Evidence map›Paper›PMID 34786306›Full record

ArticleIEEE access : practical innovations, open solutions2021

Sleeping Beauties of Coronavirus Research.

Mohsen Fazeli-Varzaneh, Ali Ghorbi, Marcel Ausloos, Emanuel Sallinger, Sahar Vahdati

Abstract read
In one paragraph

Article in IEEE access : practical innovations, open solutions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Mohsen Fazeli-VarzanehDepartment of Knowledge and Information ScienceFaculty of ManagementUniversity of Tehran Tehran 1417466191 Iran.
Ali GhorbiDepartment of Knowledge and Information ScienceFaculty of ManagementUniversity of Tehran Tehran 1417466191 Iran.
Marcel AusloosSchool of BusinessUniversity of Leicester Leicester LE2 1RQ U.K.
Emanuel SallingerFaculty of InformaticsTU Wien 1040 Vienna Austria.
Sahar VahdatiNature-Inspired Machine IntelligenceInstitute of Applied Informatics (InfAI) 01069 Dresden Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A "Sleeping Beauty" (SB) in science is a metaphor for a scholarly publication that remains relatively unnoticed by the related communities for a long time; - the publication is "sleeping". However, suddenly due to the appearance of some phenomenon, such a "forgotten" publication may become a center of scientific attention; - the SB is "awakened". Currently, there are specific scientific areas for which sleeping beauties (SBs) are awakened. For example, as the world is experiencing the COVID-19 global pandemic (triggered by SARS-CoV-2), publications on coronaviruses appear to be awakened. Thus, one can raise questions of scientific interest: are these publications coronavirus related SBs? Moreover, while much literature exists on other coronaviruses, there seems to be no comprehensive investigation on COVID-19, - in particular in the context of SBs. Nowadays, such SB papers can be even used for sustaining literature reviews and/or scientific claims about COVID-19. In our study, in order to pinpoint pertinent SBs, we use the "beauty score" (B-score) measure. The Activity Index (AI) and the Relative Specialization Index (RSI) are also calculated to compare countries where such SBs appear. Results show that most of these SBs were published previously to the present epidemic time (triggered by SARS-CoV or SARS-CoV-1), and are awakened in 2020. Besides outlining the most important SBs, we show from what countries and institutions they originate, and the most prolific author(s) of such SBs. The citation trend of SBs that have the highest B-score is also discussed.

Indexed as

activity indexBeauty scorebibliometriccoronavirusCOVID-19relative specialization indexsleeping beauty

Identifiers

PMID34786306
PMCPMC8545245

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.