The last decade have witnessed a profusion of research work on the crowdsourcing topic. Human skills are essential in achieving high quality answers in crowdsourcing solving tasks. The current paper aims to introduce an innovative crowdsourcing-based solution for a scientific meta-journal. An overall architecture of the proposed system is introduced with a focus on the aggregation of the reviewers’ evaluations to produce a final decision. We introduce several aggregation methods adapted to the nature of data to fusion and discuss them. In addition, we discuss future challenges that cope with the proposed system.