Added explanation of scores and backends to tm examples

Author: maurerv

doc/quickstart/matching/particle_picking.rst

@@ -125,9 +125,9 @@ The code below will run template matching, taking about 1-2 minutes on a consume
 
 .. warning::
 
-    When using non-spherical masks, add ``--score FLC``, or consult the :ref:`scoring functions <scoring-functions>`.
+    When using non-spherical masks, add ``--score FLC``, or consult the :ref:`scoring functions <scoring-table>`.
 
-You can inspect the results in the GUI by clicking the *Import Pickle* button. The figure below shows a lowpass-filtered representation of the tomogram subset on the left and the corresponding template matching scores on the right. Bright spots in the score map indicate potential ribosome locations, the brighter the spot the better the match.
+You can inspect the results in the GUI by clicking the *Import Pickle* button. The figure below shows the deconvolved data on the left and the corresponding template matching scores on the right. Bright spots in the score map indicate potential ribosome locations, the brighter the spot the better the match.
 
 Overall, the majority of ribosomes appear to be accounted for. However, note that
 

doc/quickstart/matching/summary.rst

@@ -18,7 +18,7 @@ Summary
 ``preprocess.py`` enables template generation, masks can be created interactively using ``preprocessor_gui.py`` or the API.
 
 
-.. _scoring-functions:
+.. _scoring-table:
 
 Scoring Functions
 -----------------