Statement of Peer Review †
1
Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA 02139-1955, USA
2
United Imaging Intelligence, Cambridge, MA 02140, USA
*
Authors to whom correspondence should be addressed.
†
All the papers are presented at the AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD), 28 February 2022; Available online: https://aibsdworkshop.github.io/2022 .
Comput. Sci. Math. Forum 2022, 3(1), 12; https://doi.org/10.3390/cmsf2022003012
Published: 31 May 2022
(This article belongs to the Proceedings of AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD))
In submitting conference proceedings to Computer Sciences & Mathematics Forum, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review administered by the volume editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal.
- Type of peer review: double-blind
- Conference submission management system: CMT via https://cmt3.research.microsoft.com/AIBSD2022 (accessed on 12 November 2021).
- Number of submissions sent for review: 19
- Number of submissions accepted: 15 submissions are accepted to be presented at the AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD), and 10 of those 15 accepted submissions are encouraged to further submit to MDPI for publication.
- Acceptance rate (number of submissions accepted/number of submissions received): ~79% for the submissions presented at the AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD); ~53% for the submissions encouraged to further submit to MDPI for publication.
- Average number of reviews per paper: 2
- Total number of reviewers involved: 16
- Any additional information on the review process: The average number of papers assigned to each reviewer is only 2~3 to ensure the review quality.
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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MDPI and ACS Style
Peng, K.-C.; Wu, Z. Statement of Peer Review. Comput. Sci. Math. Forum 2022, 3, 12. https://doi.org/10.3390/cmsf2022003012
AMA Style
Peng K-C, Wu Z. Statement of Peer Review. Computer Sciences & Mathematics Forum. 2022; 3(1):12. https://doi.org/10.3390/cmsf2022003012
Chicago/Turabian StylePeng, Kuan-Chuan, and Ziyan Wu. 2022. "Statement of Peer Review" Computer Sciences & Mathematics Forum 3, no. 1: 12. https://doi.org/10.3390/cmsf2022003012
