
Pediatric lung transplantation is considered to be an effective treatment for end-stage lung disease in children, and this study mainly conducts a bibliometric analysis in the field of pediatric lung transplantation.We used the web of science databases to perform a bibliometric analysis of the progress of research in the field of pediatric lung transplantation from 1996 to 2024. In addition, we used VOSviewer software and the "bibliometrix" package in R to visualize and analyze the authors, countries, journals, institutions, and keywords of the literature.We identified 359 literature studies related to pediatric lung transplantation, which were cited 6,387 times by 1,400 journals. The journal with the highest number of average citations was the "New England Journal of Medicine," while the journals with the highest number of publications were the "Journal of Heart and Lung Transplantation and Pediatric Transplantation." The United States was the country with the highest number of publications (64.3%), followed by the United Kingdom (11.1%) and Canada (8.08%).Research in the field of pediatric lung transplantation is currently on the rise, while research is still dominated by developed countries, with most developing countries in their infancy. Against the background of COVID-19 and global health challenges, the unique need for pediatric lung transplantation is becoming a trend.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.033 | 0.129 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".