Evidence map›Paper›PMID 40144776›Full record

ArticlePNAS nexus2025

Two-by-two ordinal patterns in art paintings.

Mateus M Tarozo, Arthur A B Pessa, Luciano Zunino, Osvaldo A Rosso, Matjaž Perc, Haroldo V Ribeiro

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 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. 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

6 authors.

Mateus M TarozoDepartamento de Física, Universidade Estadual de Maringá, Maringá, PR 87020-900, Brazil.ORCID https://orcid.org/0009-0009-9491-2679
Arthur A B PessaDepartamento de Física, Universidade Estadual de Maringá, Maringá, PR 87020-900, Brazil.
Luciano ZuninoCentro de Investigaciones Ópticas (CONICET La Plata - CIC - UNLP), Gonnet, La Plata 1897, Argentina.ORCID https://orcid.org/0000-0002-2852-3263
Osvaldo A RossoInstituto de Física, Universidade Federal de Alagoas, Maceió 57072-900, Brazil.ORCID https://orcid.org/0000-0002-1288-2528
Matjaž PercFaculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, Maribor 2000, Slovenia.ORCID https://orcid.org/0000-0002-3087-541X
Haroldo V RibeiroDepartamento de Física, Universidade Estadual de Maringá, Maringá, PR 87020-900, Brazil.ORCID https://orcid.org/0000-0002-9532-5195

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative analysis of visual arts has recently expanded to encompass a more extensive array of artworks due to the availability of large-scale digitized art collections. Consistent with formal analyses by art historians, many of these studies highlight the significance of encoding spatial structures within artworks to enhance our understanding of visual arts. However, defining universally applicable, interpretable, and sufficiently simple units that capture the essence of paintings and their artistic styles remains challenging. Here, we examine ordering patterns in pixel intensities within two-by-two partitions of images from nearly 140,000 paintings created over the past 1,000 years. These patterns, categorized into 11 types based on arguments of continuity and symmetry, are both universally applicable and detailed enough to correlate with low-level visual features of paintings. We uncover a universal distribution of these patterns, with consistent prevalence within groups, yet modulated across groups by a nontrivial interplay between pattern smoothness and the likelihood of identical pixel intensities. This finding provides a standardized metric for comparing paintings and styles, further establishing a scale to measure deviations from the average prevalence. Our research also shows that these simple patterns carry valuable information for identifying painting styles, though styles generally exhibit considerable variability in the prevalence of ordinal patterns. Moreover, shifts in the prevalence of these patterns reveal a trend in which artworks increasingly diverge from the average incidence over time; however, this evolution is neither smooth nor uniform, with substantial variability in pattern prevalence, particularly after the 1930s.

Indexed as

art historycomplexityesthetic measurespatial patterns

Identifiers

PMID40144776
PMCPMC11937958

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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.