The Best Match sort order is based on an algorithm that analyzes each PubMed citation found with your search terms. For each search query, "weight" is calculated for citations depending on how many search terms are found and in which fields they are found. In addition, recently-published articles are given a somewhat higher weight for sorting. The top articles returned by the weighted term frequency algorithm are then re-ranked for better relevance by a machine-learning algorithm.
The learned ranking algorithm combines over 150 signals that are helpful for finding best matching results. Most of these signals are computed from the query-document term pairs, e.g. number of term matches between the query and the document, while others are either specific to a document, e.g. publication type; publication year, or query, e.g. query length.
Best Match is not designed for comprehensive or systematic searches.
For more information on Best Match, please see the following article in the NLM Technical Bulletin:
For more details on how Best Match retrieves and ranks results, please see the article, "Best Match: New relevance search for PubMed"