Yes, and yes.
The results are sorted by similarity according to the metric used (cosine, euclidean, dotproduct), and by using the new dot operator you can also compute the score in results (the distance according to the metric, so lower distance = higher score). We may simplify this so including custom math functions in the result is not required. You can also return the vectors in a query, and compute custom scores or re-ordering in a client.
I see this as a likely replacement for any keyword or text search, so that relevance-based semantic results come back instead of pure keyworkd or term matches.