The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Enhancing reproducibility for computational methods
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Data, code, and workflows should be available and cited
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Cites
Promoting an open research culture
Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., Buck, S., Chambers, C. D., Chin, G., Christensen, G., et al. (2015) · Science · doi:10.1126/science.aab2374 · Cited by 2,708
Self-citationPublic Availability of Published Research Data in High-Impact Journals
Alsheikh-Ali, A. A., Qureshi, W., Al-Mallah, M. H., & Ioannidis, J. P. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024357 · Cited by 363
Self-citationStodden, V., Guo, P., & Ma, Z. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067111 · Cited by 257
Self-citation
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Opportunities and obstacles for deep learning in biology and medicine
Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0387 · Cited by 2,310
KBase: The United States Department of Energy Systems Biology Knowledgebase
(2018) · doi:10.1038/nbt.4163 · Cited by 1,624
Systematic integration of biomedical knowledge prioritizes drugs for repurposing
Himmelstein, D. S., Lizee, A., Hessler, C., Brueggeman, L., Chen, S. L., Hadley, D., Green, A., Khankhanian, P., & Baranzini, S. E. (2017) · eLife · doi:10.7554/elife.26726 · Cited by 666
Open science challenges, benefits and tips in early career and beyond
Allen, C., & Mehler, D. M. A. (2019) · PLOS Biology · doi:10.1371/journal.pbio.3000246 · Cited by 608
Transparency and reproducibility in artificial intelligence
Haibe-Kains, B., Adam, G. A., Hosny, A., Khodakarami, F., Massive Analysis Quality Control (MAQC) Society Board of Directors, Shraddha, T., Kusko, R., Sansone, S.-A., Tong, W., Wolfinger, R. D., et al. (2020) · Nature · doi:10.1038/s41586-020-2766-y · Cited by 540
Self-citationRobinson, J. L., Kocabaş, P., Wang, H., Cholley, P.-E., Cook, D., Nilsson, A., Anton, M., Ferreira, R., Domenzain, I., Billa, V., et al. (2020) · Science Signaling · doi:10.1126/scisignal.aaz1482 · Cited by 442
An empirical analysis of journal policy effectiveness for computational reproducibility
Stodden, V., Seiler, J., & Ma, Z. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1708290115 · Cited by 369
Self-citationHardwicke, T. E., Mathur, M. B., MacDonald, K., Nilsonne, G., Banks, G. C., Kidwell, M. C., Hofelich Mohr, A., Clayton, E., Yoon, E. J., Henry Tessler, M., et al. (2018) · Royal Society Open Science · doi:10.1098/rsos.180448 · Cited by 336
When Null Hypothesis Significance Testing Is Unsuitable for Research: A Reassessment
Szucs, D., & Ioannidis, J. P. A. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00390 · Cited by 298
Self-citationNaudet, F., Sakarovitch, C., Janiaud, P., Cristea, I., Fanelli, D., Moher, D., & Ioannidis, J. P. A. (2018) · BMJ · doi:10.1136/bmj.k400 · Cited by 227
Self-citationIoannidis, J. P. A., Kim, B. Y. S., & Trounson, A. (2018) · Nature Biomedical Engineering · doi:10.1038/s41551-018-0314-y · Cited by 175
Self-citationAssessment of transparency indicators across the biomedical literature: How open is open?
Serghiou, S., Contopoulos-Ioannidis, D. G., Boyack, K. W., Riedel, N., Wallach, J. D., & Ioannidis, J. P. A. (2021) · PLOS Biology · doi:10.1371/journal.pbio.3001107 · Cited by 139
Self-citationGundersen, O. E., Gil, Y., & Aha, D. W. (2018) · AI Magazine · doi:10.1609/aimag.v39i3.2816 · Cited by 99
Self-citationStable reliability diagrams for probabilistic classifiers
Dimitriadis, T., Gneiting, T., & Jordan, A. I. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2016191118 · Cited by 84
Crüwell, S., Apthorp, D., Baker, B. J., Colling, L., Elson, M., Geiger, S. J., Lobentanzer, S., Monéger, J., Patterson, A., Schwarzkopf, D. S., et al. (2023) · Psychological Science · doi:10.1177/09567976221140828 · Cited by 54
Liu, D. M., & Salganik, M. J. (2019) · Socius Sociological Research for a Dynamic World · doi:10.1177/2378023119849803 · Cited by 47
Solmi, M., Correll, C. U., Carvalho, A. F., & Ioannidis, J. P. A. (2018) · Epidemiology and Psychiatric Sciences · doi:10.1017/s204579601800032x · Cited by 44
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“…discuss and describe frameworks, theories, or other assumptions used to interpret data; and provide reviewers and the public with access to primary data that is not considered proprietary or protected by confidentiality rules pertaining to human subjects (Soranno et al. 2015; Stodden et al. 2016).”
BackgroundMüller-Hansen, F., Callaghan, M. W., & Minx, J. C. (2020) · Energy Research & Social Science · doi:10.1016/j.erss.2020.101691 · Cited by 32
Reproducible Research Using Biomodels
Mendes, P. (2018) · Bulletin of Mathematical Biology · doi:10.1007/s11538-018-0498-z · Cited by 20
Marwick, B., Barton, C. M., Bates, L., Bollwerk, E., Bocinsky, R. K., Carter, A. K., Conrad, C., Costa, S., Crema, E. R., Davies, B., et al. (2017) · doi:10.31235/osf.io/72n8g · Cited by 17
Designing reproducible large-language-model-assisted scientific analyses
Dunn, C. W., Schultz, D. T., & Musser, J. M. (2026) · Patterns · doi:10.1016/j.patter.2026.101644
From Data Islands to Knowledge Networks in Tribology: Understanding the Modern Data Architecture
Garabedian, N., & Tysoe, W. T. (2026) · Tribology Letters · doi:10.1007/s11249-026-02179-0
Metadata
- Authors
- Stodden, V., McNutt, M., Bailey, D. H., Deelman, E., Gil, Y., Hanson, B., Heroux, M. A., Ioannidis, J. P. A., & Taufer, M.
- Venue
- Science
- Published
- 2016-12-09
- Volume
- 354
- Issue
- 6317
- Pages
- 1240-1241
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2560471521
- Cited by
- 411
- References
- 3
- FWCI
- 88.92
- Type
- journal article
- Language
- en
- Open access
- green
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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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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
