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Record W4387220951 · doi:10.5539/ass.v19n5p18

Types of Organizations and Their Scope of Cooperation in Textile Research Awarded by the National Science and Technology Awards in the Past 40 Years

2023· article· en· W4387220951 on OpenAlexvenueno aff
Ninghui Zhang, Xiaoming Yang

Bibliographic record

VenueAsian Social Science · 2023
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Technologies in Various Fields
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)TextileChinaTextile industryPolitical scienceManagementEngineering ethicsEngineeringEconomicsGeographyLawComputer science

Abstract

fetched live from OpenAlex

The National Science and Technology Award is the highest award in the field of science and technology in the People's Republic of China, which was formally established in 1978 after China's reform and opening up, and it has been forty years since then. The textile award-winning research in the National Science and Technology Award is one of the important characterizations of the progress of textile science and technology and the development of the textile industry. Through the statistical analysis of the research organizations of the textile award-winning research of the National Science and Technology Award from 1979 to 2020, it is found that enterprises have been the most dominant type in the past forty years; research institutes were the important force of textile science and technology research before 2000, but their influence gradually declined after 2000; the scientific research strength of the universities has risen and the scientific research resources are concentrated in the main universities with textile specialties; different types of research organizations have their cooperation methods, and the forty years have experienced the transformation from the intra-city to the intra-country cooperation, among which, the enterprises have the highest degree of freedom on the space of cooperation.

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)0.009
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0080.008
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.023
GPT teacher head0.336
Teacher spread0.314 · 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.

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
Published2023
Admission routes1
Has abstractyes

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