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Record W2888668179 · doi:10.5539/ijef.v10n9p89

A Coupling Coordination Degree Research of Civil-Military Industrial Integration in Regional Economic Development Based on Industrial Cluster Perspective--Taking Aerospace Manufacturing of Shaanxi as an Example

2018· article· en· W2888668179 on OpenAlexvenueno aff
Chongyi Zhang

Bibliographic record

VenueInternational Journal of Economics and Finance · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economic and Spatial Analysis
Canadian institutionsnot available
FundersNanjing UniversityNanjing University of Aeronautics and Astronautics
KeywordsAerospacePerspective (graphical)Cluster (spacecraft)Coupling (piping)ManufacturingEconomic geographyEmpirical researchBusinessIndustrial organizationBusiness clusterRegional scienceManufacturing engineeringComputer scienceEngineeringEconomicsAerospace engineeringMechanical engineeringMechanism (biology)MarketingGeography

Abstract

fetched live from OpenAlex

Based on the principle of coupled cooperation, the article identifies indicators from the perspective of industrial clusters, uses the principal component analysis to extract the effective coupling indicators of military-and-civilian integration industry and regional economic development and builds a model for the coupling coordination between the two. Taking the aerospace manufacturing industry in Shaanxi Province as an example, the article finds that the coupling degree between the aerospace manufacturing industry in Shaanxi Province and the regional economy has been increasing year by year, gradually shifting from disordered development to orderly evolution. Finally, based on empirical conclusions, relevant recommendations are given.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0000.002
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 head0.210
GPT teacher head0.314
Teacher spread0.104 · 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 designSimulation or modeling
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

Citations1
Published2018
Admission routes1
Has abstractyes

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