Evidence map›Paper›PMID 41219334›Full record

ArticleScientific reports2025

Information entropy and relative entropy models for analyzing structural robustness in airway networks.

Keyan Zhao, Yanhua Li, Guangjian Ren, Zongqian Zhang

RetractedAbstract readRetracted Publication
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Keyan ZhaoSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China.
Yanhua LiSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China.
Guangjian RenSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China. zc416418@126.com.
Zongqian ZhangSchool of Traffic and Transportation, Beijing Jiaotong University, Beijing, 100044, China.

Funding

National Natural Science Foundation of China and the Civil Aviation Administration of China No. U2333206the Fundamental Research Funds for the Central Universities 2025JBWZDC002
6 · The paper itself

Abstract

As a critical foundation of air transportation, the airway network (AIN) plays an essential role in ensuring smooth flight operations. Analyzing and optimizing the structural characteristics of the AIN can help reduce flight delays and enhance the safety and reliability of air transport. In this paper, an order degree relative entropy (ODRE) model for the AIN is established based on information entropy theory. Simplified AIN models are constructed based on the actual Chinese AIN and its subnets in Beijing, Shanghai, and Guangzhou. Various attack strategies-random, degree, betweenness, closeness, eigenvector, and Bonacich centrality-are applied to the AINs. The ODRE is used to evaluate the comprehensive robustness of the AINs under these diverse attacks. Compared with traditional methods, the proposed ODRE in this paper significantly enhances the reliability and applicability of the system while maintaining consistency and stability in network efficiency. It enables a more precise assessment of AIN vulnerability under different attack scenarios and provides deeper insights into network structure and dynamics.

Indexed as

Airway networkOrder degreeRelative entropyRobustness

Identifiers

PMID41219334
PMCPMC12606160

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.