Evidence map›Paper›PMID 27560938›Full record

ArticlePloS one2016

Topology Universality and Dissimilarity in a Class of Scale-Free Networks.

Lanhua Zhang, Juan Chen, Mei Wang, Yujuan Li, Shaowei Xue, Yiyuan Tang, Baoliang Sun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Lanhua ZhangCollege of Information and Engineering, Taishan Medical University, Taian 271016, China.
Juan ChenCollege of Information and Engineering, Taishan Medical University, Taian 271016, China.
Mei WangCollege of Information and Engineering, Taishan Medical University, Taian 271016, China.
Yujuan LiCollege of Information and Engineering, Taishan Medical University, Taian 271016, China.
Shaowei XueCenter for Cognition and Brain Disorders, Department of Psychology, Hangzhou Normal University, Hangzhou 310036, China.
Yiyuan TangDepartment of Psychological Sciences, Texas Tech University, TX 79409, United States of America.
Baoliang SunKey Lab of Cerebral Microcirculation in Universities of Shandong, Taishan Medical University, Taian 271016, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We study the effect of subtle changes on the evolution in the scale-free (SF) networks. Three extended models are evolved based on competition and inner anti-preferential deletion in growth and preferential attachment processes. By nonlinear and dynamic controlling on randomness and determinacy, three models can self-organize into scale-free networks, and diverse scaling exponents appear. Moreover, the model with more determinacy has more stringent parameter control than randomness, especially in the edge deletion. Our results suggest that the nature of the topology universality and dissimilarity in SF networks may be the subtle changes of randomness and determinacy.

Indexed as

Biological EvolutionComputer SimulationModels, BiologicalAlgorithmsStochastic Processes

Identifiers

PMID27560938
PMCPMC4999222

What OpenQuestion holds

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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.