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Record W3110037402 · doi:10.36231/coedw/vol30no3.11

Zanjan , Name and Origin: A Glimpse of Its History

2019· article· en· W3110037402 on OpenAlexaboutno aff
Tha'air Salman Faisal, Shakir Mahmoud Ahmed

Bibliographic record

VenueJournal of College of Education for Women · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsQuarter (Canadian coin)Period (music)IslamOrder (exchange)JudaismHistoryGeographyFront (military)Ancient historyEconomyEconomic historyPolitical scienceArchaeologyLawBusinessArt

Abstract

fetched live from OpenAlex

The aim of study is to shed light on an Islamic city which is unknown for a lot of people, it can have an old history in Parisian country and many events happen with it , This city is characterized with political, military, economic scientific ,and social features, This city is called Zanjan and it is one of the most important cities because it dates back to the period of post history and it has a good geographic location whereas it was, passage for trade caravans to pass through as well its land which was specialized in agriculture and industry. the study follows chronological order of historical events for the city, one of the most significant conclusions is to think that this city does belong to artifacts and it is an old city and it has an old history,this city was founded by the king Ardsheer Babkan and he was a big Sasanian king, a lot of different religions like old Parisian zaradishat, Christianity, and Jewish. The study tries to uncover nature of developments and political events which the city witnessed where it was front for different political powers in order to take control over Abbasid succession, As for geographical location, it can have big impact on different dimensions since the city is located in the fourth region (Aljabal region),I,e. it is located in the first quarter of Islamic East in road of trade caravans which links Alarie and Atharbeijan region and this made it as the biggest Centre for the trade for different commodities , people of this city were very interested in different sciences and this could attract attention of a lot people to visit there and get benefit from scientific treasures .

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0050.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.247
Teacher spread0.222 · 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
Published2019
Admission routes1
Has abstractyes

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