Jules Janssens. « Mulla Sadra’s Use of Ibn Sina’s Ta‘liqat in the Asfar ». Journal of Islamic Studies 13, 1 (2002), pp. 1-13.
Bibliographic record
Abstract
In this article, Jules Janssens sheds further light on the extent to which late medieval Perso-Islamic philosophers like Mulla Sadra adhered to Avicennian principles and models in their own work. Not surprisingly, Mulla Sadra cites well-known works by Ibn Sina (such as al-Shifa’ and al-Najat), but Janssens draws us to the fact that the Asfar (more formally known as al-hikmat al-muta‘aliyya fi l-Asfar al-‘aqliyyat al-arba‘a) on occasion makes periodic references and allusions to yet another Av...
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".