# HG changeset patch
# User Robert McIntyre <rlm@mit.edu>
# Date 1399016053 14400
# Node ID c14545acdfba62900c8d84289dd5d8b02e8fc4ee
# Parent  0b891e0dd8096f77094502ffd81f997c481b808e
minor edit.

diff -r 0b891e0dd809 -r c14545acdfba thesis/cortex.org
--- a/thesis/cortex.org	Thu May 01 23:41:41 2014 -0400
+++ b/thesis/cortex.org	Fri May 02 03:34:13 2014 -0400
@@ -3209,13 +3209,14 @@
 
   After about 1 minute of manual training, I was able to achieve 95%
   accuracy on manual testing of the worm using =init-interactive= and
-  =test-empathy-accuracy=. The majority of errors are near the
-  boundaries of transitioning from one type of action to another.
-  During these transitions the exact label for the action is more open
-  to interpretation, and disagreement between empathy and experience
-  is essentially irrelevant at this point, giving a practical
-  identification accuracy of even higher than 95%. When I watch this
-  system myself, I generally see no errors in action identification.
+  =test-empathy-accuracy=. The majority of disagreements are near the
+  transition boundaries from one type of action to another.  During
+  these transitions the exact label for the action is often unclear,
+  and disagreement between empathy and experience is practically
+  irrelevant. Thus, the system's effective identification accuracy is
+  even higher than 95%. When I watch this system myself, I generally
+  see no errors in action identification compared to my own judgment
+  of what the worm is doing.
 
 ** Digression: Learning touch sensor layout through free play