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  • The user query is turned into an ElasticSearch query and applied across the cluster.
  • The number of documents returned from ElasticSearch is capped at a "large" number (default 1000, eg 10x the documents to return). The documents are ordered by their Lucene score (or optionally just by descending date).
  • Each returned document is then assigned a Significance score as described below.
  • The significance and relevance scores are then normalized against each other based on a relative importance specified by the user (default 2:1 in favor of significance) and combined, with the mean score set to 100 (like the "+" stats in baseball, eg 120 is 20% higher than average).
  • The top scoring documents or entities are returned to the client.

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