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Record W4411397319 · doi:10.53762/ddmwc281

10.53762/ddmwc281

2000· article· en· W4411397319 on OpenAlexvenueno aff
Rubina Yasmin, Rabia Sarfraz, Sumaira Akbar

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic, Cultural, and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPlutoPoetryNeptuneAstronomyPlanetAstrobiologyLiteraturePhilosophyPhysicsArt

Abstract

fetched live from OpenAlex

“Charkh Bhi kia Ajab Ajooba hay” is a long poem written by Dr. Mirza Hasan Nasir. It is a long astronomical long poem about the Universe. Allah is the creator of the universe. All living and non-living beings are creature of Allah. We cannot reach the vastness of this universe. Do as much research on this universe as you can. We will come to the conclusion that only Allah knows the secrets of Allah. The poem mentions all the planets (Mercury, Venus, Earth, Mars, Mercury, Saturn, Uranus, Neptune, Pluto and the twinkling stars). Reading this poem reveals the greatness of Allah and His arguments in the Qur'an.

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)0.000
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 score0.039
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.9610.966

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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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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