anchor.diff:  }
   --------------------------------------------------
   // NOTCONSOLE
  -<1> To take advantage of the script optimizations, provide a query vector as a script parameter.
  +<1> The script adds 1.0 to the cosine similarity to prevent the score from being negative.
  +<2> To take advantage of the script optimizations, provide a query vector as a script parameter.
   
   Similarly, for sparse_vector fields, `cosineSimilaritySparse` calculates cosine similarity
   between a given query vector and document vectors.
  
positive.code:         "match_all": {}
        },
        "script": {
          "source": "dotProduct(params.queryVector, doc['my_dense_vector'])",
          "params": {
            "queryVector": [4, 3.4, -0.2]
          }
        }
      }
  
negative.code:         "match_all": {}
        },
        "script": {
          "source": "cosineSimilaritySparse(params.query_vector, doc['my_sparse_vector']) + 1.0",
          "params": {
            "query_vector": {"2": 0.5, "10" : 111.3, "50": -1.3, "113": 14.8, "4545": 156.0}
          }
        }
      }
  