diff --git a/moptipy/evaluation/selector.py b/moptipy/evaluation/selector.py
index c3f3069e0..afab84ddd 100644
--- a/moptipy/evaluation/selector.py
+++ b/moptipy/evaluation/selector.py
@@ -9,6 +9,13 @@
 offered by this module provides the functionality to make such a selection.
 It may be a bit slow, but hopefully it will pick the largest possible
 consistent sub-selection or, at least, get close to it.
+
+The current method to select the data is rather heuristic. It is based on
+iteratively deleting those data elements whose configuration elements appear
+the least often. This is computed in absolute terms. I actually think
+normalizing this score should be better, but seemingly using the absolute raw
+score creates larger consistent datasets. So for now, this is how we will do
+it.
 """
 
 from collections import Counter
@@ -247,7 +254,7 @@ def select_consistent(data: Iterable[T], log: bool = True) -> list[T]:
     source.sort(key=lambda x: x[0])
     count: int = list.__len__(source)
     if log:
-        logger(f"Found {source} records of data.")
+        logger(f"Found {count} records of data.")
 
     set_l: Final[int] = set.__len__({x[0] for x in source})
     if set_l != count:
diff --git a/moptipy/version.py b/moptipy/version.py
index 2cf6864c3..c037144bb 100644
--- a/moptipy/version.py
+++ b/moptipy/version.py
@@ -2,4 +2,4 @@
 from typing import Final
 
 #: the version string of `moptipy`
-__version__: Final[str] = "0.9.125"
+__version__: Final[str] = "0.9.126"