Evidence map›Paper›PMID 39251724›Full record

ArticleNature human behaviour2024

What we should learn from pandemic publishing.

Satyaki Sikdar, Sara Venturini, Marie-Laure Charpignon, Sagar Kumar, Francesco Rinaldi, Francesco Tudisco, Santo Fortunato, Maimuna S Majumder

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature human behaviour, 2024. 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. Review
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

8 authors.

Satyaki Sikdar *Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA.ORCID http://orcid.org/0000-0003-1669-6594
Sara Venturini *Senseable City Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-2653-8533
Marie-Laure CharpignonInstitute for Data, Systems, and Society; Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-5786-2627
Sagar KumarNetwork Science Institute, Northeastern University, Boston, MA, USA.ORCID http://orcid.org/0000-0003-0157-4615
Francesco RinaldiDepartment of Mathematics "Tullio Levi-Civita", University of Padova, Padova, Italy.ORCID http://orcid.org/0000-0001-8978-6027
Francesco TudiscoSchool of Mathematics, The University of Edinburgh, Edinburgh, UK.ORCID http://orcid.org/0000-0002-8150-4475
Santo FortunatoLuddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA. santo@iu.edu.ORCID http://orcid.org/0000-0002-9039-4730
Maimuna S MajumderDepartment of Pediatrics, Harvard Medical School, Boston, MA, USA. maimuna.majumder@childrens.harvard.edu.ORCID http://orcid.org/0000-0002-3986-4303

Funding

Digital data streams and machine learning for real-time modeling of vaccine-preventable infectious diseasesR35GM146974 · NIGMS · BOSTON CHILDREN'S HOSPITAL · PI Maimuna Shahnaz Majumder · 2022 to 2026
$2.2M
National Science Foundation (NSF) 1927418National Science Foundation (NSF) 1927425National Science Foundation (NSF) SES2200228NIGMS NIH HHS R35 GM146974United States Department of Defense | United States Air Force | AFMC | Air Force Office of Scientific Research (AF Office of Scientific Research) FA9550-19-1-0354U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R35GM146974
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

COVID-19PublishingHumansPandemicsPeriodicals as Topic

Identifiers

PMID39251724
PMCPMC12463321

What OpenQuestion holds

Textmetadata
LicenceTDM
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.