diff --git a/domain_of_applicability.ipynb b/domain_of_applicability.ipynb
index 16db082a1f29fbbe546f4f89b149b2c862e35d49..8da3e3ec5dc29603c922c9cd90f0136a370a9126 100644
--- a/domain_of_applicability.ipynb
+++ b/domain_of_applicability.ipynb
@@ -1122,7 +1122,7 @@
     "\n",
     "To show the trade off between coverage of the DA and the error reduction within, controlled by the $\\gamma$ value, a DA analysis is performed for $\\gamma$ values ranging from 0.2 to 0.66. The following code generates all these files. \n",
     "\n",
-    "**WARNING: The next cell will take a long time to run (more than 2h). Therefore the results have been pre-calculated and stored, so that running with the default setting can be skipped.**"
+    "**WARNING: The next cell will take a long time to run (more than 2h). Therefore the results have been pre-calculated and stored, so that running with the default setting can be skipped. Please uncomment the following cell only if you wish to repeat the whole calculation.**"
    ]
   },
   {
@@ -1131,14 +1131,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "for gamma in np.linspace(0.2, 0.66, 16):\n",
-    "    update_gamma(gamma)\n",
-    "    for model in models:\n",
-    "        rm_old_files(model)\n",
-    "        run_analysis(model)\n",
-    "    data_summary = summarize_data()\n",
+    "# for gamma in np.linspace(0.2, 0.66, 16):\n",
+    "#     update_gamma(gamma)\n",
+    "#     for model in models:\n",
+    "#         rm_old_files(model)\n",
+    "#         run_analysis(model)\n",
+    "#     data_summary = summarize_data()\n",
     "    \n",
-    "    generate_table(data_summary, gamma)"
+    "#     generate_table(data_summary, gamma)"
    ]
   },
   {
@@ -1216,7 +1216,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.7.11"
   }
  },
  "nbformat": 4,