anchor.diff:  [cols="<,<",options="header",]
   |=======================================================================
   |Parameter |Description
  -|`relevant_rating_threshold` |Sets the rating threshold from which on documents are considered to be
  +|`relevant_rating_threshold` |Sets the rating threshold above which documents are considered to be
   "relevant". Defaults to `1`.
   |=======================================================================
   
  
positive.code: The `metric` section determines which of the available evaluation metrics is going to be used.
  Currently, the following metrics are supported:
  
  ==== Precision at k (Prec@k)
  
  This metric measures the number of relevant results in the top k search results. Its a form of the well known https://en.wikipedia.org/wiki/Information_retrieval#Precision[Precision] metric that only looks at the top k documents. It is the fraction of relevant documents in those first k
  search. A precision at 10 (prec@10) value of 0.6 then means six out of the 10 top hits where
  relevant with respect to the users information need.
  
  This metric works well as a first and an easy to explain evaluation metric. 
  Documents in the collection need to be rated either as relevant or irrelevant with respect to the current query. Prec@k does not take into account where in the top k results the relevant documents occur, so a ranking of ten results that contains one relevant
  result in position 10 is equally good as a ranking of ten results that contains
  one relevant result in position 1.
  
  [source,js]
  --------------------------------
  
negative.code: ------------------------------
  // NOTCONSOLE
  
  <1> a set of typical search requests, together with their provided ratings
  <2> definition of the evaluation metric to calculate
  <3> a specific metric and its parameters
  
  