I'm curious how the search results rankings work, doesn't look like it's based on date or number of citations, but seems to be deterministic (persists over multiple searches). I did a keyword search using one word.
It uses a vector search approach. Your query is embedded in a vector space using a language model and we find the closest vector to the query from the PubMed papers. This is a good summary of the techniques: https://learn.microsoft.com/en-us/azure/search/vector-search.... There are a couple more tricks but this is the gist.
The nice part is that this approach allows you to find relevant papers to your question. E.g, you can ask "Can secondhand smoke cause AMD?" and the very first few papers are answering your question (https://pubmedisearch.com/share/Can%20secondhand%20smoke%20c...). The more specific question, the better. :)
I'm curious how the search results rankings work, doesn't look like it's based on date or number of citations, but seems to be deterministic (persists over multiple searches). I did a keyword search using one word.