`isOtherModeledArgument` and `isArgumentToBuiltinFunction` contained the old logic for selecting negative endpoints for training.
These can now be deleted, and replaced by a single base class that collects all EndpointCharacteristics that are currently used to indicate negative training samples: `OtherModeledArgumentCharacteristic`.
This in turn lets us delete code from `StandardEndpointFilters` that effectively said that endpoints that are high-confidence non-sinks shouldn't be scored at inference time, either.
