Bibliographic record
Abstract
Commentary of the collection of prophetic traditions has been very revered work in the science of ḥadīth. Every collection included in the most celebrated six corpses of ḥadīth has several commentaries in different languages. An important work from the commentaries of one of these collections named “Sunan al-Nisāʻī” is “Al-Tālīqāt al-Salafia” penned by an Indo-Pakistani scholar Atāullah Ḥanīf Bhūjiānī. This article studies Bhūjiānī’s mythology in the referred work. It gives a comprehensive account of his understandings of narrators of ḥadīth, Jarh wa al-Taʻdīl, Mukhtalif al-Ḥadīth etc. It explores that the commentator, in general, very nicely deal with the relevant discussions but his work has number of flaws regarding the study of traditions in the contemporary context. To make the work most beneficial in the present scenario it may be revisited.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.978 | 0.976 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".