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Record W2790812908 · doi:10.5539/ass.v14n3p63

Research on the Public Cognitive Differences of Healthcare Functions of Silk Fabrics for Garment: Based on Research Data from Hangzhou, China

2018· article· en· W2790812908 on OpenAlexvenueno aff
Aijuan Cao, Qi Zhu, Lanlan Yan

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
FundersDonghua University
KeywordsSILKChinaCognitionHealth careResidenceFunction (biology)QuestionnairePsychologyPreferenceBusinessMarketingEngineeringSociologyEconomic growthGeographyEconomicsSocial scienceMathematicsDemographyPsychiatryStatistics

Abstract

fetched live from OpenAlex

Silk fabrics own a number of excellent qualities, while the public cognition status of on property regarding silk fabrics of the garment is unclear. In this paper, three indicators based on healthcare function as breakthrough point such as anti-mite, anti-bacteria and anti-allergy, healthy and environmentally friendly function, andskin-care function, were used to analyze the status of the public cognition on healthcare function of silk fabrics through questionnaire investigation and statistical analysis based on surveys conducted from the public of Hangzhou, China as core respondents. The result shows that the public owns high cognition on the healthy and environmentally friendly function of silk fabrics of the garment. Factors such as personal preference, purchase and use experience, whether the silk industry practitioners are of a significant impact on healthcare cognition, while gender, age, and years of residence in Hangzhou are of no significant impact.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.662
GPT teacher head0.477
Teacher spread0.186 · 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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