Evidence map›Paper›PMID 37983494›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

A network-based normalized impact measure reveals successful periods of scientific discovery across discipline.

Qing Ke, Alexander J Gates, Albert-László Barabási

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Informal connections outweigh coauthorship ties in academic impact.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Reply to Vaccario et al.: The role of baselines in fair and unbiased citation metric evaluation.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  3. The quest for an unbiased scientific impact indicator remains open.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  4. A network-based normalized impact measure reveals successful periods of scientific discovery across discipline.Proceedings of the National Academy of Sciences of the United States of America · 2023
    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

3 authors.

Qing KeSchool of Data Science, City University of Hong Kong, Hong Kong, China.ORCID 0000-0002-2945-5274
Alexander J GatesSchool of Data Science, University of Virginia, Charlottesville, VA 22904.
Albert-László BarabásiNetwork Science Institute, Northeastern University, Boston, MA 02115.ORCID 0000-0002-4028-3522

Funding

CSRD VA 1
6 · The paper itself

Abstract

The impact of a scientific publication is often measured by the number of citations it receives from the scientific community. However, citation count is susceptible to well-documented variations in citation practices across time and discipline, limiting our ability to compare different scientific achievements. Previous efforts to account for citation variations often rely on a priori discipline labels of papers, assuming that all papers in a discipline are identical in their subject matter. Here, we propose a network-based methodology to quantify the impact of an article by comparing it with locally comparable research, thereby eliminating the discipline label requirement. We show that the developed measure is not susceptible to discipline bias and follows a universal distribution for all articles published in different years, offering an unbiased indicator for impact across time and discipline. We then use the indicator to identify science-wide high impact research in the past half century and quantify its temporal production dynamics across disciplines, helping us identifying breakthroughs from diverse, smaller disciplines, such as geosciences, radiology, and optics, as opposed to citation-rich biomedical sciences. Our work provides insights into the evolution of science and paves a way for fair comparisons of the impact of diverse contributions across many fields.

Indexed as

BibliometricsJournal Impact FactorAchievementBiasbibliometricscitation analysisscience of sciencescientific impact

Identifiers

PMID37983494
PMCPMC10691329

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.