anchor.diff:  
   Search quality evaluation starts with looking at the users of your search 
   application, and the things that they are searching for. Users have a specific 
  -_information need_, for example they are looking for gift in a web shop or want 
  +_information need_; for example, they are looking for gift in a web shop or want 
   to book a flight for their next holiday. They usually enter some search terms 
   into a search box or some other web form. All of this information, together with 
   meta information about the user (for example the browser, location, earlier 
  
positive.code: ===== Mean reciprocal rank
  
  For every query in the test suite, this metric calculates the reciprocal of the 
  rank of the first relevant document. For example finding the first relevant 
  result in position 3 means the reciprocal rank is 1/3. The reciprocal rank for 
  each query is averaged across all queries in the test suite to give the 
  https://en.wikipedia.org/wiki/Mean_reciprocal_rank[mean reciprocal rank].
  
negative.code: 
  In contrast to the two metrics above, 
  https://en.wikipedia.org/wiki/Discounted_cumulative_gain[discounted cumulative gain] 
  takes both the rank and the rating of the search results into account.
  
  The assumption is that highly relevant documents are more useful for the user 
  when appearing at the top of the result list. Therefore, the DCG formula reduces 
  