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Record W2945745015 · doi:10.33195/uochjull-v1iii332018

ڈاکٹر داؤد رہبر بحیثیت شاعر: ایک تعارف

2017· article· en· W2945745015 on OpenAlexaboutno aff
Nosheen Safdar

Bibliographic record

VenueUniversity of Chitral Journal of Urdu Language & Literature · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitics and Conflicts in Afghanistan, Pakistan, and Middle East
Canadian institutionsnot available
FundersHigher Education Commission, Pakistan
KeywordsUrduPoetryHindiLiteratureDrummerDictionPersianCivilizationArabicMusicologyArtBengaliHistoryClassicsTheologyPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Daud Rahber (1926 - 5 October 2013) was a scholar of comparative religions, Arabic, Persian, Urdu literature and Indian classical music. Rahber is regarded as accomplished essayist, poet, composer, translator, philosopher, contributer to Inter civilization dialogue, musicologist, drummer, singer and guitarist. In 1949, he left Pakistan for Cambridge University where he got his Ph.D. He served as a teacher at reputable Universities in Canada and Turkey. His love for poetry and music can never be subsided. In 1968, he became a member of the faculty of Boston University where he taught comparative religions for 23 years. He retired in 1991 and settled in Florida. In rich tradition of Urdu poetry, Daud Rahber's comprehensive 'kulliyat' and 'Baqiyat' show an amazing breadth of content. His diction includes words from Hindi, Arabic, Persian and Urdu, all assimilated into flawless, rhythmic phrases. He is sensitive to the human conditions and always sees the infinite in the infinitesimal. His poetry is a colourful canvas portraying all around him.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0560.040

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 head0.009
GPT teacher head0.276
Teacher spread0.267 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

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