Reduce repetition of sentence

I am not sure if this flows better, so please give feedback on
this change.

Author: SAKavli

docs/everest/introduction.rst

@@ -32,7 +32,7 @@ Considerations regarding the usage of Everest
 
 Everest can assist the decision makers when there are many outcomes or decisions that need to be made. If the decision and outcome is limited or easy, then Everest may not be needed as one can evaluate the outcomes with a heuristic approach. However, it is unlikely that one can easily find few outcomes or real optimized, robust strategies using this “manual” approach when uncertainty is involved. In the following sections we will discuss the use of Everest in different cases and some of the "ifs and buts " associated with the application of the tool.
 
-The power of the Everest tool is to assist in optimizing strategies while capturing the underlying reservoir uncertainty, which is modelled by an ensemble of realizations. A crucial factor for the success of the optimization is to have good enough model quality and the uncertainty well represented - i.e., to span the current understanding or knowledge of the reservoir uncertainty. Moreover, the greater the reservoir complexity, the more important it is to have many model realizations in the ensemble, i.e., to span the actual reservoir uncertainty. The alternative might lead to a situation where the strategy is not representative. The essential takeaways is that Everest cannot improve a model's quality or uncertainty representation, and that the quality of the Everest optimization results is dependent on the quality of the underlying model and uncertainty representation.
+The power of the Everest tool is to assist in optimizing strategies while capturing the underlying reservoir uncertainty, which is modelled by an ensemble of realizations. A crucial factor for the success of the optimization is to have good enough model quality and the uncertainty well represented - i.e., to span the current understanding or knowledge of the reservoir uncertainty. Moreover, the greater the reservoir complexity, the more important it is to have many model realizations in the ensemble, i.e., to span the actual reservoir uncertainty. The alternative might lead to a situation where the strategy is not representative. The essential takeaway is that Everest's results depend on — but does not improve a model's quality or uncertainty representation.
 
 When doing experiments that involve tuning specific parameters, it is advisable to begin with a coarse-grained approach when adjusting control variables. Initially, one might consider modifying the parameters at long intervals, such as every several years or at key points in the process timeline. This sets a foundational structure for the optimization without overwhelming the algorithm with too many variables.