Cosmos 1.0: a multidimensional map of the emerging technology frontier.

Xian Gong, Paul X McCarthy, Colin Griffith, Claire McFarland, Marian-Andrei Rizoiu

Abstract read

In one paragraph

Article in Scientific data, 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.

Wikipedia-based AI model reveals the 100 technologies to watch.Nature · 2026
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

5 authors.

Xian Gong *University of Technology Sydney, Faculty of Engineering and Information Technology, Sydney, 2007, Australia. xian.gong@student.uts.edu.au.ORCID http://orcid.org/0000-0003-1397-5977

Paul X McCarthy *University of Technology Sydney, Faculty of Engineering and Information Technology, Sydney, 2007, Australia.

Colin GriffithData61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Sydney, Australia.

Claire McFarlandUniversity of Technology Sydney, Faculty of Engineering and Information Technology, Sydney, 2007, Australia.

Marian-Andrei RizoiuUniversity of Technology Sydney, Faculty of Engineering and Information Technology, Sydney, 2007, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper introduces the Cosmos 1.0 dataset and describes a novel methodology for creating and mapping a universe of technologies, adjacent concepts, and entities. We utilise various source data that contain a rich diversity and breadth of contemporary knowledge. The Cosmos 1.0 dataset comprises 23,544 technology-adjacent entities (TA23k) with a hierarchical structure and eight categories of external indices. Each entity is represented by a 100-dimensional contextual embedding vector, which we use to assign it to seven thematic tech-clusters (TC7) and three meta tech-clusters (TC3). We manually verify 100 emerging technologies (ET100). This dataset is enriched with additional indices specifically developed to assess the landscape of emerging technologies, including the Technology Awareness Index, Generality Index, Deeptech, and Age of Tech Index. The dataset incorporates extensive metadata sourced from Wikipedia and linked data from third-party sources such as Crunchbase, Google Books, OpenAlex and Google Scholar, which are used to validate the relevance and accuracy of the constructed indices.

Identifiers

PMID41261102

DOI10.1038/s41597-025-06125-y

PMCPMC12630975

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.