fix admonition

docs/src/stochastic_forcing.md

@@ -53,7 +53,7 @@ with ``W_t`` a Brownian motion or Wiener process, can be written in an integral
     2. Stationarity. The statistical distribution of the increment ``W_{t+s} − W_s`` does not depend on  ``s`` (and so is identical in distribution to ``W_t``).
     3. Gaussianity. ``W_t`` is a Gaussian process with mean ``\langle W_t \rangle = 0`` and covariance ``\langle W_t W_s \rangle = \min(t, s)``.
 
-!!! tip Notation, e.g., ``x_t``
+!!! tip "Notation, e.g., ``x_t``"
     It's common to use notation ``x_t`` to denote explicit ``t``-dependence of variable ``x``. Not to be confused with the other common usage of subscripts for denoting partial differentiation.
 
 The last integral in the integral representation of a SDE expression above is a stochastic integral