Remove references to the supplement in the main paper

calculus.tex

@@ -38,7 +38,7 @@
 
 Limits are computed with the \verb|limit| function. The limit module
 implements the Gruntz algorithm~\cite{Gruntz1996limits} for computing symbolic
-limits (a description of the Gruntz algorithm may be found in the supplement).
+limits.
 For example, the following computes
 $\lim\limits_{x\to \infty} x\sin(\frac{1}{x})=1$. Note that SymPy denotes
 $\infty$ as \verb|oo|.

matrices.tex

@@ -46,6 +46,3 @@
 inference, they provide powerful reasoning over invertibility,
 semi-definiteness, orthogonality, etc., which are valuable in the construction
 of numerical linear algebra systems.
-
-More examples for \verb|Matrix| and \verb|BlockMatrix| may be found in the
-supplement.

paper.tex

@@ -84,7 +84,6 @@ \section{Features}
 %%
 %% Quick overview of the main modules, what it can do and so on. It should probably provide examples how to use sympy.
 %%
-%% See also the supplement (below)
 
 \input{features}
 

polys.tex

@@ -32,6 +32,3 @@
 $K[x_0][x_1]\dotso[x_n]$. Note that despite this, the coefficient domain $K$,
 can be a multivariate polynomial domain as well. The dense recursive
 representation in Python gets inefficient as the number of variables increases.
-
-Some examples for the \texttt{sympy.polys} module can be found in the
-supplement.

solvers.tex

@@ -31,6 +31,3 @@
 \texttt{solve}. There are certain features which are implemented in
 \texttt{solve} that are not yet implemented in \texttt{solveset}. Notably,
 these include nonlinear multivariate system and transcendental equations.
-
-More examples of \texttt{solveset} and \texttt{solve} can be found in the
-supplement.