Impact and Citation Trends of Surveys Endorsed by the EUPSA Network Office in Pediatric Surgery: A Bibliometric Analysis
Bibliographic record
Abstract
Abstract The European Pediatric Surgeons' Association (EUPSA) Network Office regularly endorses surveys that address controversial topics in pediatric surgery. However, the scientific impact of these within the medical literature remains unclear. To address this gap, we conducted a bibliometric analysis of all published EUPSA-endorsed surveys. Surveys endorsed by the EUPSA Network Office were reviewed for topic, journal, participation, bibliometric indicators (total number of citations and citations per article and year), and citing countries. Simple linear regression was used to determine citation time trends. Between 2013 and 2024, at least one survey was published each year (R 2 = 0.26; p = 0.1). Most commonly, surveys were published in the European Journal of Pediatric Surgery (n = 15), and the most common survey topics included general pediatric (n = 7), thoracic (n = 4), and colorectal (n = 3) surgery. The average number of participants per survey was 167 ± 53, with 75% (range: 54–89%) European responses. The most cited surveys addressed esophageal atresia, necrotizing enterocolitis, and Hirschsprung's Disease. The median number of citations per survey was 11 (range: 1–160), with a median of 6 citations per year (range: 0–26). The total number of citations from all EUPSA Network Office-endorsed surveys increased over time (R 2 = 0.75; p = 0.0006), and the average citation per article and year was consistent (R 2 = 0.09; p = 0.34). Citations originated from 63 countries, mostly from the United States (n = 75), Germany (n = 64), and China (n = 44). Despite inherent limitations of survey-based research, the growing bibliometric impact of EUPSA Network Office-endorsed surveys highlights their scientific merit as an important tool for exploring current pediatric surgical practices, which will inform future multi-institutional studies.
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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 | BibliometricsMetaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | medium |
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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.075 | 0.182 |
| 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, 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".