Evidence map›Paper›PMID 34367614›Full record

ArticleF1000Research2021

CODECHECK: an Open Science initiative for the independent execution of computations underlying research articles during peer review to improve reproducibility.

Daniel Nüst, Stephen J Eglen

Abstract read
In one paragraph

Article in F1000Research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Extent of Open Science Practices in the Reporting of Real World Evidence Research.International journal of population data science · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. How to improve scientific peer review: Four schools of thought.Learned publishing : journal of the Association of Learned and Professional Society Publishers · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. 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

2 authors.

Daniel NüstInstitute for Geoinformatics, University of Münster, Münster, Germany.ORCID 0000-0002-0024-5046
Stephen J EglenDepartment of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, UK.ORCID 0000-0001-8607-8025

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The traditional scientific paper falls short of effectively communicating computational research.  To help improve this situation, we propose a system by which the computational workflows underlying research articles are checked. The CODECHECK system uses open infrastructure and tools and can be integrated into review and publication processes in multiple ways. We describe these integrations along multiple dimensions (importance, who, openness, when). In collaboration with academic publishers and conferences, we demonstrate CODECHECK with 25 reproductions of diverse scientific publications. These CODECHECKs show that asking for reproducible workflows during a collaborative review can effectively improve executability. While CODECHECK has clear limitations, it may represent a building block in Open Science and publishing ecosystems for improving the reproducibility, appreciation, and, potentially, the quality of non-textual research artefacts. The CODECHECK website can be accessed here: https://codecheck.org.uk/.

Indexed as

EcosystemPeer ReviewReproducibility of ResultsWorkflowcode sharingdata sharingOpen Sciencepeer reviewquality controlreproducibilityreproducible researchscholarly publishing

Identifiers

PMID34367614
PMCPMC8311796

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.