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Record W4404512138 · doi:10.5539/ass.v20n6p1

Silk and Silkworm: (Re)discussion on the Origin and Early History of Using Silk Fibres

2024· article· en· W4404512138 on OpenAlexvenueno aff
Xiyao Zhang, Xiaoming Yang

Bibliographic record

VenueAsian Social Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSilkworms and Sericulture Research
Canadian institutionsnot available
Fundersnot available
KeywordsSILKPolymer scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Discussions on the origin of silk utilisation usually focus on the origin of discovering filaments, ignoring the existence and availability of short fibres. Among these studies, some arguments with evidence of silkworms have inserted a preconception that silkworm rearing is certainly related to silk utilisation, ignoring the possibility that human ancestors might have reared silkworms for other reasons before they knew how to use silk fibres. Considering the difficulties in obtaining raw materials, the complexity of the production processes, and archaeological evidence for the early use of silk, it seems probable that silk was utilised first in the form of short fibres and these fibres were processed with the spinning technique. By analysing the relationship between silk reeling and weaving, silk reeling was invented to answer the growing demands of the weaving industry. By analysing the relationship between silk utilisation and silkworm rearing, silkworm domestication was motivated and prompted by the growing demand from silk reeling workshops. Silk reeling appeared after the birth of weaving and before the activity of rearing silkworms. Combined with the scientific study results of the silkworm taming and domestication time, silk fibres were discovered and used before 7000 BP.

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)0.001
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.007
Scholarly communication0.0020.005
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.289
Teacher spread0.241 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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