Similes in Parts Twenty-Ninth and Thirty of the Holy Quran
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to analyze the Quranic similes in Parts Twenty-ninth and Thirty of the Holy Quran as they contain 48 Surah from a total of 114 Surah, with a percentage of 42%. They are Makkan Surah except for four of them (Surah Al-Insan, Surah Al-Bayyina, Surah Al-Zalzala, Surah An-Nasr(. The study consists of two topics; the first one addressed the theoretical aspects of the term, the importance of simile and its role in clarifying the intended meaning. The second topic addressed the applied aspects by collecting, studying, analyzing, and examining the close linguistic meanings of similes, up to demonstrating their beauty and comparing them with other similes in other places in Quran. For this purpose, the researchers used the two tools of textual approach; description and analysis as the approach used in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.164 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it