Machine-Readable Disclosure is a formal academic contribution that belongs to the category of digital transparency mechanisms, specifically characterized by the structured, standardized, and computationally accessible presentation of research artifacts, enabling automated processing, verification, and reuse of scholarly information by both humans and machines.
4
Publications
139
Citations
5
Authors
5
Institutions
Publications per year
2017–2026
2
Parents
Publications
4
Rory Van Loo · SSRN Electronic Journal · 2016 · 35 citations · Full text
Scientists hide messages in papers to game AI peer review
Elizabeth Gibney · Nature · 2025 · 15 citations · Full text
The necessity of data transparency to publish
Jon Grahe · The Journal of Social Psychology · 2020 · 14 citations · Full text
Contracts in the Age of Smart Readers
Yonathan A. Arbel, Shmuel I. Becher · SSRN Electronic Journal · 2020 · 12 citations · Full text
1–5 of 4
Authors
5
- YA
1
h-index
- BO
1
h-index
- RV
1
h-index
- SI
1
h-index
- JG
1
h-index
1–5 of 5
Institutions
5
Yale University
New Haven, United States
1 h-index
1 publications
35 citations
Victoria University of Wellington
Wellington, New Zealand
1 h-index
1 publications
12 citations
Pacific Lutheran University
Tacoma, United States
1 h-index
1 publications
14 citations
Boston University
Boston, United States
1 h-index
1 publications
35 citations
University of Alabama
Tuscaloosa, United States
1 h-index
1 publications
12 citations
1–5 of 5
Venues
- SSRN Electronic Journal
Repository · 2 publications · 47 citations
2
h-index
- United States. Office of the Federal Register
1 publications · 78 citations
1
h-index
- The Journal of Social Psychology
1 publications · 14 citations
1
h-index
- Nature
1 publications · 15 citations
1–4