add comment to tutorial

Author: EdwinB12

docs/tutorials/emulation/01_quickstart.ipynb

@@ -212,7 +212,16 @@
    "source": [
     "# Choosing an Emulator\n",
     "\n",
-    "From this list, we can choose an emulator based on the index from the summary dataframe, or quickly get the best performing one using the `best_result` function, which picks based on the `r2_test` metric by default. "
+    "From this list, we can choose an emulator based on the index from the summary dataframe, or quickly get the best performing one using the `best_result` function, which picks based on the `r2_test` metric by default. \n",
+    "\n",
+    "<details>\n",
+    "\n",
+    "<summary>Choosing a metric for determining the best model</summary>\n",
+    "\n",
+    "`metric_name` can be set in the `best_result` method to choose what metric is used to determine the best model: \n",
+    "\n",
+    "`ae.best_result(metric_name='rmse')`\n",
+    "</details>"
    ]
   },
   {
@@ -225,16 +234,6 @@
     "print(\"Model with id: \", best.id, \" performed best: \", best.model_name)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "best = ae.best_result(metric=\"RMSE\")\n",
-    "print(\"Model with id: \", best.id, \" performed best: \", best.model_name)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,