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index 7f37b5b5..eaf6fec9 100644
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@@ -18483,7 +18483,7 @@
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@@ -18498,14 +18498,14 @@
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@@ -18520,13 +18520,13 @@
             "_view_name": "HTMLView",
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-            "layout": "IPY_MODEL_41d31b0bd5134e198aac234022f700b2",
+            "layout": "IPY_MODEL_fd1668d9e47f4c53882d670975ce061e",
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-            "style": "IPY_MODEL_d8e3374ff2cd45ada94f99a17102bd32",
+            "style": "IPY_MODEL_50b75f18541240d28a4b10f245b594f8",
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@@ -18542,15 +18542,15 @@
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@@ -18565,13 +18565,13 @@
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-            "style": "IPY_MODEL_a38f7dd92d704a2aad67bb2947600b8f",
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+            "style": "IPY_MODEL_2af170da050f47e5baa6c2bbafe130ac",
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@@ -18623,7 +18623,7 @@
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@@ -18675,7 +18675,7 @@
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@@ -18690,7 +18690,7 @@
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@@ -18742,7 +18742,7 @@
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@@ -18758,7 +18758,7 @@
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@@ -18810,7 +18810,7 @@
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@@ -18861,7 +18861,7 @@
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-        "outputId": "fd594291-156e-42f1-b46c-d79c5417d9bc"
+        "outputId": "63956c0f-73d6-47ff-fd57-8482100191bf"
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       "execution_count": 2,
       "outputs": [
@@ -18872,44 +18872,12 @@
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             "remote: Enumerating objects: 42, done.\u001b[K\n",
             "remote: Total 42 (delta 0), reused 0 (delta 0), pack-reused 42\u001b[K\n",
-            "Receiving objects: 100% (42/42), 1.57 MiB | 19.38 MiB/s, done.\n",
+            "Receiving objects: 100% (42/42), 1.57 MiB | 19.86 MiB/s, done.\n",
             "Resolving deltas: 100% (10/10), done.\n"
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-    {
-      "cell_type": "code",
-      "source": [
-        "\n",
-        "\n",
-        "os.getcwd()"
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-          "height": 35
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-      "execution_count": 3,
-      "outputs": [
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-          "data": {
-            "text/plain": [
-              "'/content'"
-            ],
-            "application/vnd.google.colaboratory.intrinsic+json": {
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-          },
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-          "execution_count": 3
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     {
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@@ -18931,7 +18899,7 @@
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-        "outputId": "634797a3-038e-4c24-fb5e-19970e3cbf0c"
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       "execution_count": 5,
       "outputs": [
@@ -19086,7 +19054,7 @@
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-        "outputId": "cfd47fc7-2bec-418d-899b-3e9c208aeffb"
+        "outputId": "b7e3830b-f1d4-49a9-bcd8-7468794a33bd"
       },
       "execution_count": 7,
       "outputs": [
@@ -19099,9 +19067,8 @@
             "remote: Counting objects: 100% (1043/1043), done.\u001b[K\n",
             "remote: Compressing objects: 100% (279/279), done.\u001b[K\n",
             "remote: Total 10388 (delta 584), reused 963 (delta 523), pack-reused 9345\u001b[K\n",
-            "Receiving objects: 100% (10388/10388), 367.01 MiB | 32.27 MiB/s, done.\n",
-            "Resolving deltas: 100% (6749/6749), done.\n",
-            "Updating files: 100% (382/382), done.\n"
+            "Receiving objects: 100% (10388/10388), 367.01 MiB | 21.28 MiB/s, done.\n",
+            "Resolving deltas: 100% (6749/6749), done.\n"
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@@ -19116,7 +19083,7 @@
         "colab": {
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-        "outputId": "506b14a5-8905-4b23-d139-dc1884c16ff7"
+        "outputId": "78a3052e-98f5-41a4-c791-e1d07217ef41"
       },
       "execution_count": 8,
       "outputs": [
@@ -19130,11 +19097,11 @@
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+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m16.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25hRequirement already satisfied: scipy>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from matbench==0.6) (1.11.4)\n",
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             "\u001b[?25hRequirement already satisfied: scikit-learn>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matbench==0.6) (1.2.2)\n",
             "Requirement already satisfied: numpy<2,>=1.23 in /usr/local/lib/python3.10/dist-packages (from matminer>=0.7.4->matbench==0.6) (1.25.2)\n",
             "Requirement already satisfied: requests~=2.31 in /usr/local/lib/python3.10/dist-packages (from matminer>=0.7.4->matbench==0.6) (2.31.0)\n",
@@ -19142,14 +19109,14 @@
             "Requirement already satisfied: tqdm~=4.66 in /usr/local/lib/python3.10/dist-packages (from matminer>=0.7.4->matbench==0.6) (4.66.4)\n",
             "Collecting pymongo~=4.5 (from matminer>=0.7.4->matbench==0.6)\n",
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+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m670.0/670.0 kB\u001b[0m \u001b[31m24.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25hCollecting scikit-learn>=1.0.1 (from matbench==0.6)\n",
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             "Building wheels for collected packages: matbench\n",
             "  Building wheel for matbench (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for matbench: filename=matbench-0.6-py3-none-any.whl size=5449480 sha256=8eb4d6b440ead1d42a0e22ad53f321117f04ca698d73a126513b36775ec3c5b9\n",
-            "  Stored in directory: /tmp/pip-ephem-wheel-cache-_27kz6xs/wheels/0d/71/69/39ae3b7c60edd18e46ed290a09bc2fe0c344372520cd165c70\n",
+            "  Created wheel for matbench: filename=matbench-0.6-py3-none-any.whl size=5449480 sha256=21118a50e093168124303d796628ed4d15a24ef227a5125d3c15d93dcf56ecc9\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-o8vzp4k6/wheels/0d/71/69/39ae3b7c60edd18e46ed290a09bc2fe0c344372520cd165c70\n",
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             "Installing collected packages: uncertainties, spglib, ruamel.yaml.clib, palettable, monty, latexcodec, dnspython, scikit-learn, ruamel.yaml, pymongo, pybtex, pymatgen, matminer, matbench\n",
             "\u001b[33m  WARNING: The scripts pybtex, pybtex-convert and pybtex-format are installed in '/root/.local/bin' which is not on PATH.\n",
@@ -19234,7 +19201,7 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "outputId": "efef4a6d-1539-4b9b-c843-dfc247ba3395"
+        "outputId": "19c35786-9fa1-4ddd-8011-5e86a3c121c1"
       },
       "execution_count": 10,
       "outputs": [
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@@ -19276,10 +19243,10 @@
             "  Downloading mccabe-0.6.1-py2.py3-none-any.whl (8.6 kB)\n",
             "Collecting pycodestyle<2.9.0,>=2.8.0 (from flake8==4.0.1->-r requirements-dev.txt (line 7))\n",
             "  Downloading pycodestyle-2.8.0-py2.py3-none-any.whl (42 kB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.1/42.1 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.1/42.1 kB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25hCollecting pyflakes<2.5.0,>=2.4.0 (from flake8==4.0.1->-r requirements-dev.txt (line 7))\n",
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-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.7/69.7 kB\u001b[0m \u001b[31m10.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.7/69.7 kB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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@@ -19296,13 +19263,13 @@
             "INFO: pip is looking at multiple versions of matminer to determine which version is compatible with other requirements. This could take a while.\n",
             "Collecting matminer>=0.7.4 (from matbench==0.6)\n",
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-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m12.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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             "\u001b[?25hCollecting pandas~=1.5 (from matminer>=0.7.4->matbench==0.6)\n",
             "  Downloading pandas-1.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.1 MB)\n",
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+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.1/12.1 MB\u001b[0m \u001b[31m81.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25hCollecting matminer>=0.7.4 (from matbench==0.6)\n",
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-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m58.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.4/1.4 MB\u001b[0m \u001b[31m12.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25hRequirement already satisfied: future in /usr/local/lib/python3.10/dist-packages (from matminer>=0.7.4->matbench==0.6) (0.18.3)\n",
             "Requirement already satisfied: pymatgen in /root/.local/lib/python3.10/site-packages (from matminer>=0.7.4->matbench==0.6) (2024.5.1)\n",
             "Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=1.0.1->matbench==0.6) (1.4.2)\n",
@@ -19313,19 +19280,19 @@
             "INFO: pip is looking at multiple versions of pymatgen to determine which version is compatible with other requirements. This could take a while.\n",
             "Collecting pymatgen (from matminer>=0.7.4->matbench==0.6)\n",
             "  Downloading pymatgen-2024.4.13-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m12.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m76.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.4.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m14.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m57.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.3.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m38.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m38.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.2.23-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m54.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.2.20-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m13.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m19.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.2.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (10.0 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m6.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.0/10.0 MB\u001b[0m \u001b[31m51.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Downloading pymatgen-2024.1.27.tar.gz (7.2 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m97.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m20.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
             "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
             "  Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
@@ -19357,10 +19324,10 @@
             "Requirement already satisfied: latexcodec>=1.0.4 in /root/.local/lib/python3.10/site-packages (from pybtex->pymatgen->matminer>=0.7.4->matbench==0.6) (3.0.0)\n",
             "Building wheels for collected packages: matbench, pymatgen\n",
             "  Building editable for matbench (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for matbench: filename=matbench-0.6-0.editable-py3-none-any.whl size=3622 sha256=9faa20e2edea9128712a28871e4f9de0b8a9dd24c7a49a3aeb03a74cdb88ac3e\n",
-            "  Stored in directory: /tmp/pip-ephem-wheel-cache-id9pupbj/wheels/0d/71/69/39ae3b7c60edd18e46ed290a09bc2fe0c344372520cd165c70\n",
+            "  Created wheel for matbench: filename=matbench-0.6-0.editable-py3-none-any.whl size=3622 sha256=2543740d086d28759c38528a7a709a1f9380a26a1f71387e128484223259d533\n",
+            "  Stored in directory: /tmp/pip-ephem-wheel-cache-8dxz848k/wheels/0d/71/69/39ae3b7c60edd18e46ed290a09bc2fe0c344372520cd165c70\n",
             "  Building wheel for pymatgen (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for pymatgen: filename=pymatgen-2024.1.27-cp310-cp310-linux_x86_64.whl size=8767375 sha256=52f748f354052fc925f62a0dc53b0197421299982ff51b46efbf7880fb6d99db\n",
+            "  Created wheel for pymatgen: filename=pymatgen-2024.1.27-cp310-cp310-linux_x86_64.whl size=8767378 sha256=9fe1528bfeb13e80a7c4e417544d291be54286e3c6891b56f4305b648270faf3\n",
             "  Stored in directory: /root/.cache/pip/wheels/ee/58/93/14b5660717b7cf0223df12fcdf754c2ee6aa4daba441b337f1\n",
             "Successfully built matbench pymatgen\n",
             "Installing collected packages: mccabe, wheel, pyflakes, pycodestyle, pathspec, mypy-extensions, monty, isort, coverage, pandas, flake8, black, pymatgen, matminer, matbench\n",
@@ -19415,7 +19382,7 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "AbCvuaICLFaw",
-        "outputId": "961ab1c0-b9da-44ca-cc72-586ef399cd0f"
+        "outputId": "30c87ce5-79ff-4b10-9633-4d9d9935d63c"
       },
       "execution_count": 11,
       "outputs": [
@@ -19444,7 +19411,7 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "h3DfACJ1LPK9",
-        "outputId": "b4cffa60-aa35-4013-e766-c90adee1a715"
+        "outputId": "ee9f24e5-9342-4dfb-c126-dea6002f0a8c"
       },
       "execution_count": 12,
       "outputs": [
@@ -19518,9 +19485,9 @@
           "base_uri": "https://localhost:8080/",
           "height": 658
         },
-        "outputId": "a028548b-c35e-41f5-df46-ab31aaed9b2e"
+        "outputId": "05c48a03-777d-49a8-8b58-27bec5e2e562"
       },
-      "execution_count": 16,
+      "execution_count": 18,
       "outputs": [
         {
           "output_type": "stream",
@@ -19529,16 +19496,13 @@
             "Collecting scikit-learn==1.5\n",
             "  Using cached scikit_learn-1.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.3 MB)\n",
             "Collecting numpy>=1.19.5 (from scikit-learn==1.5)\n",
-            "  Downloading numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m18.2/18.2 MB\u001b[0m \u001b[31m17.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hCollecting scipy>=1.6.0 (from scikit-learn==1.5)\n",
-            "  Downloading scipy-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (38.6 MB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m38.6/38.6 MB\u001b[0m \u001b[31m8.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hCollecting joblib>=1.2.0 (from scikit-learn==1.5)\n",
-            "  Downloading joblib-1.4.2-py3-none-any.whl (301 kB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m301.8/301.8 kB\u001b[0m \u001b[31m35.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25hCollecting threadpoolctl>=3.1.0 (from scikit-learn==1.5)\n",
-            "  Downloading threadpoolctl-3.5.0-py3-none-any.whl (18 kB)\n",
+            "  Using cached numpy-1.26.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB)\n",
+            "Collecting scipy>=1.6.0 (from scikit-learn==1.5)\n",
+            "  Using cached scipy-1.13.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (38.6 MB)\n",
+            "Collecting joblib>=1.2.0 (from scikit-learn==1.5)\n",
+            "  Using cached joblib-1.4.2-py3-none-any.whl (301 kB)\n",
+            "Collecting threadpoolctl>=3.1.0 (from scikit-learn==1.5)\n",
+            "  Using cached threadpoolctl-3.5.0-py3-none-any.whl (18 kB)\n",
             "Installing collected packages: threadpoolctl, numpy, joblib, scipy, scikit-learn\n",
             "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
             "cudf-cu12 24.4.1 requires pandas<2.2.2dev0,>=2.0, but you have pandas 1.5.3 which is incompatible.\u001b[0m\u001b[31m\n",
@@ -19551,7 +19515,10 @@
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/sklearn already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/threadpoolctl.py already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/joblib-1.4.2.dist-info already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/scikit_learn-1.5.0.dist-info already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/scipy already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/scipy-1.13.1.dist-info already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/numpy-1.26.4.dist-info already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/numpy already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/scipy.libs already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
             "\u001b[0m\u001b[33mWARNING: Target directory /usr/local/lib/python3.10/dist-packages/bin already exists. Specify --upgrade to force replacement.\u001b[0m\u001b[33m\n",
@@ -19567,7 +19534,7 @@
                   "joblib"
                 ]
               },
-              "id": "abc79fed5601455dba6602de390012fd"
+              "id": "b10b4d1bee714f3f8d9d2cc94cf00a2f"
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@@ -19609,7 +19576,7 @@
       "metadata": {
         "id": "mmcr8nDFBpIV"
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-      "execution_count": 13,
+      "execution_count": 1,
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     {
@@ -19622,7 +19589,7 @@
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         "id": "tUYFfnGjDHwn"
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-      "execution_count": null,
+      "execution_count": 2,
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     {
@@ -19633,7 +19600,7 @@
       "metadata": {
         "id": "WNgvKuttDPL-"
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-      "execution_count": 1,
+      "execution_count": 3,
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     {
@@ -19655,7 +19622,7 @@
       "metadata": {
         "id": "94r1T6YADSzO"
       },
-      "execution_count": 2,
+      "execution_count": 4,
       "outputs": []
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     {
@@ -19702,9 +19669,9 @@
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
-        "outputId": "3386b7f8-7319-4ef8-b3f9-1f9e36455309"
+        "outputId": "8f63b269-742c-4ed2-84a1-ee35feb92bf6"
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-      "execution_count": null,
+      "execution_count": 5,
       "outputs": [
         {
           "output_type": "stream",
@@ -19717,7 +19684,7 @@
           "output_type": "stream",
           "name": "stderr",
           "text": [
-            "Fetching https://ml.materialsproject.org/projects/matbench_steels.json.gz in MB: 0.010239999999999999MB [00:00,  3.64MB/s]     \n"
+            "Fetching https://ml.materialsproject.org/projects/matbench_steels.json.gz in MB: 0.010239999999999999MB [00:00,  3.07MB/s]     \n"
           ]
         }
       ]
@@ -19737,9 +19704,9 @@
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-        "outputId": "995fbec2-87c7-43c2-cedf-4d56069b44c3"
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@@ -19773,9 +19740,9 @@
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-        "outputId": "96c7f4a6-763e-4e79-b193-d063fbdafc58"
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       "outputs": [
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@@ -19790,7 +19757,7 @@
             ],
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-              "  <div id=\"df-886a9672-2a23-449b-89b6-e87c3ae76cef\" class=\"colab-df-container\">\n",
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               "    <div>\n",
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@@ -19845,7 +19812,7 @@
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@@ -19897,12 +19864,12 @@
               "\n",
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-              "        document.querySelector('#df-886a9672-2a23-449b-89b6-e87c3ae76cef button.colab-df-convert');\n",
+              "        document.querySelector('#df-9e27a320-add7-4c70-a9b8-a604c9d92329 button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-886a9672-2a23-449b-89b6-e87c3ae76cef');\n",
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               "        const dataTable =\n",
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@@ -19922,8 +19889,8 @@
               "  </div>\n",
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               "\n",
@@ -20042,7 +20009,7 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-cd1153d2-a1bb-40e5-9600-b90b844bf051 button');\n",
+              "        document.querySelector('#df-b80b2d1d-33a2-4deb-895b-92ac5d674ae5 button');\n",
               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
@@ -20058,7 +20025,7 @@
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+          "execution_count": 7
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@@ -20072,9 +20039,9 @@
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@@ -20101,7 +20068,7 @@
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-      "execution_count": null,
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@@ -20114,7 +20081,7 @@
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-      "execution_count": null,
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@@ -20130,7 +20097,7 @@
       "metadata": {
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-      "execution_count": null,
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@@ -20145,23 +20112,23 @@
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@@ -20172,7 +20139,7 @@
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@@ -20197,7 +20164,7 @@
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@@ -20264,7 +20231,7 @@
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@@ -20316,12 +20283,12 @@
               "\n",
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               "      const buttonEl =\n",
-              "        document.querySelector('#df-542dc1ba-e7c4-4267-b4fe-cccbb4d3dae5 button.colab-df-convert');\n",
+              "        document.querySelector('#df-a274b1a7-4c2a-4802-ba30-665565e507b3 button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-542dc1ba-e7c4-4267-b4fe-cccbb4d3dae5');\n",
+              "        const element = document.querySelector('#df-a274b1a7-4c2a-4802-ba30-665565e507b3');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -20341,8 +20308,8 @@
               "  </div>\n",
               "\n",
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-              "<div id=\"df-1dd1c82e-f705-4f3d-9c4d-1dc7ba79015c\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1dd1c82e-f705-4f3d-9c4d-1dc7ba79015c')\"\n",
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@@ -20461,7 +20428,7 @@
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-              "        document.querySelector('#df-1dd1c82e-f705-4f3d-9c4d-1dc7ba79015c button');\n",
+              "        document.querySelector('#df-1214637a-e183-4431-bcbd-dc178b5df3f1 button');\n",
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@@ -20477,7 +20444,7 @@
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@@ -20493,23 +20460,23 @@
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@@ -20520,7 +20487,7 @@
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@@ -20554,7 +20521,7 @@
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-              "  <div id=\"df-2fc84590-03e8-4ff7-bf87-c068e1f67395\" class=\"colab-df-container\">\n",
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@@ -20724,7 +20691,7 @@
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-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2fc84590-03e8-4ff7-bf87-c068e1f67395')\"\n",
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@@ -20776,12 +20743,12 @@
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               "      const buttonEl =\n",
-              "        document.querySelector('#df-2fc84590-03e8-4ff7-bf87-c068e1f67395 button.colab-df-convert');\n",
+              "        document.querySelector('#df-8604354b-8866-467d-8cd3-6f2b24b9ec75 button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
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               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-2fc84590-03e8-4ff7-bf87-c068e1f67395');\n",
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               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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@@ -20801,8 +20768,8 @@
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-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-bbbe8a2d-61f3-4ea8-8a85-ccedef510686')\"\n",
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@@ -20921,7 +20888,7 @@
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-              "        document.querySelector('#df-bbbe8a2d-61f3-4ea8-8a85-ccedef510686 button');\n",
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@@ -20936,7 +20903,7 @@
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@@ -20953,9 +20920,9 @@
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@@ -21017,7 +20984,7 @@
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-              "  <div id=\"df-5eaf992b-51ac-4965-8e9e-5626aa65b04b\" class=\"colab-df-container\">\n",
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@@ -21259,7 +21226,7 @@
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               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -21311,12 +21278,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-5eaf992b-51ac-4965-8e9e-5626aa65b04b button.colab-df-convert');\n",
+              "        document.querySelector('#df-4cd0158f-53c5-44e1-a4e2-e100b9c72265 button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-5eaf992b-51ac-4965-8e9e-5626aa65b04b');\n",
+              "        const element = document.querySelector('#df-4cd0158f-53c5-44e1-a4e2-e100b9c72265');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -21336,8 +21303,8 @@
               "  </div>\n",
               "\n",
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+              "<div id=\"df-dc0366aa-7a1b-4458-beb0-1dde1b6a2c1d\">\n",
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               "            title=\"Suggest charts\"\n",
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@@ -21456,7 +21423,7 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-7f4f0e88-9202-4626-bf75-f8c842cbc1df button');\n",
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               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
@@ -21472,7 +21439,7 @@
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@@ -21659,12 +21626,12 @@
               "\n",
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-              "        document.querySelector('#df-7a9a427a-2cb5-41d0-9a49-6daafbba7e06 button.colab-df-convert');\n",
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               "      buttonEl.style.display =\n",
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               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
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@@ -21684,8 +21651,8 @@
               "  </div>\n",
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@@ -21820,7 +21787,7 @@
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@@ -21863,7 +21830,7 @@
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@@ -21895,7 +21862,7 @@
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@@ -22044,12 +22011,12 @@
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               "      const buttonEl =\n",
-              "        document.querySelector('#df-9e7a3a0d-292b-429c-9b45-2ed37c73823e button.colab-df-convert');\n",
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               "      buttonEl.style.display =\n",
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-              "        const element = document.querySelector('#df-9e7a3a0d-292b-429c-9b45-2ed37c73823e');\n",
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               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -22069,8 +22036,8 @@
               "  </div>\n",
               "\n",
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@@ -22189,7 +22156,7 @@
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-              "        document.querySelector('#df-8110b30d-613a-452e-b095-af10fd6de863 button');\n",
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               "      quickchartButtonEl.style.display =\n",
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               "    })();\n",
@@ -22205,7 +22172,7 @@
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       "outputs": [
         {
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@@ -22248,7 +22215,7 @@
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@@ -22310,7 +22277,7 @@
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@@ -22480,7 +22447,7 @@
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               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e4fc7c55-5ba3-4fca-b8f4-a4f59b08895d')\"\n",
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@@ -22532,12 +22499,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-e4fc7c55-5ba3-4fca-b8f4-a4f59b08895d button.colab-df-convert');\n",
+              "        document.querySelector('#df-9ed74532-150c-4969-8738-0f46df4e2f29 button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-e4fc7c55-5ba3-4fca-b8f4-a4f59b08895d');\n",
+              "        const element = document.querySelector('#df-9ed74532-150c-4969-8738-0f46df4e2f29');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -22557,8 +22524,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "<div id=\"df-9d8afb46-279f-4526-b5e0-5c2969bb0259\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-9d8afb46-279f-4526-b5e0-5c2969bb0259')\"\n",
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@@ -22677,7 +22644,7 @@
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-              "        document.querySelector('#df-9d8afb46-279f-4526-b5e0-5c2969bb0259 button');\n",
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@@ -22692,7 +22659,7 @@
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@@ -22706,9 +22673,9 @@
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@@ -22720,7 +22687,7 @@
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@@ -22734,9 +22701,9 @@
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@@ -22746,7 +22713,7 @@
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@@ -22760,9 +22727,9 @@
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@@ -22772,7 +22739,7 @@
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@@ -22786,9 +22753,9 @@
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       "outputs": [
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           "output_type": "execute_result",
@@ -22800,7 +22767,7 @@
             ]
           },
           "metadata": {},
-          "execution_count": 32
+          "execution_count": 21
         }
       ]
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@@ -22816,9 +22783,9 @@
           "height": 461
         },
         "id": "4zwuY5BrcKL9",
-        "outputId": "d439181b-0bcb-44ac-95e0-b711caca4f36"
+        "outputId": "67c9f145-cf2f-49f5-b21e-7b446b658ee5"
       },
-      "execution_count": null,
+      "execution_count": 22,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -22854,7 +22821,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-1121c8a2-2acf-4094-a52c-7a6d48bf0234\" class=\"colab-df-container\">\n",
+              "  <div id=\"df-dac399a2-3eaf-4319-8fca-6c524e5f4d1d\" class=\"colab-df-container\">\n",
               "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
@@ -23072,7 +23039,7 @@
               "    <div class=\"colab-df-buttons\">\n",
               "\n",
               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1121c8a2-2acf-4094-a52c-7a6d48bf0234')\"\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dac399a2-3eaf-4319-8fca-6c524e5f4d1d')\"\n",
               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -23124,12 +23091,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-1121c8a2-2acf-4094-a52c-7a6d48bf0234 button.colab-df-convert');\n",
+              "        document.querySelector('#df-dac399a2-3eaf-4319-8fca-6c524e5f4d1d button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-1121c8a2-2acf-4094-a52c-7a6d48bf0234');\n",
+              "        const element = document.querySelector('#df-dac399a2-3eaf-4319-8fca-6c524e5f4d1d');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -23149,8 +23116,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "<div id=\"df-d9978c92-04ca-4b65-9e57-cb76048d9f07\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d9978c92-04ca-4b65-9e57-cb76048d9f07')\"\n",
+              "<div id=\"df-5df1082b-db60-4518-956c-432d4ff21e1e\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5df1082b-db60-4518-956c-432d4ff21e1e')\"\n",
               "            title=\"Suggest charts\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -23269,7 +23236,7 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-d9978c92-04ca-4b65-9e57-cb76048d9f07 button');\n",
+              "        document.querySelector('#df-5df1082b-db60-4518-956c-432d4ff21e1e button');\n",
               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
@@ -23285,7 +23252,7 @@
             }
           },
           "metadata": {},
-          "execution_count": 33
+          "execution_count": 22
         }
       ]
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@@ -23307,9 +23274,9 @@
           "height": 478
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         "id": "J1_tJwtRcPOu",
-        "outputId": "08b80bfd-bae7-4dd1-cab7-569aa335d3de"
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-      "execution_count": null,
+      "execution_count": 23,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -23371,7 +23338,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-af5cc4b6-66f7-4700-9945-0901904c37ba\" class=\"colab-df-container\">\n",
+              "  <div id=\"df-17756949-0d85-449a-aaba-73fd69358d0e\" class=\"colab-df-container\">\n",
               "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
@@ -23685,7 +23652,7 @@
               "    <div class=\"colab-df-buttons\">\n",
               "\n",
               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af5cc4b6-66f7-4700-9945-0901904c37ba')\"\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-17756949-0d85-449a-aaba-73fd69358d0e')\"\n",
               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -23737,12 +23704,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-af5cc4b6-66f7-4700-9945-0901904c37ba button.colab-df-convert');\n",
+              "        document.querySelector('#df-17756949-0d85-449a-aaba-73fd69358d0e button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-af5cc4b6-66f7-4700-9945-0901904c37ba');\n",
+              "        const element = document.querySelector('#df-17756949-0d85-449a-aaba-73fd69358d0e');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -23762,8 +23729,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "<div id=\"df-33fb7324-27f4-4182-979f-5d955578b876\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-33fb7324-27f4-4182-979f-5d955578b876')\"\n",
+              "<div id=\"df-716911d9-cbec-4b05-ac2d-b99e7436f537\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-716911d9-cbec-4b05-ac2d-b99e7436f537')\"\n",
               "            title=\"Suggest charts\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -23882,7 +23849,7 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-33fb7324-27f4-4182-979f-5d955578b876 button');\n",
+              "        document.querySelector('#df-716911d9-cbec-4b05-ac2d-b99e7436f537 button');\n",
               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
@@ -23897,7 +23864,7 @@
             }
           },
           "metadata": {},
-          "execution_count": 36
+          "execution_count": 23
         }
       ]
     },
@@ -23911,9 +23878,9 @@
           "base_uri": "https://localhost:8080/"
         },
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-        "outputId": "1802f545-22df-4515-f819-f62bf1b40db2"
+        "outputId": "74169263-6156-4dec-d5ea-bada476d7076"
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-      "execution_count": null,
+      "execution_count": 24,
       "outputs": [
         {
           "output_type": "stream",
@@ -23964,9 +23931,9 @@
           "height": 932
         },
         "id": "twAWYH6ysBj_",
-        "outputId": "50f7e58b-f952-440f-a71f-bbf61adbd0e3"
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       },
-      "execution_count": null,
+      "execution_count": 25,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -23976,7 +23943,7 @@
             ]
           },
           "metadata": {},
-          "execution_count": 38
+          "execution_count": 25
         },
         {
           "output_type": "display_data",
@@ -23996,7 +23963,7 @@
       "metadata": {
         "id": "IKE3q36IGyCH"
       },
-      "execution_count": null,
+      "execution_count": 25,
       "outputs": []
     },
     {
@@ -24031,7 +23998,7 @@
       "metadata": {
         "id": "ZtRcFSUujIPC"
       },
-      "execution_count": null,
+      "execution_count": 26,
       "outputs": []
     },
     {
@@ -24045,9 +24012,9 @@
           "height": 478
         },
         "id": "5LTOKdu4sZC0",
-        "outputId": "b9a34165-7f05-4dac-e8a7-0fdf1ae9c043"
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       },
-      "execution_count": null,
+      "execution_count": 27,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -24109,7 +24076,7 @@
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-0a85ba42-1aa8-4eff-8ed8-b4ac6fedf338\" class=\"colab-df-container\">\n",
+              "  <div id=\"df-6a364c3c-1a53-4b3b-96c9-783c4fe4378d\" class=\"colab-df-container\">\n",
               "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
@@ -24411,7 +24378,7 @@
               "    <div class=\"colab-df-buttons\">\n",
               "\n",
               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a85ba42-1aa8-4eff-8ed8-b4ac6fedf338')\"\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6a364c3c-1a53-4b3b-96c9-783c4fe4378d')\"\n",
               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -24463,12 +24430,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-0a85ba42-1aa8-4eff-8ed8-b4ac6fedf338 button.colab-df-convert');\n",
+              "        document.querySelector('#df-6a364c3c-1a53-4b3b-96c9-783c4fe4378d button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-0a85ba42-1aa8-4eff-8ed8-b4ac6fedf338');\n",
+              "        const element = document.querySelector('#df-6a364c3c-1a53-4b3b-96c9-783c4fe4378d');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -24488,8 +24455,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "<div id=\"df-d5fe36d0-9914-4072-81e3-174aaffd300a\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d5fe36d0-9914-4072-81e3-174aaffd300a')\"\n",
+              "<div id=\"df-033380c7-56e6-4858-bee5-c8a5660db02e\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-033380c7-56e6-4858-bee5-c8a5660db02e')\"\n",
               "            title=\"Suggest charts\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -24608,7 +24575,7 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-d5fe36d0-9914-4072-81e3-174aaffd300a button');\n",
+              "        document.querySelector('#df-033380c7-56e6-4858-bee5-c8a5660db02e button');\n",
               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
@@ -24624,7 +24591,7 @@
             }
           },
           "metadata": {},
-          "execution_count": 40
+          "execution_count": 27
         }
       ]
     },
@@ -24693,7 +24660,7 @@
       "metadata": {
         "id": "XyFo13gbr8Qs"
       },
-      "execution_count": null,
+      "execution_count": 28,
       "outputs": []
     },
     {
@@ -24706,9 +24673,9 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "sCT9h16AJ5Ub",
-        "outputId": "9fa96d4a-0065-4fa3-f5c6-ac8b66de2714"
+        "outputId": "37e76ef8-5ac0-41c5-b781-65f50719067d"
       },
-      "execution_count": null,
+      "execution_count": 29,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -24720,9 +24687,9 @@
               "  'XGBoost': 109.286921812996,\n",
               "  'HistGradientBoosting': 110.59885613241298,\n",
               "  'AdaBoost': 128.15915510481574,\n",
-              "  'GradientBoosting': 97.97207327577024,\n",
+              "  'GradientBoosting': 97.17688026951241,\n",
               "  'SVR': 246.6394792314533,\n",
-              "  'KernelRidge': 171.38895043089343,\n",
+              "  'KernelRidge': 171.38895002088935,\n",
               "  'BayesianRidge': 238.25470726953395},\n",
               " {'Random Forest': 139.2945539573979,\n",
               "  'Linear Regression': 212.98635368804023,\n",
@@ -24730,9 +24697,9 @@
               "  'XGBoost': 148.68420534170488,\n",
               "  'HistGradientBoosting': 159.44170998201767,\n",
               "  'AdaBoost': 157.81219978064576,\n",
-              "  'GradientBoosting': 132.76270771545163,\n",
+              "  'GradientBoosting': 132.0744346103804,\n",
               "  'SVR': 328.2090895489837,\n",
-              "  'KernelRidge': 240.4757370428366,\n",
+              "  'KernelRidge': 240.4757366399335,\n",
               "  'BayesianRidge': 307.4891482817299},\n",
               " {'Random Forest': 0.8062720190494954,\n",
               "  'Linear Regression': 0.5470736001611378,\n",
@@ -24740,14 +24707,14 @@
               "  'XGBoost': 0.7792738692467237,\n",
               "  'HistGradientBoosting': 0.746178757864505,\n",
               "  'AdaBoost': 0.7513404030172695,\n",
-              "  'GradientBoosting': 0.8240147453707464,\n",
+              "  'GradientBoosting': 0.8258347134492112,\n",
               "  'SVR': -0.0755368308413158,\n",
-              "  'KernelRidge': 0.42261352409575736,\n",
+              "  'KernelRidge': 0.4226135260305123,\n",
               "  'BayesianRidge': 0.055974631157888366})"
             ]
           },
           "metadata": {},
-          "execution_count": 42
+          "execution_count": 29
         }
       ]
     },
@@ -24757,7 +24724,7 @@
       "metadata": {
         "id": "-s-mdrCmIYVp"
       },
-      "execution_count": null,
+      "execution_count": 29,
       "outputs": []
     },
     {
@@ -24789,7 +24756,7 @@
       "metadata": {
         "id": "BgPeinX2kK22"
       },
-      "execution_count": null,
+      "execution_count": 30,
       "outputs": []
     },
     {
@@ -24804,9 +24771,9 @@
           "height": 80
         },
         "id": "QMPC1r_XjlAu",
-        "outputId": "27467877-e7d0-4629-9e4d-55d99e46f45a"
+        "outputId": "9a213abf-5ce5-4164-abb0-e87409a54e0b"
       },
-      "execution_count": null,
+      "execution_count": 31,
       "outputs": [
         {
           "output_type": "execute_result",
@@ -25223,7 +25190,7 @@
             ]
           },
           "metadata": {},
-          "execution_count": 44
+          "execution_count": 31
         }
       ]
     },
@@ -25245,21 +25212,21 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "ZhnZA4AXkbvW",
-        "outputId": "cbe33b10-099b-4f88-d43f-03f5f18b897d"
+        "outputId": "dc912be2-cb26-4b68-9309-f5b3194e1544"
       },
-      "execution_count": null,
+      "execution_count": 32,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "[0.99737661 0.99750453 0.99766506 0.9972478  0.99711882 0.9974906\n",
-            " 0.99793645 0.99743527 0.99690617 0.99787398]\n",
-            "[0.62602027 0.81881496 0.86247895 0.84311412 0.90390446 0.89535361\n",
-            " 0.50485765 0.72969038 0.74478517 0.86701499]\n",
+            "[0.9974449  0.99745362 0.99783926 0.99687033 0.99778265 0.99757234\n",
+            " 0.99715941 0.99790314 0.99759218 0.99663247]\n",
+            "[0.85838002 0.72119344 0.74075046 0.95000567 0.58097475 0.64761935\n",
+            " 0.80927823 0.8530523  0.85732538 0.93981176]\n",
             "dict_keys(['fit_time', 'score_time', 'test_r2', 'train_r2', 'test_mae', 'train_mae', 'test_mse', 'train_mse', 'test_mape', 'train_mape'])\n",
-            "Train(metric), Test(metric): 0.997, 0.780\n",
-            "Train(metric), Test(metric): 12.061, 88.429\n"
+            "Train(metric), Test(metric): 0.997, 0.796\n",
+            "Train(metric), Test(metric): 12.115, 85.602\n"
           ]
         }
       ]
@@ -25273,7 +25240,7 @@
       "metadata": {
         "id": "Jf_NVjQ_zykt"
       },
-      "execution_count": null,
+      "execution_count": 33,
       "outputs": []
     },
     {
@@ -25310,21 +25277,21 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "szyIeFTy0Ail",
-        "outputId": "6d638f4b-eb4b-4786-c052-5b3c636f359a"
+        "outputId": "c8e359e9-7e82-4225-fb21-26f49431b92e"
       },
-      "execution_count": null,
+      "execution_count": 34,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "[0.9999998  0.99999921 0.99999948 0.99999948 0.99999905 0.99999932\n",
-            " 0.99999908 0.99999933 0.99999905 0.99999942]\n",
-            "[0.80692657 0.89454576 0.84141704 0.60314347 0.69797768 0.56175097\n",
-            " 0.68157385 0.92563621 0.49173431 0.86374305]\n",
+            "[0.99999866 0.99999967 0.99999924 0.99999912 0.99999956 0.99999936\n",
+            " 0.9999989  0.99999958 0.9999997  0.99999941]\n",
+            "[0.83162383 0.62498054 0.78910623 0.90877724 0.60389899 0.51763964\n",
+            " 0.88884139 0.67223623 0.44869194 0.79279146]\n",
             "dict_keys(['fit_time', 'score_time', 'test_r2', 'train_r2', 'test_mae', 'train_mae', 'test_mse', 'train_mse', 'test_mape', 'train_mape'])\n",
-            "Train(metric), Test(metric): 1.000, 0.737\n",
-            "Train(metric), Test(metric): 0.180, 96.374\n"
+            "Train(metric), Test(metric): 1.000, 0.708\n",
+            "Train(metric), Test(metric): 0.179, 93.489\n"
           ]
         }
       ]
@@ -25345,15 +25312,15 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "WBVCaIFR3Dcw",
-        "outputId": "ef001c6a-f451-455e-83d1-56f0b67158cf"
+        "outputId": "81bcdf45-cb91-477a-c6fc-b1f85e5063d5"
       },
-      "execution_count": null,
+      "execution_count": 35,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "0.7758914299142441\n"
+            "0.7759073405187773\n"
           ]
         }
       ]
@@ -25375,7 +25342,7 @@
       "metadata": {
         "id": "xK0eX5QhZl_R"
       },
-      "execution_count": null,
+      "execution_count": 35,
       "outputs": []
     },
     {
@@ -25405,9 +25372,9 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "Rc0b_cNIaYGp",
-        "outputId": "5b7c09b8-ed73-4837-bed4-9d7e3fe86858"
+        "outputId": "c7df136a-c0f8-4628-dd49-434399d6c73a"
       },
-      "execution_count": null,
+      "execution_count": 36,
       "outputs": [
         {
           "output_type": "stream",
@@ -25418,53 +25385,53 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.467926 \n",
             "Fold 1/5 , model 1 , r2===0.607910 \n",
-            "Fold 1/5 , model 2 , r2===0.713114 \n",
+            "Fold 1/5 , model 2 , r2===0.713045 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===0.735262 \n",
             "Fold 2/5 , model 1 , r2===0.696357 \n",
-            "Fold 2/5 , model 2 , r2===0.781318 \n",
+            "Fold 2/5 , model 2 , r2===0.782034 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.776923 \n",
             "Fold 3/5 , model 1 , r2===0.732796 \n",
-            "Fold 3/5 , model 2 , r2===0.827626 \n",
+            "Fold 3/5 , model 2 , r2===0.827686 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.725732 \n",
             "Fold 4/5 , model 1 , r2===0.545276 \n",
-            "Fold 4/5 , model 2 , r2===0.713435 \n",
+            "Fold 4/5 , model 2 , r2===0.695651 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.826311 \n",
             "Fold 5/5 , model 1 , r2===0.823888 \n",
-            "Fold 5/5 , model 2 , r2===0.852178 \n",
+            "Fold 5/5 , model 2 , r2===0.851731 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.530065 seconds \n",
+            " level 0 lasted 9.772650 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.344470 \n",
+            "Fold 1/5 , model 0 , r2===0.306274 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===0.711914 \n",
+            "Fold 2/5 , model 0 , r2===0.739851 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.744692 \n",
+            "Fold 3/5 , model 0 , r2===0.752449 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.566766 \n",
+            "Fold 4/5 , model 0 , r2===0.565166 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.813641 \n",
+            "Fold 5/5 , model 0 , r2===0.803607 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.871905 seconds \n",
+            " level 1 lasted 9.668343 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 34.405983 seconds \n",
+            " fit() lasted 19.442715 seconds \n",
             "====================== Start of Level 0 ======================\n",
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
             "************************\n",
-            " 0.8581754923098954\n",
+            " 0.8562818063968041\n",
             "************************\n",
-            " 87.90447952498737\n"
+            " 88.13604662347294\n"
           ]
         }
       ]
@@ -25486,286 +25453,10 @@
         "# print('Train(metric), Test(metric): %.3f, %.3f' % (np.mean(scores['train_mae']), np.mean(scores['test_mae'])))\n"
       ],
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "f5iEtpDgh64v",
-        "outputId": "a9a27040-7a7b-49f3-9e85-474d39f9fe4e"
+        "id": "f5iEtpDgh64v"
       },
-      "execution_count": null,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "====================== Start of Level 0 ======================\n",
-            "Input Dimensionality 20 at Level 0 \n",
-            "3 models included in Level 0 \n",
-            "Fold 1/5 , model 0 , custom===0.872970 \n",
-            "Fold 1/5 , model 1 , custom===0.814608 \n",
-            "Fold 1/5 , model 2 , custom===0.872920 \n",
-            "=========== end of fold 1 in level 0 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.781848 \n",
-            "Fold 2/5 , model 1 , custom===0.765228 \n",
-            "Fold 2/5 , model 2 , custom===0.816307 \n",
-            "=========== end of fold 2 in level 0 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.823965 \n",
-            "Fold 3/5 , model 1 , custom===0.726821 \n",
-            "Fold 3/5 , model 2 , custom===0.813376 \n",
-            "=========== end of fold 3 in level 0 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.664061 \n",
-            "Fold 4/5 , model 1 , custom===0.646937 \n",
-            "Fold 4/5 , model 2 , custom===0.627758 \n",
-            "=========== end of fold 4 in level 0 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.663774 \n",
-            "Fold 5/5 , model 1 , custom===0.685916 \n",
-            "Fold 5/5 , model 2 , custom===0.679194 \n",
-            "=========== end of fold 5 in level 0 ===========\n",
-            "Output dimensionality of level 0 is 3 \n",
-            "====================== End of Level 0 ======================\n",
-            " level 0 lasted 18.262664 seconds \n",
-            "====================== Start of Level 1 ======================\n",
-            "Input Dimensionality 23 at Level 1 \n",
-            "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , custom===0.835540 \n",
-            "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.746396 \n",
-            "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.787041 \n",
-            "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.640307 \n",
-            "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.522661 \n",
-            "=========== end of fold 5 in level 1 ===========\n",
-            "Output dimensionality of level 1 is 1 \n",
-            "====================== End of Level 1 ======================\n",
-            " level 1 lasted 17.182471 seconds \n",
-            "====================== End of fit ======================\n",
-            " fit() lasted 35.448526 seconds \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "Input Dimensionality 20 at Level 0 \n",
-            "3 models included in Level 0 \n",
-            "Fold 1/5 , model 0 , custom===0.753318 \n",
-            "Fold 1/5 , model 1 , custom===0.785693 \n",
-            "Fold 1/5 , model 2 , custom===0.811107 \n",
-            "=========== end of fold 1 in level 0 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.711620 \n",
-            "Fold 2/5 , model 1 , custom===0.654802 \n",
-            "Fold 2/5 , model 2 , custom===0.671256 \n",
-            "=========== end of fold 2 in level 0 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.803641 \n",
-            "Fold 3/5 , model 1 , custom===0.736728 \n",
-            "Fold 3/5 , model 2 , custom===0.792260 \n",
-            "=========== end of fold 3 in level 0 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.796421 \n",
-            "Fold 4/5 , model 1 , custom===0.518474 \n",
-            "Fold 4/5 , model 2 , custom===0.846659 \n",
-            "=========== end of fold 4 in level 0 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.645727 \n",
-            "Fold 5/5 , model 1 , custom===0.544997 \n",
-            "Fold 5/5 , model 2 , custom===0.622026 \n",
-            "=========== end of fold 5 in level 0 ===========\n",
-            "Output dimensionality of level 0 is 3 \n",
-            "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.711757 seconds \n",
-            "====================== Start of Level 1 ======================\n",
-            "Input Dimensionality 23 at Level 1 \n",
-            "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , custom===0.702840 \n",
-            "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.605708 \n",
-            "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.468704 \n",
-            "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.703826 \n",
-            "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.652147 \n",
-            "=========== end of fold 5 in level 1 ===========\n",
-            "Output dimensionality of level 1 is 1 \n",
-            "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.641401 seconds \n",
-            "====================== End of fit ======================\n",
-            " fit() lasted 34.355973 seconds \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "Input Dimensionality 20 at Level 0 \n",
-            "3 models included in Level 0 \n",
-            "Fold 1/5 , model 0 , custom===0.840415 \n",
-            "Fold 1/5 , model 1 , custom===0.840497 \n",
-            "Fold 1/5 , model 2 , custom===0.832862 \n",
-            "=========== end of fold 1 in level 0 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.792322 \n",
-            "Fold 2/5 , model 1 , custom===0.665001 \n",
-            "Fold 2/5 , model 2 , custom===0.827707 \n",
-            "=========== end of fold 2 in level 0 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.796784 \n",
-            "Fold 3/5 , model 1 , custom===0.731078 \n",
-            "Fold 3/5 , model 2 , custom===0.763302 \n",
-            "=========== end of fold 3 in level 0 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.405353 \n",
-            "Fold 4/5 , model 1 , custom===0.457721 \n",
-            "Fold 4/5 , model 2 , custom===0.503097 \n",
-            "=========== end of fold 4 in level 0 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.698257 \n",
-            "Fold 5/5 , model 1 , custom===0.605934 \n",
-            "Fold 5/5 , model 2 , custom===0.699024 \n",
-            "=========== end of fold 5 in level 0 ===========\n",
-            "Output dimensionality of level 0 is 3 \n",
-            "====================== End of Level 0 ======================\n",
-            " level 0 lasted 18.742084 seconds \n",
-            "====================== Start of Level 1 ======================\n",
-            "Input Dimensionality 23 at Level 1 \n",
-            "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , custom===0.825606 \n",
-            "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.834812 \n",
-            "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.771748 \n",
-            "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.605812 \n",
-            "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.610083 \n",
-            "=========== end of fold 5 in level 1 ===========\n",
-            "Output dimensionality of level 1 is 1 \n",
-            "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.779898 seconds \n",
-            "====================== End of fit ======================\n",
-            " fit() lasted 35.523730 seconds \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "Input Dimensionality 20 at Level 0 \n",
-            "3 models included in Level 0 \n",
-            "Fold 1/5 , model 0 , custom===0.823516 \n",
-            "Fold 1/5 , model 1 , custom===0.699534 \n",
-            "Fold 1/5 , model 2 , custom===0.846083 \n",
-            "=========== end of fold 1 in level 0 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.712296 \n",
-            "Fold 2/5 , model 1 , custom===0.739516 \n",
-            "Fold 2/5 , model 2 , custom===0.776874 \n",
-            "=========== end of fold 2 in level 0 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.860966 \n",
-            "Fold 3/5 , model 1 , custom===0.756017 \n",
-            "Fold 3/5 , model 2 , custom===0.855464 \n",
-            "=========== end of fold 3 in level 0 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.901260 \n",
-            "Fold 4/5 , model 1 , custom===0.836559 \n",
-            "Fold 4/5 , model 2 , custom===0.881604 \n",
-            "=========== end of fold 4 in level 0 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.443464 \n",
-            "Fold 5/5 , model 1 , custom===0.468378 \n",
-            "Fold 5/5 , model 2 , custom===0.567936 \n",
-            "=========== end of fold 5 in level 0 ===========\n",
-            "Output dimensionality of level 0 is 3 \n",
-            "====================== End of Level 0 ======================\n",
-            " level 0 lasted 23.025588 seconds \n",
-            "====================== Start of Level 1 ======================\n",
-            "Input Dimensionality 23 at Level 1 \n",
-            "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , custom===0.850123 \n",
-            "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.652366 \n",
-            "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.797301 \n",
-            "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.670731 \n",
-            "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.387702 \n",
-            "=========== end of fold 5 in level 1 ===========\n",
-            "Output dimensionality of level 1 is 1 \n",
-            "====================== End of Level 1 ======================\n",
-            " level 1 lasted 17.061743 seconds \n",
-            "====================== End of fit ======================\n",
-            " fit() lasted 40.091802 seconds \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "Input Dimensionality 20 at Level 0 \n",
-            "3 models included in Level 0 \n",
-            "Fold 1/5 , model 0 , custom===0.854734 \n",
-            "Fold 1/5 , model 1 , custom===0.760988 \n",
-            "Fold 1/5 , model 2 , custom===0.889494 \n",
-            "=========== end of fold 1 in level 0 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.510614 \n",
-            "Fold 2/5 , model 1 , custom===0.490943 \n",
-            "Fold 2/5 , model 2 , custom===0.632916 \n",
-            "=========== end of fold 2 in level 0 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.823085 \n",
-            "Fold 3/5 , model 1 , custom===0.772802 \n",
-            "Fold 3/5 , model 2 , custom===0.833726 \n",
-            "=========== end of fold 3 in level 0 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.859707 \n",
-            "Fold 4/5 , model 1 , custom===0.778830 \n",
-            "Fold 4/5 , model 2 , custom===0.847239 \n",
-            "=========== end of fold 4 in level 0 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.669015 \n",
-            "Fold 5/5 , model 1 , custom===0.511400 \n",
-            "Fold 5/5 , model 2 , custom===0.730421 \n",
-            "=========== end of fold 5 in level 0 ===========\n",
-            "Output dimensionality of level 0 is 3 \n",
-            "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.534643 seconds \n",
-            "====================== Start of Level 1 ======================\n",
-            "Input Dimensionality 23 at Level 1 \n",
-            "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , custom===0.841589 \n",
-            "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , custom===0.433086 \n",
-            "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , custom===0.688474 \n",
-            "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , custom===0.781353 \n",
-            "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , custom===0.659429 \n",
-            "=========== end of fold 5 in level 1 ===========\n",
-            "Output dimensionality of level 1 is 1 \n",
-            "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.675574 seconds \n",
-            "====================== End of fit ======================\n",
-            " fit() lasted 34.212889 seconds \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "====================== Start of Level 0 ======================\n",
-            "5 estimators included in Level 0 \n",
-            "====================== Start of Level 1 ======================\n",
-            "5 estimators included in Level 1 \n",
-            "[0.9693958  0.95406991 0.96808435 0.97102371 0.96923852]\n",
-            "[0.71530265 0.81015099 0.77534298 0.75173496 0.85714487]\n",
-            "dict_keys(['fit_time', 'score_time', 'test_r2', 'train_r2', 'test_mae', 'train_mae', 'test_mse', 'train_mse', 'test_mape', 'train_mape'])\n",
-            "Train(metric), Test(metric): 0.966, 0.782\n",
-            "Train(metric), Test(metric): 33.568, 91.081\n"
-          ]
-        }
-      ]
+      "execution_count": 37,
+      "outputs": []
     },
     {
       "cell_type": "markdown",
@@ -25782,7 +25473,7 @@
       "metadata": {
         "id": "TJxNdRvDxY40"
       },
-      "execution_count": null,
+      "execution_count": 37,
       "outputs": []
     },
     {
@@ -25799,7 +25490,7 @@
       "metadata": {
         "id": "xTqSOq_Wwgou"
       },
-      "execution_count": null,
+      "execution_count": 38,
       "outputs": []
     },
     {
@@ -25850,7 +25541,7 @@
       "metadata": {
         "id": "R5f1TfN-Avrp"
       },
-      "execution_count": null,
+      "execution_count": 39,
       "outputs": []
     },
     {
@@ -25863,15 +25554,15 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "0elSHOsPwSp7",
-        "outputId": "53ec63d9-2022-4c95-8379-906eefeecb65"
+        "outputId": "8a834bc1-7d3f-44b2-c621-0c2ebc9cbe90"
       },
-      "execution_count": null,
+      "execution_count": 40,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "2024-05-27 18:18:50 INFO     Initialized benchmark 'matbench_v0.1' with 1 tasks: \n",
+            "2024-05-28 09:34:09 INFO     Initialized benchmark 'matbench_v0.1' with 1 tasks: \n",
             "['matbench_steels']\n"
           ]
         },
@@ -25920,6 +25611,8 @@
         "        # predictions = my_model.predict(test_inputs)\n",
         "        predictions = stack_net.predict(X_test)\n",
         "\n",
+        "        predictions = predictions.flatten()\n",
+        "\n",
         "        # Record your data!\n",
         "        task.record(fold, predictions)\n",
         "\n",
@@ -25934,575 +25627,589 @@
           "base_uri": "https://localhost:8080/",
           "height": 1000,
           "referenced_widgets": [
-            "d0093155ab7645818b33ecf805a4e24f",
-            "766de92e3f0e4517a1e7a6e7983715cf",
-            "ff2172e8a95847a6895e6eaa82d4c0b7",
-            "79ccedbfc0b849e186928fc496f10196",
-            "4ba509948c234cec9f1aa9fa12268ee8",
-            "8118f09611604defb1d6e7fe2c7a38cc",
-            "9cea02a758864db7a7d4bd8287706480",
-            "066d9ed6d0324512b2387e8fad51d6d7",
-            "c83a7c55d0574b84a7055880d6e21609",
-            "2dc9c8229b934bb3829fe16604d4aa40",
-            "77e8ec0fee7f46d2b64459f78a19eac4",
-            "1d8f97605c1e4ebda22df2204b314c2b",
-            "65c4970c344345e3915a46fff6d1eaac",
-            "5e46b086557e4aa8a0aa8b8fb7f2d91f",
-            "f1245ebe0f2c4b90a22f4e3f0c4be3ac",
-            "8f9dfa28bd7c46119cee66b08553243d",
-            "28a2679f2e5f4b788eaafc4aa34d95cf",
-            "86568ce023fe4f4d8aa75e0ad073b4cc",
-            "70603e4f25084a4ba8f4ac487b1e64c2",
-            "380722e242bb4f949442e000a7a8a18d",
-            "b81cb03e2960461e8b25cdf076102f05",
-            "25290564fada419abb5d1edf25158455",
-            "d9c8fee7b6a1491bbe534cd40cecbe7b",
-            "0d4578184d0e435b82f357354333004d",
-            "10fd038b7ecf4e29a6a62707f8e259be",
-            "c75c476a09c049e7a8586cde63ecef4e",
-            "890ed1d7e6ea4fa18330471dc8d28efd",
-            "fb44735df1544cc99eb004c1d65e02f5",
-            "c826dd76f82848608270dce93d3c8e76",
-            "5a519e55faec481784a64dc40e750607",
-            "189dfb02af004234ae3054fdd2df340d",
-            "884eff2df3b247bdac5128737e515cd8",
-            "d253702326274bb8928fbdd0acad04b8",
-            "4d0c1558ce6d453593ca99f01dbce797",
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           ]
         },
         "id": "6dBaWWoG1wvw",
-        "outputId": "f9b3336d-fc11-4a50-a636-a70df2cc7e85"
+        "outputId": "e022cd18-08e9-4494-96d4-c3d91a3483a0"
       },
-      "execution_count": null,
+      "execution_count": 41,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "2024-05-27 18:41:12 INFO     Dataset matbench_steels already loaded; not reloading dataset.\n"
+            "2024-05-28 09:34:09 INFO     Loading dataset 'matbench_steels'...\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "INFO:matbench.task:Loading dataset 'matbench_steels'...\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "2024-05-28 09:34:09 INFO     Dataset 'matbench_steels loaded.\n"
           ]
         },
         {
           "output_type": "stream",
           "name": "stderr",
           "text": [
-            "INFO:matbench.task:Dataset matbench_steels already loaded; not reloading dataset.\n"
+            "INFO:matbench.task:Dataset 'matbench_steels loaded.\n"
           ]
         },
         {
@@ -26514,7 +26221,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "d0093155ab7645818b33ecf805a4e24f"
+              "model_id": "e707dae0983e472884c217f3619056c2"
             }
           },
           "metadata": {}
@@ -26528,7 +26235,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "1d8f97605c1e4ebda22df2204b314c2b"
+              "model_id": "d6278fe9587d429ab9836c4b2c6d960c"
             }
           },
           "metadata": {}
@@ -26542,7 +26249,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "d9c8fee7b6a1491bbe534cd40cecbe7b"
+              "model_id": "824872abf99c4c8d880e13f4b01ae388"
             }
           },
           "metadata": {}
@@ -26556,7 +26263,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "4d0c1558ce6d453593ca99f01dbce797"
+              "model_id": "9044d17fe2304db1b446bdb9e4c1d2e1"
             }
           },
           "metadata": {}
@@ -26570,7 +26277,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "ec584f58337b496c84b587d1fe752dfd"
+              "model_id": "0cf54304b2b7463eab6674de9dd97665"
             }
           },
           "metadata": {}
@@ -26584,45 +26291,45 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.812643 \n",
             "Fold 1/5 , model 1 , r2===0.756501 \n",
-            "Fold 1/5 , model 2 , r2===0.760748 \n",
+            "Fold 1/5 , model 2 , r2===0.766412 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===0.694843 \n",
             "Fold 2/5 , model 1 , r2===0.559417 \n",
-            "Fold 2/5 , model 2 , r2===0.690066 \n",
+            "Fold 2/5 , model 2 , r2===0.681655 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.888666 \n",
             "Fold 3/5 , model 1 , r2===0.859816 \n",
-            "Fold 3/5 , model 2 , r2===0.897067 \n",
+            "Fold 3/5 , model 2 , r2===0.899364 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.671192 \n",
             "Fold 4/5 , model 1 , r2===0.629115 \n",
-            "Fold 4/5 , model 2 , r2===0.760067 \n",
+            "Fold 4/5 , model 2 , r2===0.763225 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.766110 \n",
             "Fold 5/5 , model 1 , r2===0.711169 \n",
-            "Fold 5/5 , model 2 , r2===0.821355 \n",
+            "Fold 5/5 , model 2 , r2===0.821130 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.610867 seconds \n",
+            " level 0 lasted 9.703811 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.687480 \n",
+            "Fold 1/5 , model 0 , r2===0.719790 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===0.684141 \n",
+            "Fold 2/5 , model 0 , r2===0.650211 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.890868 \n",
+            "Fold 3/5 , model 0 , r2===0.891652 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.592479 \n",
+            "Fold 4/5 , model 0 , r2===0.613004 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.800423 \n",
+            "Fold 5/5 , model 0 , r2===0.805599 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.871732 seconds \n",
+            " level 1 lasted 9.082571 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 34.507080 seconds \n"
+            " fit() lasted 18.800702 seconds \n"
           ]
         },
         {
@@ -26634,7 +26341,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "005afc83071e47a5a806ec196d9a3d25"
+              "model_id": "7172ab9b6b2046f29cda82e3f64b5db8"
             }
           },
           "metadata": {}
@@ -26648,7 +26355,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "1c2c7949383a4d0e8ba5771281a1c107"
+              "model_id": "e7aab8277cce479d8bd185795dc0f574"
             }
           },
           "metadata": {}
@@ -26662,7 +26369,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "8cf2dac6348044288062182852cc2209"
+              "model_id": "fbe900499bfc4522af062a0a9f06bff2"
             }
           },
           "metadata": {}
@@ -26676,7 +26383,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "49920193317b41dbb02b128a837a9399"
+              "model_id": "e5d5fc04f95c4edc98163f3f0e72bdce"
             }
           },
           "metadata": {}
@@ -26690,7 +26397,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "8b4c2f2c07fe48a8bc1a051bf907e27c"
+              "model_id": "647c96f35cfc45b8b88dab29d68a15b9"
             }
           },
           "metadata": {}
@@ -26703,7 +26410,7 @@
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
-            "2024-05-27 18:42:22 INFO     Recorded fold matbench_steels-0 successfully.\n"
+            "2024-05-28 09:34:36 INFO     Recorded fold matbench_steels-0 successfully.\n"
           ]
         },
         {
@@ -26722,7 +26429,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "cb533cde781b44b7930f6f87ff829212"
+              "model_id": "24453e598d3446be8fa829d38055a70e"
             }
           },
           "metadata": {}
@@ -26736,7 +26443,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "9479f9433a2b40d184cb460ebea45a14"
+              "model_id": "bb7acfb84bc142bc927bbce3416cec45"
             }
           },
           "metadata": {}
@@ -26750,7 +26457,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "abeb221871b84d88b0db18c710a73b63"
+              "model_id": "fc423a69158d459589e0567a28181e2c"
             }
           },
           "metadata": {}
@@ -26764,7 +26471,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "34b5a434f30544c18e7044df0bda541d"
+              "model_id": "85e39c90568646f482008c94cd10edd5"
             }
           },
           "metadata": {}
@@ -26778,7 +26485,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "2acd74345acc4fc7a3fe4b1ed6e9250d"
+              "model_id": "2e290dc9f9a34e698921b48e4ce9850f"
             }
           },
           "metadata": {}
@@ -26792,45 +26499,45 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.843579 \n",
             "Fold 1/5 , model 1 , r2===0.802530 \n",
-            "Fold 1/5 , model 2 , r2===0.838731 \n",
+            "Fold 1/5 , model 2 , r2===0.838018 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===0.816399 \n",
             "Fold 2/5 , model 1 , r2===0.666329 \n",
-            "Fold 2/5 , model 2 , r2===0.771298 \n",
+            "Fold 2/5 , model 2 , r2===0.774435 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.715725 \n",
             "Fold 3/5 , model 1 , r2===0.573871 \n",
-            "Fold 3/5 , model 2 , r2===0.668584 \n",
+            "Fold 3/5 , model 2 , r2===0.676477 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.665806 \n",
             "Fold 4/5 , model 1 , r2===0.515958 \n",
-            "Fold 4/5 , model 2 , r2===0.750060 \n",
+            "Fold 4/5 , model 2 , r2===0.759455 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.583193 \n",
             "Fold 5/5 , model 1 , r2===0.481928 \n",
-            "Fold 5/5 , model 2 , r2===0.614408 \n",
+            "Fold 5/5 , model 2 , r2===0.615905 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 18.118026 seconds \n",
+            " level 0 lasted 9.925138 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.873343 \n",
+            "Fold 1/5 , model 0 , r2===0.872132 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===0.611328 \n",
+            "Fold 2/5 , model 0 , r2===0.591746 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.689610 \n",
+            "Fold 3/5 , model 0 , r2===0.705999 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.725044 \n",
+            "Fold 4/5 , model 0 , r2===0.720788 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.479192 \n",
+            "Fold 5/5 , model 0 , r2===0.464553 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.899742 seconds \n",
+            " level 1 lasted 9.154488 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 35.041944 seconds \n"
+            " fit() lasted 19.096183 seconds \n"
           ]
         },
         {
@@ -26842,7 +26549,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "949d05a45cf04c70b4bab6c1969b2c4a"
+              "model_id": "72cab45dec0043219bca378fc6f77951"
             }
           },
           "metadata": {}
@@ -26856,7 +26563,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "8ef671b320714fae93cf2324277d5d4d"
+              "model_id": "3e1331961e1546d69e749891c3cbf4d2"
             }
           },
           "metadata": {}
@@ -26870,7 +26577,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "6677592bd88d48f39a39f02fb3f51ecb"
+              "model_id": "7712988e84ea4bf6b6272c6460ac27f3"
             }
           },
           "metadata": {}
@@ -26884,7 +26591,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "84799302b17948fe998cfc69f64c2707"
+              "model_id": "808ae27e9feb4bd9b92969f57e46efba"
             }
           },
           "metadata": {}
@@ -26898,7 +26605,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "c230b98570b24bdc9b296cb3a52a1997"
+              "model_id": "ecec751bb40a4e2c83e82137d102577d"
             }
           },
           "metadata": {}
@@ -26911,7 +26618,7 @@
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
-            "2024-05-27 18:43:33 INFO     Recorded fold matbench_steels-1 successfully.\n"
+            "2024-05-28 09:35:03 INFO     Recorded fold matbench_steels-1 successfully.\n"
           ]
         },
         {
@@ -26930,7 +26637,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "b48490e695154529a0f898298b5f99e0"
+              "model_id": "bf8b8518d9cb485abcd1a55907f086c9"
             }
           },
           "metadata": {}
@@ -26944,7 +26651,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "768bc41c329641c98d40230df8d4e97d"
+              "model_id": "63f54bd83d714653ae4bc2b921b960fd"
             }
           },
           "metadata": {}
@@ -26958,7 +26665,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "9fb9891626c246c396a299122922f56c"
+              "model_id": "7e3879013e974497b294afc6cde0f620"
             }
           },
           "metadata": {}
@@ -26972,7 +26679,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "25a86fe8394d451e8f6d02f8167317a3"
+              "model_id": "4a1db01c360b419e8046e6a869339c12"
             }
           },
           "metadata": {}
@@ -26986,7 +26693,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "e8845ff39a7b4ddb9559e91b35b3dc59"
+              "model_id": "e0b0810f63be4c5eb3da40f93099aa39"
             }
           },
           "metadata": {}
@@ -27000,45 +26707,45 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.862870 \n",
             "Fold 1/5 , model 1 , r2===0.789035 \n",
-            "Fold 1/5 , model 2 , r2===0.867109 \n",
+            "Fold 1/5 , model 2 , r2===0.871161 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===-0.023714 \n",
             "Fold 2/5 , model 1 , r2===0.156559 \n",
-            "Fold 2/5 , model 2 , r2===0.134267 \n",
+            "Fold 2/5 , model 2 , r2===0.131832 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.882532 \n",
             "Fold 3/5 , model 1 , r2===0.838092 \n",
-            "Fold 3/5 , model 2 , r2===0.868790 \n",
+            "Fold 3/5 , model 2 , r2===0.871898 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.845742 \n",
             "Fold 4/5 , model 1 , r2===0.790818 \n",
-            "Fold 4/5 , model 2 , r2===0.871387 \n",
+            "Fold 4/5 , model 2 , r2===0.868480 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.434990 \n",
             "Fold 5/5 , model 1 , r2===0.206355 \n",
-            "Fold 5/5 , model 2 , r2===0.450117 \n",
+            "Fold 5/5 , model 2 , r2===0.465966 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 18.079647 seconds \n",
+            " level 0 lasted 9.453974 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.837436 \n",
+            "Fold 1/5 , model 0 , r2===0.832972 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===-0.285833 \n",
+            "Fold 2/5 , model 0 , r2===-0.169444 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.845839 \n",
+            "Fold 3/5 , model 0 , r2===0.851219 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.807087 \n",
+            "Fold 4/5 , model 0 , r2===0.805301 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.282370 \n",
+            "Fold 5/5 , model 0 , r2===0.179530 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.876967 seconds \n",
+            " level 1 lasted 8.983493 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 34.985764 seconds \n"
+            " fit() lasted 18.453007 seconds \n"
           ]
         },
         {
@@ -27050,7 +26757,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "85af84b4f079445690da446bf5b6de19"
+              "model_id": "01342c98b836440087b7171222bfff44"
             }
           },
           "metadata": {}
@@ -27064,7 +26771,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "7faf4fcc789d4c52b76ee687e5af58b8"
+              "model_id": "2bcc4580444e411f9d5ec9b7a6eaa017"
             }
           },
           "metadata": {}
@@ -27078,7 +26785,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "3a649e16ea3e4d7f99e2dc8dd0de150e"
+              "model_id": "02ca33c6e6eb4918a72b123c1e50ce8c"
             }
           },
           "metadata": {}
@@ -27092,7 +26799,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "bb9b7a1f2ef643a29ae93e1e3d2af80c"
+              "model_id": "134642f7fa8c4ab8ac4a1493b7ddc249"
             }
           },
           "metadata": {}
@@ -27106,7 +26813,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "a2908ecfd56e4b28b3c94db362fbe10c"
+              "model_id": "2af8ed86fa2046bda01248f13ff752fe"
             }
           },
           "metadata": {}
@@ -27119,7 +26826,7 @@
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
-            "2024-05-27 18:44:43 INFO     Recorded fold matbench_steels-2 successfully.\n"
+            "2024-05-28 09:35:29 INFO     Recorded fold matbench_steels-2 successfully.\n"
           ]
         },
         {
@@ -27138,7 +26845,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "a379838766cd4177823f295b33246248"
+              "model_id": "d35c44c8f5d94266a0e60e66131b95d9"
             }
           },
           "metadata": {}
@@ -27152,7 +26859,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "39694a800cd44ea3bab7aca291aa6936"
+              "model_id": "fce43fce5cc64816a67a033e631e1f1e"
             }
           },
           "metadata": {}
@@ -27166,7 +26873,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "f48564690aa843c798ff7019fca1dacc"
+              "model_id": "d185b15a832d458783a8f0652661b487"
             }
           },
           "metadata": {}
@@ -27180,7 +26887,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "4b42bdc575ca4a1ca7fb780c8e9b4e70"
+              "model_id": "74aac947e8864eb1bfea8b80c5fb7515"
             }
           },
           "metadata": {}
@@ -27194,7 +26901,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "cd9988d01bba44f1b2b34a1cca33ff91"
+              "model_id": "dd19572d40854af582183cd0cbda49d4"
             }
           },
           "metadata": {}
@@ -27208,45 +26915,45 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.791067 \n",
             "Fold 1/5 , model 1 , r2===0.641994 \n",
-            "Fold 1/5 , model 2 , r2===0.818674 \n",
+            "Fold 1/5 , model 2 , r2===0.816415 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===0.269821 \n",
             "Fold 2/5 , model 1 , r2===0.355068 \n",
-            "Fold 2/5 , model 2 , r2===0.343695 \n",
+            "Fold 2/5 , model 2 , r2===0.354684 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.740311 \n",
             "Fold 3/5 , model 1 , r2===0.614102 \n",
-            "Fold 3/5 , model 2 , r2===0.720597 \n",
+            "Fold 3/5 , model 2 , r2===0.721331 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.750091 \n",
             "Fold 4/5 , model 1 , r2===0.635502 \n",
-            "Fold 4/5 , model 2 , r2===0.807331 \n",
+            "Fold 4/5 , model 2 , r2===0.799203 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.576571 \n",
             "Fold 5/5 , model 1 , r2===0.567783 \n",
-            "Fold 5/5 , model 2 , r2===0.524409 \n",
+            "Fold 5/5 , model 2 , r2===0.527001 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.563887 seconds \n",
+            " level 0 lasted 9.671608 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.677815 \n",
+            "Fold 1/5 , model 0 , r2===0.703851 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===-0.191303 \n",
+            "Fold 2/5 , model 0 , r2===-0.127569 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.664220 \n",
+            "Fold 3/5 , model 0 , r2===0.666467 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.779244 \n",
+            "Fold 4/5 , model 0 , r2===0.781319 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.401631 \n",
+            "Fold 5/5 , model 0 , r2===0.403243 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.805774 seconds \n",
+            " level 1 lasted 9.277647 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 34.392859 seconds \n"
+            " fit() lasted 18.966771 seconds \n"
           ]
         },
         {
@@ -27258,7 +26965,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "9a7eb53745c44c5687e84e34ec51fa0a"
+              "model_id": "307c30e3319d4fbab21261fb87f10638"
             }
           },
           "metadata": {}
@@ -27272,7 +26979,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "dd7c932427124a3aadc30d655191baac"
+              "model_id": "0c48656a24d24e958a280098d5435ada"
             }
           },
           "metadata": {}
@@ -27286,7 +26993,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "345eec84935746d1bf384e5e0268bfa4"
+              "model_id": "7ea6f1c497f643168918f6b7f9ce79c0"
             }
           },
           "metadata": {}
@@ -27300,7 +27007,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "6d2189ea99be4b75b826aa0cf7ed25ca"
+              "model_id": "697a2e72542348378d8b72496b8527ef"
             }
           },
           "metadata": {}
@@ -27314,7 +27021,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "a3d84153d98d490c9ec4a9df76f5e327"
+              "model_id": "335d63914bef4280af5373c5175b8830"
             }
           },
           "metadata": {}
@@ -27327,7 +27034,7 @@
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
-            "2024-05-27 18:45:55 INFO     Recorded fold matbench_steels-3 successfully.\n"
+            "2024-05-28 09:35:56 INFO     Recorded fold matbench_steels-3 successfully.\n"
           ]
         },
         {
@@ -27346,7 +27053,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "ce1e3e8f96004313937cdce517cc202c"
+              "model_id": "2d83d96f346d4b13aa662a21646c6281"
             }
           },
           "metadata": {}
@@ -27360,7 +27067,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "b13ac64be8ec4d488709ffaf4cf12c54"
+              "model_id": "46182337bdae4082b323b923f94a78a1"
             }
           },
           "metadata": {}
@@ -27374,7 +27081,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "f24e5bb46da44f7ba8265ab54f692cdb"
+              "model_id": "6e7b625db09844848632a37dfdeae6d3"
             }
           },
           "metadata": {}
@@ -27388,7 +27095,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "b3da7e59b18c40fea9d3b9aaf8e2ade3"
+              "model_id": "3f0cbf90e2c54a3a844a4d120a3fee5a"
             }
           },
           "metadata": {}
@@ -27402,7 +27109,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "a317a600d4d745769075b7f0f409f2b8"
+              "model_id": "86f11e04d22d47bdab3c2915f11e3824"
             }
           },
           "metadata": {}
@@ -27416,45 +27123,45 @@
             "3 models included in Level 0 \n",
             "Fold 1/5 , model 0 , r2===0.663005 \n",
             "Fold 1/5 , model 1 , r2===0.590550 \n",
-            "Fold 1/5 , model 2 , r2===0.691480 \n",
+            "Fold 1/5 , model 2 , r2===0.698332 \n",
             "=========== end of fold 1 in level 0 ===========\n",
             "Fold 2/5 , model 0 , r2===0.734094 \n",
             "Fold 2/5 , model 1 , r2===0.632546 \n",
-            "Fold 2/5 , model 2 , r2===0.771730 \n",
+            "Fold 2/5 , model 2 , r2===0.779159 \n",
             "=========== end of fold 2 in level 0 ===========\n",
             "Fold 3/5 , model 0 , r2===0.714137 \n",
             "Fold 3/5 , model 1 , r2===0.655525 \n",
-            "Fold 3/5 , model 2 , r2===0.731433 \n",
+            "Fold 3/5 , model 2 , r2===0.737282 \n",
             "=========== end of fold 3 in level 0 ===========\n",
             "Fold 4/5 , model 0 , r2===0.835898 \n",
             "Fold 4/5 , model 1 , r2===0.831099 \n",
-            "Fold 4/5 , model 2 , r2===0.867124 \n",
+            "Fold 4/5 , model 2 , r2===0.860465 \n",
             "=========== end of fold 4 in level 0 ===========\n",
             "Fold 5/5 , model 0 , r2===0.774231 \n",
             "Fold 5/5 , model 1 , r2===0.607155 \n",
-            "Fold 5/5 , model 2 , r2===0.752588 \n",
+            "Fold 5/5 , model 2 , r2===0.757905 \n",
             "=========== end of fold 5 in level 0 ===========\n",
             "Output dimensionality of level 0 is 3 \n",
             "====================== End of Level 0 ======================\n",
-            " level 0 lasted 17.475495 seconds \n",
+            " level 0 lasted 9.454694 seconds \n",
             "====================== Start of Level 1 ======================\n",
             "Input Dimensionality 23 at Level 1 \n",
             "1 models included in Level 1 \n",
-            "Fold 1/5 , model 0 , r2===0.727818 \n",
+            "Fold 1/5 , model 0 , r2===0.704521 \n",
             "=========== end of fold 1 in level 1 ===========\n",
-            "Fold 2/5 , model 0 , r2===0.718650 \n",
+            "Fold 2/5 , model 0 , r2===0.709902 \n",
             "=========== end of fold 2 in level 1 ===========\n",
-            "Fold 3/5 , model 0 , r2===0.677734 \n",
+            "Fold 3/5 , model 0 , r2===0.688357 \n",
             "=========== end of fold 3 in level 1 ===========\n",
-            "Fold 4/5 , model 0 , r2===0.860270 \n",
+            "Fold 4/5 , model 0 , r2===0.866128 \n",
             "=========== end of fold 4 in level 1 ===========\n",
-            "Fold 5/5 , model 0 , r2===0.726931 \n",
+            "Fold 5/5 , model 0 , r2===0.714033 \n",
             "=========== end of fold 5 in level 1 ===========\n",
             "Output dimensionality of level 1 is 1 \n",
             "====================== End of Level 1 ======================\n",
-            " level 1 lasted 16.777733 seconds \n",
+            " level 1 lasted 9.311920 seconds \n",
             "====================== End of fit ======================\n",
-            " fit() lasted 34.276301 seconds \n"
+            " fit() lasted 18.782230 seconds \n"
           ]
         },
         {
@@ -27466,7 +27173,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "c6062aa576854fd9a1f4b001ac0bab72"
+              "model_id": "c59b452c7c70457d90cab50eb3bfb9e7"
             }
           },
           "metadata": {}
@@ -27480,7 +27187,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "6c06e4696b0e477f80dfb55e3daaab47"
+              "model_id": "93a5fd9c0fda425fac53f5c74c2e04c5"
             }
           },
           "metadata": {}
@@ -27494,7 +27201,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "5bbc4748398e4d12b865bb8593392f51"
+              "model_id": "53cb593b9e7b45ee8f7eff8908f2d0ab"
             }
           },
           "metadata": {}
@@ -27508,7 +27215,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "cb2c96aa5d6e406e997ec0f2914371d4"
+              "model_id": "82a52acd41034e48b6e37c2f79931b5f"
             }
           },
           "metadata": {}
@@ -27522,7 +27229,7 @@
             "application/vnd.jupyter.widget-view+json": {
               "version_major": 2,
               "version_minor": 0,
-              "model_id": "6e56d785fd6e48328301bd9f59eaeb84"
+              "model_id": "eb82b6ad57df4b7a95c03dfce5865a2e"
             }
           },
           "metadata": {}
@@ -27535,7 +27242,7 @@
             "5 estimators included in Level 0 \n",
             "====================== Start of Level 1 ======================\n",
             "5 estimators included in Level 1 \n",
-            "2024-05-27 18:47:06 INFO     Recorded fold matbench_steels-4 successfully.\n"
+            "2024-05-28 09:36:23 INFO     Recorded fold matbench_steels-4 successfully.\n"
           ]
         },
         {
@@ -27549,7 +27256,7 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "2024-05-27 18:47:06 INFO     Successfully wrote MatbenchBenchmark to file 'results.json.gz'.\n"
+            "2024-05-28 09:36:23 INFO     Successfully wrote MatbenchBenchmark to file 'results.json.gz'.\n"
           ]
         },
         {
diff --git a/benchmarks/matbench_v0.1_StackNet-mat_v0.2/info.json b/benchmarks/matbench_v0.1_StackNet-mat_v0.2/info.json
index 241045af..debb16cc 100644
--- a/benchmarks/matbench_v0.1_StackNet-mat_v0.2/info.json
+++ b/benchmarks/matbench_v0.1_StackNet-mat_v0.2/info.json
@@ -2,7 +2,7 @@
   "authors": "Oleksii Kudin, Anastasiiya Krivokhata, Yuriy Belokon, Dmytro Kruglyak, Sergii Ilin",
   "algorithm": "StackNet-mat v02",
   "algorithm_long": "A method based on basic machine learning algorithms: RandomFores, HistGradientBoosting, AdaBoost, GradientBoosting, and the use of Stacknet as a metamodel",
-  "bibtex_refs": null,
-  "notes": null,
+  "bibtex_refs": " ",
+  "notes": " ",
   "requirements": {"python":  ["scikit-learn==1.5.0", "numpy==1.25.2", "matbench==0.6", "matminer==0.9.2", "pystacknet==0.0.1", "tensorflow==2.15.0"]}
 }
diff --git a/benchmarks/matbench_v0.1_StackNet-mat_v0.2/results.json.gz b/benchmarks/matbench_v0.1_StackNet-mat_v0.2/results.json.gz
index 9b031ccb..9be1851f 100644
Binary files a/benchmarks/matbench_v0.1_StackNet-mat_v0.2/results.json.gz and b/benchmarks/matbench_v0.1_StackNet-mat_v0.2/results.json.gz differ