Evidence map›Paper›PMID 37147665›Full record

ArticleBioData mining2023

Changing word meanings in biomedical literature reveal pandemics and new technologies.

David N Nicholson, Faisal Alquaddoomi, Vincent Rubinetti, Casey S Greene

Abstract read
In one paragraph

Article in BioData mining, 2023. 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

4 authors.

David N NicholsonGenomics and Computational Biology Program, University of Pennsylvania, Philadelpia, PA, USA.ORCID http://orcid.org/0000-0003-0002-5761
Faisal AlquaddoomiDepartment of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA.ORCID http://orcid.org/0000-0003-4297-8747
Vincent RubinettiDepartment of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA.
Casey S GreeneDepartment of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, USA. casey.s.greene@cuanschutz.edu.ORCID http://orcid.org/0000-0001-8713-9213

Funding

Network-based algorithms for target identification and drug repositioning from genetic associationsR01HG010067 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI GREENE, CASEY S · 2018 to 2022
$3.2M
NHGRI NIH HHS R01 HG010067
6 · The paper itself

Abstract

While we often think of words as having a fixed meaning that we use to describe a changing world, words are also dynamic and changing. Scientific research can also be remarkably fast-moving, with new concepts or approaches rapidly gaining mind share. We examined scientific writing, both preprint and pre-publication peer-reviewed text, to identify terms that have changed and examine their use. One particular challenge that we faced was that the shift from closed to open access publishing meant that the size of available corpora changed by over an order of magnitude in the last two decades. We developed an approach to evaluate semantic shift by accounting for both intra- and inter-year variability using multiple integrated models. This analysis revealed thousands of change points in both corpora, including for terms such as 'cas9', 'pandemic', and 'sars'. We found that the consistent change-points between pre-publication peer-reviewed and preprinted text are largely related to the COVID-19 pandemic. We also created a web app for exploration that allows users to investigate individual terms ( https://greenelab.github.io/word-lapse/ ). To our knowledge, our research is the first to examine semantic shift in biomedical preprints and pre-publication peer-reviewed text, and provides a foundation for future work to understand how terms acquire new meanings and how peer review affects this process.

Indexed as

Linguistic shiftNoveltyPandemicSoftware

Identifiers

PMID37147665
PMCPMC10161184

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.