The Pattern of Publications on Cerebral Arteriovenous Malformations and Cavernomas in the Middle East and North Africa
Bibliographic record
Abstract
Background: Cerebrovascular malformations are encountered frequently in clinical practice, but not much is known about the pattern of publication in the Middle East and North Africa (MENA) countries. We aim to evaluate the status and pattern of publications of cerebral arteriovenous malformations (AVM) and cavernomas in the MENA. Materials and Methods: PubMed database was searched for publications on cerebral AVM and cavernomas in the MENA between 2009 and 2019. Results: We found only 94 publications in the MENA region out of 31,333 publications pertaining to AVMs (0.3%). The highest publishing country was Turkey, with 50 (53.1%) studies. The case report was the study design used most by authors with 59 (62.7%) studies. The majority of publications were by neurosurgeons with 42 of 94 (42.4%) papers. European journals ranked first in the number of published articles with 42 of 94 (46.1%) articles. Conclusions: We found a limited number of publications on cerebral AVMs and cavernomas by MENA countries in the past decade. Research support and national/regional registries are important factors to improve the academic output on AVMs and cavernomas in the MENA region.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, not a consensus.
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".