The Impact of Chinese Seals on the Structure, Design, and Usage of the Īl-Khānids Seals and Coins
Bibliographic record
Abstract
Il-Khanid seals and coins are a type of seal featuring figurative patterns typically characterized by the Rectangular style of Kufic script, the absence of figures, extensive use of calligraphy, geometric, and abstract patterns. Although it is based on the Persian seal-carving tradition, the Īl-Khānids seals and coins exhibit various elements from the Chinese seals (印章), and also similar in their style to the Mongolian writing systems. While the Silk Road, the central path for trade and economic purposes, brought together China and Persia, the two nations had strong influences regarding culture, tradition, and religion, and Persian art has applied many Chinese artistic elements, particularly in the art of seal making. Indeed, the historical evidence suggests that the Mongolian Empire employed the Chinese seals (印章) throughout their territory, stretching from China to Persia. The intercultural influences through the Silk Road seem to be well-rooted in Central Asia, and for the first time, Chinese culture is seen abundantly in the Īl-Khānids seal history, as well as the Rectangular style of Kufic script on the seals and coins, influenced by the Uighur script. This paper uses an interdisciplinary approach to analyse the Chinese and the Īl-Khānids seals and coins to survey transmission of the Chinese tradition through Silk Road cultural exchanges. The results show that there exists a strong possibility that the manner in which the writing of Arabic characters in the Rectangular Kufic writing system was inserted at the top to the bottom unexpectedly followed the style of Mongolian words.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".