Cited by 43Scientific Computing and Data ManagementAcademic Publishing and Open AccessResearch Data Management Practices

This AI researcher is trying to ward off a reproducibility crisis

Open access
Gibney, Elizabeth·2020·Nature

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Crossref · 10.1038/d41586-019-03895-5

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Authors
Gibney, E.
Corresponding author
Gibney, Elizabeth
Venue
Nature
Published
2019-12-19
Volume
577
Issue
7788
Pages
14-14
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2995700434
Cited by
43
References
0
Citations by year
2026: 2 · 2025: 2 · 2024: 24 · 2023: 3 · 2022: 1 · 2021: 8 · 2020: 3
FWCI
3.55
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
  • Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Keywords
replication crisis, open science, open-source code, artificial intelligence research, research transparency

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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