Took out comment from appendix.

paper/appendix.tex

@@ -202,10 +202,10 @@ The Gaussians were restricted to the positive real axis and both had mean $0$ an
 
 \section{Independent decision maker}\label{sec:independent}
 
+%TAKING OUT THIS COMMENT, MICHAEL(?) HAS ADDED THE POINT IN RELATED WORK
+%\rcomment{Similar decision maker has been proposed by \citet{kleinberg2018human}, see p. 256. They formalize the decision making threshold for the decision maker as a trade-off point between the costs of incarceration and committing a crime (as evaluated by that judge).}
 
-\rcomment{Similar decision maker has been proposed by \citet{kleinberg2018human}, see p. 256. They formalize the decision making threshold for the decision maker as a trade-off point between the costs of incarceration and committing a crime (as evaluated by that judge).}
-
-In section \ref{sec:decisionmakers} we presented an {\it independent} decision maker. 
+In section \ref{sec:decisionmakers} we formulated an {\it independent} decision maker. 
 %
 Here we motivate it.
 %

paper/experiments.tex

@@ -56,7 +56,7 @@ Additional noise is added to the outcome of each case via $e_\outcome$, which wa
 %\acomment{Like this: To add noise to the outcomes we flipped the outcomes with probability X. Or: To add noise to the outcomes, we included a noise term from $\gaussian{0}{0.1}$ into the logistic regression formula for each subject. In a way that I can do it without being confused. Now I am because epsilon is no longer in the formulas.}
 
 
-\subsection{Decision Makers}
+\subsection{Decision Makers} \label{sec:decisionmakers}
 \label{sec:dm_exps}
 
 Our experimentation involves two categories of decision makers: (i) the set of decision makers \humanset, the decisions of which are reflected in a dataset, and (ii) the decision maker \machine, whose performance is to be evaluated on the log of cases decided by \humanset.