Reproducibility: A tragedy of errors
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Reproducibility issues usually stem from inappropriate study design or baseline comparisons, and miscalculation.
“This usually stems from inappropriate study design or baseline comparisons, and miscalculation.”
From Artificial Intelligence in Detecting Statistical Errors: Implications for Authors, Reviewers, and Editors (2025) · cites this paper as [19]
The opening section describes a mathematical model that overestimated an effect by more than tenfold, and ‘What can be done?’ recommends statistical expertise for experimental design and analysis. But our copy does not identify inappropriate baseline comparisons as a cause or establish that these issues ‘usually’ cause reproducibility problems; the authors say their review was not systematic and they do not know the rate of errors. The referenced ‘Three common errors’ textbox is not present in the passages returned from our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measuredSometimes, reproducibility is not feasible given a vague description of the methodology.
“Sometimes, reproducibility is not feasible given a vague description of the methodology.19”
From Artificial Intelligence in Detecting Statistical Errors: Implications for Authors, Reviewers, and Editors (2025) · cites this paper as [19]
The section ‘Six Problems > No standard mechanism exists to request raw data’ describes difficulty obtaining data to check suspected errors, not an inability to reproduce work because its methodology is vaguely described. Searches for insufficient methodological detail and descriptions needed to replicate a study found no passage addressing that point in our copy. (LLM, conf=0.70)
Experimental — accuracy not yet measuredSimilar errors continue today, are sometimes severe enough to call entire studies into question, and may occur with nontrivial frequency.
“Similar errors continue today, are sometimes severe enough to call entire studies into question (11), and may occur with nontrivial frequency (12–14).”
From Issues with data and analyses: Errors, underlying themes, and potential solutions (2018) · cites this paper as [11]
Correction of errors often requires an arduous process that highlights limitations of the self-correcting nature of science.
“Unfortunately, correction of errors often requires an arduous process that highlights limitations of the self-correcting nature of science (11).”
From Issues with data and analyses: Errors, underlying themes, and potential solutions (2018) · cites this paper as [11]
The process of getting errors corrected, even through proper channels with journals, is often some combination of absurdly slow, inept, confusing, costly, time-intensive, and unsatisfying.
“As we reported elsewhere (11), the process of getting errors corrected, even when going through proper channels with journals, is often some combination of absurdly slow, inept, confusing, costly, time-intensive, and unsatisfying.”
From Issues with data and analyses: Errors, underlying themes, and potential solutions (2018) · cites this paper as [11]
The handling of data and statistically oriented errors in published papers is haphazard, unduly slow, inconsistent, and often markedly socially inappropriate.
“Experience indicates that the handling of such errors (both purported and confirmed) is haphazard, unduly slow, inconsistent, and often markedly socially inappropriate (11, 80, 81).”
From Issues with data and analyses: Errors, underlying themes, and potential solutions (2018) · cites this paper as [11]
Much of the difficulty to achieve desirable clinical translation may stem from lack of reproducibility and from biases in the early stages of the translational pipeline.
“Much of the difficulty to achieve the desirable clinical translation may stem from lack of reproducibility and from biases in the early stages of the translational pipeline3,4.”
From How to design preclinical studies in nanomedicine and cell therapy to maximize the prospects of clinical translation (2018) · cites this paper as [4]
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- Authors
- Allison, D. B., Brown, A. W., George, B. J., & Kaiser, K. A.
- Affiliations
- University of Alabama at Birmingham (US)
- Corresponding author
- Allison, David B.
- Venue
- Nature
- Published
- 2016-02-03
- Volume
- 530
- Issue
- 7588
- Pages
- 27-29
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4831566
- OpenAlex
- W2263593861
- Cited by
- 255
- References
- 10
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 48 · 2023: 19 · 2022: 11 · 2021: 29 · 2020: 30 · 2019: 27 · 2018: 25 · 2017: 26 · 2016: 22 · 2015: 1
- FWCI
- 175.39
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (acceptedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK056336)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Publishing and Scholarly Communication
- Keywords
- reproducibility, research errors, peer review, scholarly publishing, research integrity, error correction
- MeSH terms
- Humans, Periodicals as Topic, Research Design, Retraction of Publication as Topic, Reproducibility of Results, Peer Review, Research, Access to Information, Editorial Policies
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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