Issues of disagreement with Imam Al-Ashmouni in the endowment and initiation in his book Manar Al-Huda in the statement of endowment and initiation, a collection and study (The first quarter of Surat Al-Baqarah as a model)
Bibliographic record
Abstract
The research aims to study the issues of disagreement with Al-Ashmouni in endowment and initiation, in his book Manar Al-Huda, confined to the first quarter of Surat Al-Baqara, and one of the most prominent goals is to extrapolate the book of Al-Ashmouni, and to know the issues of disagreement that he mentioned, and to know Al-Ashmouni’s methodology in mentioning the issues of disagreement, and his choice for that. Among the most prominent results: the reader of Al-Ashmouni’s book finds that issues of disagreement are repeated in many places in the surah itself, due to scientific considerations such as language, syntax, and endowment. Among the recommendations that I recommend: Completing the study of the issues of disagreement with Al-Ashmouni, with a balance between Al-Ashmouni’s approach in his book and the methods of the scholars who preceded him in presenting the issues of disagreement, stating the sayings, and clarifying the differences and agreement.
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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 | 0.012 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.027 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".