Cited by 11

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The potential of DAOs for funding and collaborative development in the life sciences

Fantaccini, Simone, Grassi, Laura, Rampoldi, Andrea·2024·Nature Biotechnology

Overview

Integrity signals

Registry

Crossref · 10.1038/s41587-024-02189-0

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • VitaDAO has deployed over $4.2 million to fund over 20 research projects since 2021, including a $285,000 investment in Newcastle University's Korolchuk Lab.

    “Since its launch in 2021, VitaDAO has deployed over $4.2 million to fund over 20 research projects, including a noteworthy $285,000 investment in Newcastle University's Korolchuk Lab to identify novel autophagy activators that could play a critical role in treating age-related diseases.”
  • VitaDAO's success exemplifies the potential of DAO frameworks to disrupt traditional research funding and enable impactful scientific innovation in a decentralized ecosystem.

    “VitaDAO's success exemplifies the potential of DAO frameworks to disrupt traditional research funding and enable impactful scientific innovation in a decentralized ecosystem.”
  • DAO can be used to govern data markets and enhance discoveries in different scientific fields.

    “DAO can be used to govern data markets (Ding et al., 2023a) and enhance discoveries in different scientific fields, such as longevity, reproductive health, and machine learning (Fantaccini et al., 2024).”

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 21

  1. Grassi, L. & Fantaccini, S. Financ. Innov. 8, 84 (2022). · DOI
  2. Seyhan, A. A. Transl. Med. Commun. 4, 18 (2019). · DOI
  3. Goldberg, M. & Schär, F. J. Bus. Res. 160, 113764 (2023). · DOI · Paper page
  4. Santana, C. & Albareda, L. Technol. Forecast. Soc. Change 182, 121806 (2022). · DOI
  5. Wang, S. et al. IEEE Trans. Comput. Soc. Syst. 6, 870–878 (2019). · DOI · Paper page
  6. Singh, M. & Kim, S. Adv. Comput. 115, 115–140 (2019). · DOI
  7. Kaal, W. A. Ann. Corp. Gov. 5, 237–307 (2021).
  8. Faqir-Rhazoui, Y., Arroyo, J. & Hassan, S. J. Internet Serv. Appl. 12, 9 (2021). · DOI · Paper page
  9. Zhao, X., Ai, P., Lai, F., Luo, X. & Benitez, J. J. Oper. Manage. 68, 649–674 (2022). · DOI
  10. Grassi, L., Lanfranchi, D., Faes, A. & Renga, F. M. Qual. Res. Account. Manag. 19, 323–347 (2022). · DOI
  11. Murray, A., Kuban, S., Josefy, M. & Anderson, J. Acad. Manage. Perspect. 35, 622–641 (2021). · DOI
  12. DeFrancesco, L. & Klevecz, A. Nat. Biotechnol. 40, 1310–1315 (2022). · DOI
  13. Bellavitis, C., Fisch, C. & Momtaz, P. P. Ventur. Cap. 25, 187–203 (2023). · DOI
  14. Onjewu, A. K., Walton, N. & Koliousis, I. Technol. Forecast. Soc. Change 191, 122482 (2023). · DOI
  15. Bischof, E. et al. IEEE Access 10, 33048–33058 (2022). · DOI
  16. Beck, R., Müller-Bloch, C. & King, J. L. J. Assoc. Inf. Syst. 19, 1020–1034 (2018).
  17. Saurabh, K., Rani, N. & Upadhyay, P. Benchmarking (Bradf.) 30, 475–502 (2023). · DOI
  18. Zamani, E. D. & Giaglis, G. M. Ind. Manage. Data Syst. 118, 637–652 (2018). · DOI
  19. Ding, W. et al. IEEE Trans. Comput. Soc. Syst. 9, 1563–1573 (2022). · DOI · Paper page
  20. Gompers, P. A., Gornall, W., Kaplan, S. N. & Strebulaev, I. A. J. Financ. Econ. 135, 169–190 (2020). · DOI
  21. Hsieh, Y. Y., Vergne, J. P., Anderson, P., Lakhani, K. & Reitzig, M. J. Organiz. Des. 7, 14 (2018).

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Metadata

Authors
Fantaccini, S., Grassi, L., & Rampoldi, A.
Venue
Nature Biotechnology
Published
2024-04
Volume
42
Issue
4
Pages
555-562
ISSN
  • 1087-0156
  • 1546-1696
Cited by
11
References
1
Language
en

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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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