Evidence map›Paper›PMID 39967681›Full record

ArticlePNAS nexus2025

Classification and spatiotemporal correlation of dominant fluctuations in complex dynamical systems.

Cristina Caruso, Martina Crippa, Annalisa Cardellini, Matteo Cioni, Mattia Perrone, Massimo Delle Piane, Giovanni M Pavan

Abstract read
In one paragraph

Article in PNAS nexus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Cristina CarusoDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0002-1372-2374
Martina CrippaDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0002-6682-0015
Annalisa CardelliniDepartment of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Polo Universitario Lugano, Campus Est, Via la Santa 1, Lugano-Viganello 6962, Switzerland.ORCID https://orcid.org/0000-0002-6359-6118
Matteo CioniDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0003-4391-2096
Mattia PerroneDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0003-3903-1616
Massimo Delle PianeDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0001-8522-9047
Giovanni M PavanDepartment of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy.ORCID https://orcid.org/0000-0002-3473-8471

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The behaviors of many complex systems, from nanostructured materials to animal colonies, are governed by local events/rearrangements that, while involving a restricted number of interacting units, may generate collective cascade phenomena. Tracking such local events and understanding their emergence and propagation in the system is often challenging. Common strategies consist, for example, in monitoring over time parameters (descriptors) that are designed ad hoc to analyze certain systems. However, such approaches typically require prior knowledge of the system's physics and are poorly transferable. Here, we present a general, transferable, and agnostic analysis approach that can reveal precious information on the physics of a variety of complex dynamical systems starting solely from the trajectories of their constitutive units. Built on a bivariate combination of two abstract descriptors, Local Environments and Neighbors Shuffling and

Indexed as

complex dynamical systemsdescriptorsfluctuationslocal and collective dynamical eventsspatiotemporal correlations

Identifiers

PMID39967681
PMCPMC11833705

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.