Bibliographic record
Abstract
Fawā'id al-Fuwād is a renowned book written by Nizamuddīn Auwliya. The book offers a collection of valuable insights and teachings from Nizāmuddīn Auwliyā, a renowned medieval Sufi saint of the Chishtī order in India. This book contains valuable insights into the spiritual journey of a Sufi and highlights the virtues, wisdom, and guidance necessary for achieving true love and devotion to God. It is believed that Hazrat Nizāmuddīn Auwliyā wrote this book to convey his message to his followers who were unable to meet him in person. The book is considered a masterpiece of Sufi literature and has been translated into several languages. Through Fawā'id al-Fuwād, readers gain a deeper understanding of Sufism and its teachings, making it a valuable resource for those pursuing the path of spirituality. This is an analytical study to explore the methodology style of Fawā'id al-Fuwād and its contemporary importance. For this purpose, data is gathered from secondary sources; books, articles and online sources. The study reveals that Fawā'id al-Fuwād is the first book of al-Malfūzāt that was first compiled in book form. Its position is also high in the sense that it contains the most Hadiths with text. The book is a source and source book of spiritual teachings. This book not only emphasized on worship but also enlightened people's hearts with Islamic teachings. It Encourages people to have a good character through the morals of the Prophet (PBUH) in Fawā'id al-Fuwād.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.979 | 0.979 |
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".