Evidence map›Paper›PMID 34545336›Full record

ArticleArXiv2021

An Open-Publishing Response to the COVID-19 Infodemic.

Halie M Rando, Simina M Boca, Lucy D'Agostino McGowan, Daniel S Himmelstein, Michael P Robson, Vincent Rubinetti, Ryan Velazquez, COVID-19 Review Consortium, Casey S Greene, Anthony Gitter

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Halie M RandoUniversity of Colorado School of Medicine, Center for Health AI, Aurora, CO, USA.ORCID 0000-0001-7688-1770
Simina M BocaGeorgetown University Medical Center, Innovation Center for Biomedical Informatics, Washington, DC, USA.ORCID 0000-0002-1400-3398
Lucy D'Agostino McGowanWake Forest University, Department of Mathematics and Statistics, Winston-Salem, NC, USA.ORCID 0000-0001-7297-9359
Daniel S HimmelsteinUniversity of Pennsylvania, Perelman School of Medicine, Department of Systems Pharmacology and Translational Therapeutics, Philadelphia, PA, USA.ORCID 0000-0002-3012-7446
Michael P RobsonVillanova University, Department of Computing Sciences, Villanova, PA, USA.ORCID 0000-0002-4859-0033
Vincent RubinettiUniversity of Colorado School of Medicine, Center for Health AI, Aurora, CO, USA.ORCID 0000-0002-4655-3773
Ryan VelazquezAzimuth1, McLean, VA, USA.ORCID 0000-0002-3655-3403
COVID-19 Review Consortium
Casey S GreeneUniversity of Colorado School of Medicine, Center for Health AI, Aurora, CO, USA.ORCID 0000-0001-8713-9213
Anthony GitterUniversity of Wisconsin-Madison, Department of Biostatistics and Medical Informatics, Madison, WI, USA.ORCID 0000-0002-5324-9833

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

The COVID-19 pandemic catalyzed the rapid dissemination of papers and preprints investigating the disease and its associated virus, SARS-CoV-2. The multifaceted nature of COVID-19 demands a multidisciplinary approach, but the urgency of the crisis combined with the need for social distancing measures present unique challenges to collaborative science. We applied a massive online open publishing approach to this problem using Manubot. Through GitHub, collaborators summarized and critiqued COVID-19 literature, creating a review manuscript. Manubot automatically compiled citation information for referenced preprints, journal publications, websites, and clinical trials. Continuous integration workflows retrieved up-to-date data from online sources nightly, regenerating some of the manuscript's figures and statistics. Manubot rendered the manuscript into PDF, HTML, LaTeX, and DOCX outputs, immediately updating the version available online upon the integration of new content. Through this effort, we organized over 50 scientists from a range of backgrounds who evaluated over 1,500 sources and developed seven literature reviews. While many efforts from the computational community have focused on mining COVID-19 literature, our project illustrates the power of open publishing to organize both technical and non-technical scientists to aggregate and disseminate information in response to an evolving crisis.

Identifiers

PMID34545336
PMCPMC8452106

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.