Look for vectors closest to this.
When using the target (with or without context), the integer part of the score represents the rank with respect to the context, while the decimal part of the score relates to the distance to the target.
Pairs of { positive, negative } examples to constrain the search.
When using only the context (without a target), a special search - called context search - is performed where pairs of points are used to generate a loss that guides the search towards the zone where most positive examples overlap. This means that the score minimizes the scenario of finding a point closer to a negative than to a positive part of a pair.
Since the score of a context relates to loss, the maximum score a point can get is 0.0, and it becomes normal that many points can have a score of 0.0.
For discovery search (when including a target), the context part of the score for each pair is calculated +1 if the point is closer to a positive than to a negative part of a pair, and -1 otherwise.