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Record W1993146964 · doi:10.5539/jsd.v1n2p111

A Study on the Coupling Rules between Ecological Environment and Urban Competitiveness

2009· article· en· W1993146964 on OpenAlexvenueno aff
Tong Yang, Tao Zeng

Bibliographic record

VenueJournal of Sustainable Development · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsKuznets curveDissipative systemProcess (computing)Coupling (piping)EcologyDevelopment (topology)Economic geographyEconomicsComputer scienceMathematicsBiologyThermodynamics

Abstract

fetched live from OpenAlex

The relation between city and ecological environment forms in the coupling process of urban systems and environmental factors, in which there is a definite rule. Urban competitiveness embodies the evolvement and development of the city, using the dissipative structure principle and mathematical analysis, this paper probes into the coupling rule between urban competitiveness and ecological environment. It is indicated that the amicability degree of human environmental behavior determines the shape of environmental Kuznets curve, the human amicable behavior and technological progress are significant for coordinating the city development and improving the urban competitiveness.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.242
Teacher spread0.220 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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