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Science and medicine in Iran/Central Asia 600–1500

2021· other· en· W3205097126 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Encyclopedia of Ancient History · 2021
Typeother
Languageen
FieldArts and Humanities
TopicHistory of Medicine Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAncient historyQuarter (Canadian coin)IslamCentral asiaHistoryClassicsThe RenaissanceEmpireTraditional medicineArchaeologyArt historyMedicine

Abstract

fetched live from OpenAlex

Khurasan and Central Asia, which formed the eastern part of the Islamic Empire, were the region from which most scholars came to the new capital Baghdad in the second half of the eighth century and realized the renaissance of the ancient sciences. Throughout the period under consideration, the most important mathematicians, astronomers, astrologers, physicians, and pharmacologists came from this region and were attracted by the gradually emerging centers of power. The best known are al‐Khwarazmi (d. ca. 850), Abu Mashar (ca. 886), known as Albumasar, al‐Farghani (d. 861), al‐Farabi (d. 950), al‐Razi (d. 925), known as Rhazes, Ali ibn al‐Abbas al‐Majusi (d. last quarter of the tenth century), known as Hali Abbas, Ibn Sina (d. 1037), known as Avicenna, al‐Biruni (d. ca. 1048), Nasir al‐Din al‐Tusi (d. 1274), and Ulugh Beg (r. 1447–9). Less well known but very influential were Habash al‐Hasib (d. ca. 864), Abu Jafar al‐Khazin (d. 971), Abu Nasr Ibn Iraq (ca. 1036), and many others. The most important centers that attracted scholars were Merv, Bukhara, Ghazna, Hamadan, Maragha, and Samarqand.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.109
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.009
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.000

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 head0.032
GPT teacher head0.234
Teacher spread0.203 · 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