Evidence map›Paper›PMID 40702185›Full record

ArticleNature2025

Contextualizing ancient texts with generative neural networks.

Yannis Assael, Thea Sommerschield, Alison Cooley, Brendan Shillingford, John Pavlopoulos, Priyanka Suresh, Bailey Herms, Justin Grayston, Benjamin Maynard, Nicholas Dietrich and 4 more

Abstract readHistorical Article
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature, 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

14 authors.

Yannis Assael *Google DeepMind, London, UK. yannisassael@google.com.ORCID 0000-0001-7408-3847
Thea Sommerschield *Department of Classics and Archaeology, University of Nottingham, Nottingham, UK. thea.sommerschield@durham.ac.uk.ORCID 0000-0002-6965-8105
Alison CooleyDepartment of Classics and Ancient History, University of Warwick, Warwick, UK.ORCID 0000-0003-4324-7241
Brendan ShillingfordGoogle DeepMind, London, UK.
John PavlopoulosDepartment of Informatics, Athens University of Economics and Business, Athens, Greece.ORCID 0000-0001-9188-7425
Priyanka SureshGoogle DeepMind, London, UK.ORCID 0009-0000-8324-7129
Bailey HermsGoogle, Mountain View, CA, USA.
Justin GraystonGoogle, Mountain View, CA, USA.
Benjamin MaynardGoogle, Mountain View, CA, USA.
Nicholas DietrichGoogle DeepMind, London, UK.ORCID 0009-0009-7450-7852
Robbe WulgaertSint-Lievenscollege, Ghent, Belgium.ORCID 0009-0003-7225-4368
Jonathan PragFaculty of Classics, University of Oxford, Oxford, UK.ORCID 0000-0003-3819-8537
Alex MullenDepartment of Classics and Archaeology, University of Nottingham, Nottingham, UK.
Shakir MohamedGoogle DeepMind, London, UK.

Funding

Leverhulme Trust
6 · The paper itself

Abstract

Human history is born in writing. Inscriptions are among the earliest written forms, and offer direct insights into the thought, language and history of ancient civilizations. Historians capture these insights by identifying parallels-inscriptions with shared phrasing, function or cultural setting-to enable the contextualization of texts within broader historical frameworks, and perform key tasks such as restoration and geographical or chronological attribution

Indexed as

Neural Networks, ComputerCivilizationHistory, AncientHumans

Identifiers

PMID40702185
PMCPMC12408360

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.