anchor.diff:  --------------------------------------------------
   // CONSOLE
   // TEST[continued]
  -==================================================
   
   [[docs-termvectors-artificial-doc]]
  -[example]
  -.Artificial documents
  ---
  +[float]
  +==== Example: Artificial documents
   
   Term vectors can also be generated for artificial documents,
   that is for documents not present in the index.  For example, the following request would
  
positive.code: // TESTRESPONSE[s/"sum_doc_freq": 2/"sum_doc_freq": "$body.term_vectors.fullname.field_statistics.sum_doc_freq"/]
  // TESTRESPONSE[s/"doc_count": 4/"doc_count": "$body.term_vectors.fullname.field_statistics.doc_count"/]
  // TESTRESPONSE[s/"sum_ttf": 4/"sum_ttf": "$body.term_vectors.fullname.field_statistics.sum_ttf"/]
  ==================================================
  
  [[docs-termvectors-terms-filtering]]
  .Terms filtering
  ==================================================
  
  Finally, the terms returned could be filtered based on their tf-idf scores. In
  the example below we obtain the three most "interesting" keywords from the
  
negative.code: when requesting term vectors of artificial documents, a shard to get the statistics
  from is randomly selected. Use `routing` only to hit a particular shard.
  
  [float]
  ==== Example: Returning stored term vectors
  
  First, we create an index that stores term vectors, payloads etc. :
  
  