ArticleScientific reports2019
The heterogeneity in link weights may decrease the robustness of real-world complex weighted networks.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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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.
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Who cites it
15 citing papers in PubMed, 64 citations in OpenAlex.
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- Dynamic Robustness of Open-Source Project Knowledge Collaborative Network Based on Opinion Leader Identification.Entropy (Basel, Switzerland) · 2021Article
- Adaptive Rewiring in Weighted Networks Shows Specificity, Robustness, and Flexibility.Frontiers in systems neuroscience · 2021Article
- Modelling photosystem I as a complex interacting network.Journal of the Royal Society, Interface · 2020Article
- Nonlinear model of cascade failure in weighted complex networks considering overloaded edges.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Here we report a comprehensive analysis of the robustness of seven high-quality real-world complex weighted networks to errors and attacks toward nodes and links. We use measures of the network damage conceived for a binary (e.g. largest connected cluster LCC, and binary efficiency Eff
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.