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Record W2132615286 · doi:10.1080/00207540500046715

Production research in China

2005· article· en· W2132615286 on OpenAlexaff
Sohail S. Chaudhry, H. Li, Ling Li, Haoyue Sui, J. L. Zhang, Ze Zhang, Li Da Xu

Bibliographic record

VenueInternational Journal of Production Research · 2005
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChinaProduction (economics)Manufacturing engineeringEngineeringBusinessComputer scienceEconomicsPolitical scienceMicroeconomics

Abstract

fetched live from OpenAlex

(First paragraph) China is the world’s largest emerging economy. In recent years, China has moved to an increasingly market-oriented economy that opens to international trade and investment. At the same time, the popularity of China as a manufacturing base, assembling goods for sale worldwide is growing. In addition to global manufacturers who have built their own plants in China, many manufacturing companies are outsourcing production to Chinese subcontractors and branding the products with their own logos. In today’s China, production research is becoming more and more important; advanced production research becomes an important enabler to make its manufacturing industry competitive. Although China has different financial, legal, and physical infrastructure, production researchers in China have successfully proven that production research can help to manage global manufacturing competition.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.503
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0000.000

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 head0.121
GPT teacher head0.481
Teacher spread0.360 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations11
Published2005
Admission routes1
Has abstractyes

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