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Record W3136263789 · doi:10.53762/gqm7hk74

10.53762/gqm7hk74

2000· article· en· W3136263789 on OpenAlexvenueno aff
Abdul Hayee, Qari Taj Afser

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAnnotationComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This article investigates and annotates an Arabic Commentary of “Sūrah al-Aḥzāb” from a Tafsīr manuscript named “Ilhām al-Raḥmān” by ʻUbaidullāh al-Sindhī, a well-known scholar and a political activist of Indian independence movement. “Ilhām al-Raḥmān” was dictated by al-Sindhī to his disciples during his stay in Mecca. I have selected the referred manuscript for study and connotation as no work has been done on this scholarly effort yet. The study finds the relevant exegesis a distinctive interpretation of the Quran in terms of knowledgeable and scientific thought. It relates the issues of real life to the teaching of Quran and authentic prophetic traditions.interpretation, which still exist in the form of manuscript. It is a distinctive interpretation of other interpretations in terms of scientific thought and research, which relates the issues of real life to the teaching of Qur'an and authentic prophetic traditions. Due to importance of this intellectual work, I have selected this topic for my research to highlights the merits and demerits of this unique commentary.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.068
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.9320.940

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.

Opus teacher head0.012
GPT teacher head0.227
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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