The cross_fields scoring type can produce negative scores when some documents
are missing fields. When blending term document frequencies, we take the maximum
document frequency across all fields. If one field appears in fewer documents
than another, this means that its IDF can become negative. This is because IDF
is calculated as `Math.log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5))`

This change adjusts the docFreq for each field to `Math.min(docCount, docFreq)`
so that the IDF can never become negative. It makes sense that the term document
frequency should never exceed the number of documents containing the field.