Quṭb al-Dīn al-Shīrāzī’s Commentary on Ibn Sīnā’s Qānūn in Historical Context: Edition and Translation of the Preface
Bibliographic record
Abstract
Abstract Ibn Sīnā’s al-Qānūn fī l-ṭibb, especially its first book, al-Kulliyyāt, elicited dozens of commentaries from the 6th/12th century through the 8th/14th century. Among them, Quṭb al-Dīn al-Shīrāzī’s commentary, entitled al-Tuḥfa al-saʿdiyya, is distinguished in that in it he analyzed and synthesized almost all commentaries written before his death in 710/1311. This article shows how Shīrāzī bridged some of the political boundaries that divided the Islamic world after the Mongol invasion to gather his predecessors’ commentaries, as well as other sources for composing al-Tuḥfa al-saʿdiyya. Shīrāzī’s extensive travels and proximity to patronage allowed him to acquire, and later disseminate, medical and scientific texts that were otherwise unavailable in Anatolia and the eastern territories of the Islamic world.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".