A news aggregation service uses a language model to generate three different summary options for each article. To improve the quality of the summaries shown to users, the service employs human editors to review thousands of these generated summaries and assign each one a 'quality' score from 1 (poor) to 5 (excellent). Based on this scenario, propose a method for using this scored dataset to automatically select the best summary for future articles. What specific role would the trained component play in the final system?