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Conquering the Time: An Example of a Manual for Making an Astrolabe Quadrant: Muhammad Qunawı’s Hadiyyat al-muluk

2016· article· W7162122109 on OpenAlexaboutno aff
Taha Yasin Arslan

Bibliographic record

Venuenot available
Typearticle
Language
FieldPhysics and Astronomy
TopicHistorical Astronomy and Related Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAstrolabeAstronomerTurkishIslamQuarter (Canadian coin)Simple (philosophy)Front (military)

Abstract

fetched live from OpenAlex

Perhaps the most fruitful and valuable outcome of the advancements in astronomy that occurred in the Muslim world is the extraordinary development of instrumentation. With the application of trigonometry on a higher level and more accurate than ever before, Muslim astronomers developed new devices and techniques. One of these first-of-its-kind devices is the astrolabe quadrant, which is a simpler and easier-to-use version of the astrolabe. This instrument, albeit less accurate than the large-scale ones, is quite practical since it has all the mark- ings of an astrolabe’s front and rete, only inside a quarter of a circle. This small and portable device can be used by anyone who has a basic knowledge of astronomy and a simple user manual. It became popular specifically among those astronomers who worked on timekeeping. Although it is a very popular instrument, manuals for making it are quite rare. Muhammad ibn Kātib Sīnān al-Qunawī al-Muwaqqit (d. c. 1524), one of the most important Otto- man astronomers in this regard, wrote two treatises on how to make an astrolabe quadrant: Hadiyyat al-Mulūk and Risala fī ma‘rifat wad‘ al-rub‘ al-dāirat al-mawdu‘ ‘ala al-muqantarāt. Both of these treatises are the earliest manuals in Turkish for making this instrument. This article aims to introduce manuals for instrument-making via the ex- ample of Qunawī’s detailed explanatory remarks in his Hadiyyat al-Mulūk. It follows his instructions step by step and uses his tables. At the end of the article is an astrolabe quadrant drawn according to his instructions. For more comprehensive studies, the transliteration of the treatise is attached in the appendix.

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)0.002
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.032
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.005
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0320.014

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 head0.025
GPT teacher head0.270
Teacher spread0.245 · 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
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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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