Digital Hadith authentication: Recent advances, open challenges, and future directions
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
Abstract The Holy Quran and Hadith are the two main sources of legislation and guidelines for Muslims to shape their lives. The daily activities, sayings, and deeds of the Holy Prophet Muhammad (PBUH) are called Hadiths. Hadiths are the optimal practical descriptions of the Holy Quran. Technological advancements of information and communication technologies (ICT) have revolutionized every field of daily life, including digitizing the Holy Quran and Hadith. Available online contents of Hadith are obtained from different sources. Thus, alterations and fabrications of fake Hadiths are feasible. Authentication of these online available Hadith contents is a complex and challenging task and a crucial area of study in Islam. Few Hadith authentication techniques and systems are proposed in the literature. In this study, we have surveyed all techniques and systems, which are proposed for Hadith authentication. Furthermore, classification, open challenges, and future research directions related to Hadith authentication are identified.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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