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Reveal Review Publication

Search by COSMIC Score

When filtering by COSMIC Score, documents are returned based on how well they fit the probability model as determined by a custom Machine Learning model. Users train a “model” data set by tagging for COSMIC groups, and then the algorithm works through the remaining documents based on the user trained data, with each term's relevance probability returned as a number between 0 and 100. This is what the COSMIC Mission Control Statistics table underlying this process looks like:


This enables Reveal AI to return similarly classified documents based on the probability of matching the model. 

The COSMIC Score drop-down button is used to interactively weigh COSMIC scores by their relative probability. In the Settings, users can choose Low, Medium or High probability as well as No score, Errors, and Custom ranges.


Users can define a number of thresholds for any COSMIC model in their storybook. For example, a user can check the ALL option, and use a High probability of “Financing Strategy” and low probability of “Personal Communicatios - Test” in conjunction to find documents that only fit both thresholds. Users can also choose the ANY option, to require just one of the conditional thresholds be met to return results, instead of ALL which would mean that all COSMIC models selected must be present to return the document.