Bibliometric profile of neurogenic bladder in the literature: a 20-year bibliometric analysis
Why this work is in the frame
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Bibliographic record
Abstract
Neurogenic bladder is a dysfunction of the lower urinary tract caused by nervous system disorder. We investigated the trends in publication of articles under the topic "neurogenic bladder" using bibliometric analysis. Articles on neurogenic bladder, published between 1995 and 2014, were retrieved from the ISI Web of Science citation database. We analyzed the search results for authors, countries, institutions, journals, and top-cited papers. A total of 1,904 articles were retrieved. There was a small increase in the number of articles on neurogenic bladder from 1995 (n = 43) to 2014 (n = 117). The USA was the leading country in the total number of articles (n = 598). However, the number of publications from China has rapidly increased, and China was ranked second in 2014. Emmanuel Chartier-Kastler (n = 65) was the most productive author, and University of Paris VI (Paris 6) (n = 61) was the most productive institution. The Journal of Urology published the greatest number of articles on this topic (n = 285). Articles on neurogenic bladder were often published in a professional journal under the category Urology & Nephrology, Neurosciences & Neurology, or Rehabilitation. Visualization analysis based on co-citation networks was conducted using CiteSpace III. Visualization analysis revealed that the hot spots in neurogenic bladder were botulinum toxin-A, prazosin, bethanechol, and afferent pathways. These findings provide new insight into the publication trends and hot spots in neurogenic bladder.
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.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.541 | 0.868 |
| 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