ArticlePNAS nexus2024
Emergent scale-free networks.
Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Measuring Safety Risks in Online Drug Sales: Empirical Study Based on Complex Network Theory.JMIR infodemiology · 2026Article
- Evolution and Vulnerability of the Global Ready-to-Eat Aquatic Products Trade Network: A Complex Network Analysis.Foods (Basel, Switzerland) · 2026Article
- Speech Recognition with an fMRISNN Constrained by Human Functional Brain Networks: A Study of Enhanced MFCC-Driven Sparse Spike Encoding.Biomimetics (Basel, Switzerland) · 2026Article
- Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks.Scientific reports · 2025Article
- Combined topological and spatial constraints are required to capture the structure of neural connectomes.Network neuroscience (Cambridge, Mass.) · 2025Article
- Heavy-tailed neuronal connectivity arises from Hebbian self-organization.Nature physics · 2024Article
- Circulation of a digital community currency.Scientific reports · 2023Article
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
Many complex systems-from the Internet to social, biological, and communication networks-are thought to exhibit scale-free structure. However, prevailing explanations require that networks grow over time, an assumption that fails in some real-world settings. Here, we explain how scale-free structure can emerge without growth through network self-organization. Beginning with an arbitrary network, we allow connections to detach from random nodes and then reconnect under a mixture of preferential and random attachment. While the numbers of nodes and edges remain fixed, the degree distribution evolves toward a power-law with an exponent
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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.