Clinical Neuroscience Research in Saudi Arabia: A Comparative Evaluation of Performance at Country and Worldwide Levels Based on the Relative Specialization Index
Bibliographic record
Abstract
This review is an appraisal of the performance of clinical neuroscience research in Saudi Arabia based on the measurement of the Relative Specialization Index (RSI). The latter is an established quantitative performance indicator that determines whether a country has a relatively higher or lower share in world publications in a specialty than its overall part in the world total publications. The study aimed to assess the trends in the specialty’s RSI, comparing it to other medical specialties in Saudi Arabia and to that of the top 50 countries worldwide in clinical neuroscience. SCImago Journal and Country Rank were used to determine the total articles and total citations for 46 medical specialties in Saudi Arabia and clinical neuroscience in the worldwide top 50 countries during 1996‑ 2023. The RSI was calculated for each medical specialty and each country. A positive or negative RSI implied that the specialty’s share in the country’s total documents or total citations was higher or lower than the average for the specialty worldwide. A steady increase in Saudi Arabia’s total articles and total citations in clinical neuroscience was observed over the last 28 years. The RSI values, however, remained negative throughout except for limited periods (2003-2006 for total articles) and (1996 and 1998 for total citations). Compared to other medical specialties in Saudi Arabia, the specialization performance for clinical neuroscience was within the mid-range in total articles (ranking 30th out of 46 specialties) and the low range in total citations (ranking 39th out of 46 specialties). Saudi Arabia’s worldwide ranking in clinical neuroscience based on total citations was 39; however, the country’s ranking dropped to 45 when the RSI values were applied. Furthermore, clinical neuroscience was considered to have had a strong relative contribution (RSI ≥ 0.1) to the total articles in five countries (Italy, Austria, Germany, Japan, and Canada) and total citations in six countries (Luxembourg, Austria, Germany, Canada, Italy, and Finland). In conclusion, despite an increase in Saudi Arabia’s total articles and total citations in clinical neuroscience over the years, the specialty’s relative share of the total productivity in the country remains lower than the overall for the specialty worldwide. The performance of the specialty was within the mid-to-low range compared to the other 45 medical specialties in Saudi Arabia. In addition, the country's worldwide ranking based on total citations in the specialty dropped when the RSI was used. Clinical neuroscience researchers in Saudi Arabia are encouraged to improve the quality and quantity of their research productivity to be one of the leading medical specialties in Saudi Arabia.
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How this classification was reachedexpand
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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".