tRCM protocol stands for trustless review consensus mechanism. It is the core protocol of CheckerChain built with blockchain and AI/ML integration.
Definition For a review to hold any value, - it should be trustless without any control of poster or reviewer. - it should be honest without any biased motive of anyone involved.
In tRCM protocol, anyone can participate but the protocol selects the reviewers arbitrarily to review a product. Selected reviewers can only get reward for their work when their review score falls in consensus range. Closer the consensus, more the reward.
Reviewers have higher probability to make their review closer to consensus only when they are honest. Any dishonest review or reviewer falls short of consensus making no or least reward which will eventually discourage to perform such wasteful work.
tRCM protocol has been filed for US patent. See details here.
Types of Scores
- 1.Trust Score: This is an atomic data of a product calculated from reviewer's task. It represents rating of a product in the range of 0 to 100.
- 2.Normalized Trust Score: This is a derived data of a product calculated from Trust score to determine the impact on reward. Posters receive reward based on Normalized Trust score.
- 3.Consensus Score: This is an atomic data of reviewer's task. It represents the quality of trust score in the range of 0 to 100.
- 4.Profile Score: This is both an atomic and aggregated data of reviewer's performance. It represents the quality of consensus in the range of 0 to 100. Reviewers receive reward based on Profile score.
- 5.Rating Score: This is a derived data of a product calculated as Trust score out of 5 and processed with Bayesian Average.
- 6.Feedback Score: This is an aggregated data of reviewer's task combined with influencer's task. It represents sentiments of a product in the range of 0 to 5.
- 7.Normalized Feedback Score: This is a derived data calculated from Feedback Score; processed with Bayesian Average.
- 8.Sentiment Score: This is a categorical data of a product from reviewer's task. It is non-numerical in category and numerical inside a category in the range of 0 to 100.
- 9.Ranking Score: This is a derived data of a product calculated from Rating score and Consensus score. It represents the rank of a product starting from 1 over 24h, 7 days, 30 days and All-Time ranges.