Evidence map›Paper›PMID 36437299›Full record

ArticleScientific reports2022

Through history to growth dynamics: deciphering the evolution of spatial networks.

Stanisław Żukowski, Piotr Morawiecki, Hansjörg Seybold, Piotr Szymczak

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 48% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. TheProceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  2. Breakthrough-induced loop formation in evolving transport networks.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
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

4 authors at 4 institutions in 4 countries.

Stanisław ŻukowskiInstitute of Theoretical Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland.ORCID 0000-0001-6319-3995
Piotr MorawieckiDepartment of Mathematical Sciences, University of Bath, Bath, UK.ORCID 0000-0002-7136-7980
Hansjörg SeyboldDepartment of Environmental System Science, ETH Zürich, Zürich, Switzerland.ORCID 0000-0002-3793-1904
Piotr SzymczakInstitute of Theoretical Physics, Faculty of Physics, University of Warsaw, Warsaw, Poland. piotr.szymczak@fuw.edu.pl.ORCID 0000-0001-8940-7891
Centre National de la Recherche Scientifique · FRETH Zurich · CHUniversity of Bath · GBUniversity of Warsaw · PL

Funding

National Science Center, Poland 2016/21/B/ST3/01373
6 · The paper itself

Abstract

Many ramified, network-like patterns in nature, such as river networks or blood vessels, form as a result of unstable growth of moving boundaries in an external diffusive field. Here, we pose the inverse problem for the network growth-can the growth dynamics be inferred from the analysis of the final pattern? We show that by evolving the network backward in time one can not only reconstruct the growth rules but also get an insight into the conditions under which branch splitting occurs. Determining the growth rules from a single snapshot in time is particularly important for growth processes so slow that they cannot be directly observed, such as growth of river networks and deltas or cave passages. We apply this approach to analyze the growth of a real river network in Vermont, USA. We determine its growth rule and argue that branch splitting events are triggered by an increase in the tip growth velocity.

Indexed as

RiversDiffusion

Identifiers

PMID36437299
PMCPMC9701698
OpenAlexW4310273908

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.