diff --git a/docs/examples/emulator/robustgasp/plot_scalargasp.py b/docs/examples/emulator/robustgasp/plot_scalargasp.py
index 7e0b58992b629291d461f6c8a0d51b0e8ed3502d..a9baa354a95e8040d9f3a951c7bd235412e16c55 100644
--- a/docs/examples/emulator/robustgasp/plot_scalargasp.py
+++ b/docs/examples/emulator/robustgasp/plot_scalargasp.py
@@ -115,10 +115,10 @@ plt.tight_layout()
 
 # %% md
 #
-# Above example shows how to train a GP emulator based on noise-free training data,
-# which is often the case of emulating a deterministic simulator. If you are dealing
-# with noisy training data, you can
+# .. tip:: Above example shows how to train a GP emulator based on noise-free training data,
+#    which is often the case of emulating a deterministic simulator. If you are dealing
+#    with noisy training data, you can
 #
-# - set the parameter ``nugget`` to a desired value, or
-# - set ``nugget`` to :math:`0` and ``nugget_est`` to `True`, meaning that ``nugget``
-#   is estimated from the noisy training data.
\ No newline at end of file
+#     - set the parameter ``nugget`` to a desired value, or
+#     - set ``nugget`` to :math:`0` and ``nugget_est`` to `True`, meaning that ``nugget``
+#       is estimated from the noisy training data.
\ No newline at end of file