Citation analysis of Muslim scholars of the Islamic Golden Age on the Web of Science
Bibliographic record
Abstract
The purpose of this study is to investigate the scientific impact of Muslim scholars of the Islamic Golden Age (750-1258 AD) through citation analysis of documents indexed in the Web of Science. For this purpose, after reviewing the related reference sources, 150 Muslim scholars of the Islamic Golden Age were selected for the study. To collect citation data for each scholar in the study population, the Cited Reference search option in WoS was used. Of the 150 Muslim scholars, 32 scholars did not receive any citations on the WoS. According to the research findings, Ibn Sina, with 3587 citations, was the most cited scholar among the Muslim scholars of the Islamic Golden Age. His book, entitled "Kitab al-shifa" (known as "Book of Healing"), with 1,599 citations, was the most cited work among the works of Islamic Golden Age Muslim scholars. Al-Ghazali, Ibn Rushd, and Al-Farabi were other highly cited scholars of the Islamic Golden Age on the WoS. Subject analysis of citing documents to the works of scholars of the Islamic Golden Age showed that the top 10 subject areas include religion, Asian studies, philosophy, history, humanities (multidisciplinary), medieval and Renaissance studies, history and philosophy of science, Archaeology, Pharmacology and Pharmacy, And Integrative and Complementary Medicine.Furthermore, the USA, the Islamic Republic of Iran, England, Turkey, France, Malaysia, Israel, Germany, Canada, and Spain are the top 10 countries citing the works of Muslim scholars of the Islamic Golden Age, respectively. Finally, English, French, Turkish, Spanish, German, Italian, Arabic, Malay, Russian, and Dutch were the top languages, citing the works of Islamic Golden Age Muslim scholars. The results showed that Muslim scholars of the Islamic Golden Age have had a broad and significant impact on the indexed documents of the WoS across various subjects. This research provides a core bibliography of the works of Muslim scholars of the Islamic Golden Age.
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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 | 0.005 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.064 | 0.101 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".