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Record W2799439296 · doi:10.5539/ass.v14n5p95

Study on Woolen Clothing and Pattern Unearthed in Zagunluk Cemetery in Qiemo County of Xinjiang

2018· article· en· W2799439296 on OpenAlexvenueno aff

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicFashion and Cultural Textiles
Canadian institutionsnot available
Fundersnot available
KeywordsClothingWeavingGeographyArchaeologyEngineering

Abstract

fetched live from OpenAlex

Located in the western border of the motherland, Xinjiang Uyghur Autonomous Region used to be the hub of the ancient Silk Road. Known as Western Regions, it has created splendid multi-ethnic cultures with distinctive geographical features. With its multiple archeological resources, there are many exquisite historic relics unearthed here, which shocked the world, with woolen fabrics as the most characteristic and the earliest fabrics. Zagunluk Cemetery witnessed sufficient unearthed fabrics in quantities and types. This paper focuses on woolen clothing and accessories and their patterns unearthed in Zagunluk Cemetery, Qiemo County, Xinjiang Uyghur Autonomous Region. Zagunluke woolen clothing and accessories reflect the circumstances of evolving weaving technologies in ancient Xinjiang. These woolen clothing and accessories were daily necessities of ancestors of Zagunluk, witnessing their material and cultural life. This paper analyzes about 20 typical woolen clothes and accessories, attempting to find out the characteristics of woolen fabric patterns and their formation background.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.286
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; 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 designObservational
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

Citations0
Published2018
Admission routes1
Has abstractyes

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