ArticleScientific reports2025
A study of dominant factors in the coupled coordination of population-ecology-energy-digital economy in China based on random forest algorithm.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study aims to examine the spatiotemporal patterns and dominant influencing factors of the coupling coordinated development (CCD) among population, ecology, energy, and digital economy (PEED) systems in China, contributing to the broader goal of sustainable regional development. Using panel data from 31 Chinese provinces over the period 2011-2020, we construct a PEED coordination index and analyze its evolution through coupling coordination models, spatial autocorrelation (Moran's I), the Geodetector model, and a Random Forest algorithm with SHAP analysis. Results show a steady improvement in the overall CCD across provinces, although significant regional disparities persist-eastern provinces such as Guangdong and Beijing lead in coordination, while western and northeastern regions lag behind. Among the four subsystems, the ecological subsystem shows the greatest spatial variation, while the digital economy subsystem is more homogeneous. The Nighttime Light Index, Urbanization Rate, and Green Coverage Rate are identified as the most important drivers, with the Nighttime Light Index consistently exhibiting the strongest influence on CCD. SHAP analysis reveals nonlinear effects of all drivers, highlighting the complexity of subsystem interactions. The findings provide policy-relevant insights for promoting balanced and sustainable development. Policymakers should focus on enhancing urban planning, ecological protection, renewable energy adoption, and digital infrastructure investment, especially in less-developed regions, to further strengthen PEED coordination and support the achievement of Sustainable Development Goals (SDGs).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.