Bibliographic record
Abstract
Thematic exegesis at the beginning of the chapters of Bihar al-Anwar is a matter that researchers and authors have commented on it and they know him as the beginner of thematic exegesis.He briefly used this method of exegesis (Sobhani, 1981: Vol.1, p.2). Research on the validity of this view can be performed in three parts of gathering chapters, sub-chapters, examining the viewpoints of exegetes and analysis and conclusion according to the definition of thematic exegesis.This study aimed to study the thematic approach of Majlesi to the Quran which is the introduction and entrance basis to thematic exegesis.For this purpose, the number of chapters were randomly and proportionally selected from each subject package of Bihar al-Anwar and then examined.Totally, proportion included about 100 chapters with their titles.According to the results, on the one hand, coverage and diversity of the subjects of Bihar al-Anwar are proved and on the other hand, it is proved that each chapter includes all related verses.Also, the order and coherence of Majlesi's method at the entrance to the exegesis of verses becomes clear.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.971 | 0.965 |
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".