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Record W2795263742 · doi:10.5539/jpl.v11n2p6

Qozloq Route (Astrabad to Shahrud) Impact on Economic Developments of the Region (Safavid Course)

2018· article· en· W2795263742 on OpenAlexvenueno aff
Mustafa Nadim, Ghorbanali Zahedi

Bibliographic record

VenueJournal of Politics and Law · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBelt and Road Initiative
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityDynamismContext (archaeology)Course (navigation)EconomyGeographyBusinessEconomic geographyRegional scienceEconomicsEngineeringEconomic growthArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

The Qozloq Route was one of the branches of the famous Silk Road in the northeast of Iran, which linked two important and strategic regions of Shahrud and Astrabad. This road constituted rough and smooth paths and was the passage of different nations with different goals. In this context, various cultures have also been published and exchanged in line with the trade of various goods.The presence of different caravansaries around the road indicates its importance and prosperity in the Safavid course, but with all of this, there is little information available on the importance of this route in the existing travel books and historical books. Despite all the inadequacies, in this research, with the descriptive-analytical approach based on the research data, it is concluded that the Qozloq Route has been of great importance in the Safavid course, strategically, and in term of the publication of the culture and prosperity of the economy, and the dynamism of development and awareness.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.001

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 head0.037
GPT teacher head0.275
Teacher spread0.238 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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