Replication and Incentivization: A decentralised peer-to-peer review system and the issuance of smart contracts fosters a collaborative environment, and incentivises replication research to either confirm or contradict existing studies. This ensures the reproducibility of findings, and minimises wasteful time and financial spending.  We also envisage a scenario where some amount of tokens is allocated for replication of a study : when a researcher confirms the study both the original author and the replicating author are compensated.  If  however, the study could not replicated, then the replicating author gets the tokens at the expense of the original author's, thus incentivising replication research. 
By allowing confirmatory (positive) and contradictory (negative) data to be published onto the seeding original observation (seeding node), the seeding node gets extended. Our visualization algorithm enables the seeding node to be linked through edges that can either be positive (green edge) or negative (red edge). If a particular seeding observation can be reproduced by say, 5 different groups (and not by one group), then this seed has a high confirmatory score saying that this is reproducible (see accompanying figure). However, if the seeding observation cannot be reproduced by many groups and has mainly contradictory links, then this has a low confirmatory score and a high contradictory score. We believe that this important as such identification measures could enable or even predict the success or failure of clinical trials or translatability of the findings.  In addition, we created MattericTM, the metric that measures the “seeding potential” and the “extension potential” of both the author and the observation itself. Seeding potential refers to how powerful a seeder an author/observation is: how many further links were based on that particular node? For example, if a rural researcher in Indonesia, without much knowledge about molecular biology or mechanistic insight, discovers that a herbal extract has a potential to reduce psoriasis, and publishes this “single but robustly validated observation” in Matters, then if this is extended by others in terms of mechanistic insights, identifying molecular and immunological basis by several other researchers and industry trying to replicate in other cohorts and pharmaceutical chemists isolating the very compound or a mixture of compounds responsible for: as a result that particular study from the rural Indonesian researcher and her/his single observation would qualify as a great “seeder”. And how far that researcher extended this observation is another measure of focus and persistence. We combine these two in the MattericTM, which we believe is a much better and a direct measure of impact than the existing “journal’s impact factor”.