From 38f919c55ab241b6ced08f5d4342bd7770882da2 Mon Sep 17 00:00:00 2001
From: Jeff VanOss <jeff.vanoss@bamfhealth.com>
Date: Fri, 6 Oct 2023 17:08:25 +0000
Subject: [PATCH 1/3] update notebook

---
 .pre-commit-config.yaml |   2 +-
 model_performance.ipynb | 379 +++++++++++++++++++++++++++++++---------
 2 files changed, 302 insertions(+), 79 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index cc789d5..c0a2782 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -16,7 +16,7 @@ repos:
   - repo: https://github.com/psf/black
     rev: 23.9.1
     hooks:
-      - id: black
+      - id: black-jupyter
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.5.1
     hooks:
diff --git a/model_performance.ipynb b/model_performance.ipynb
index 6ba4f34..f3ea381 100644
--- a/model_performance.ipynb
+++ b/model_performance.ipynb
@@ -18,7 +18,7 @@
    "outputs": [],
    "source": [
     "%%capture\n",
-    "%pip install pandas pydicom pydicom-seg scikit-learn seaborn segmentationmetrics"
+    "%pip install pandas pydicom pydicom-seg scikit-learn seaborn segmentationmetrics requests"
    ]
   },
   {
@@ -30,29 +30,49 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
     "import warnings\n",
-    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "warnings.filterwarnings(\"ignore\")\n",
     "\n",
     "from pathlib import Path\n",
     "import requests\n",
     "import zipfile\n",
     "import io\n",
+    "import numpy as np\n",
     "import pandas as pd\n",
-    "from sklearn.metrics import cohen_kappa_score\n",
+    "import scipy.stats as stats\n",
     "import pydicom\n",
     "import pydicom_seg\n",
     "import SimpleITK as sitk\n",
+    "import matplotlib.pyplot as plt\n",
     "import segmentationmetrics as sm\n",
     "from segmentationmetrics.surface_distance import compute_surface_dice_at_tolerance\n",
     "import seaborn as sns\n",
+    "\n",
     "sns.set_theme(style=\"whitegrid\")\n",
-    "colors = ['#4e67c8','#5ecbf3', '#5dceae','#a7ea53']\n",
-    "sns.set_palette(sns.color_palette(colors))\n",
-    "%matplotlib inline\n"
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt_colors = {\n",
+    "    \"ne1\": \"#5eceb0\",\n",
+    "    \"rad1\": \"#9e70e1\",\n",
+    "    \"tp\": \"k\",\n",
+    "    \"fp\": \"b\",\n",
+    "    \"fn\": \"r\",\n",
+    "}\n",
+    "\n",
+    "revewer_cmap = sns.color_palette([plt_colors[\"ne1\"], plt_colors[\"rad1\"]])\n",
+    "vol_cmap = sns.color_palette([plt_colors[\"fp\"], plt_colors[\"fn\"]])"
    ]
   },
   {
@@ -64,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -73,13 +93,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
     "def download_inference(\n",
     "    extract_dir=\"qa-results\",\n",
-    "    url=\"https://zenodo.org/record/8352041/files/liver-mr.zip\",\n",
+    "    url=\"https://zenodo.org/record/8400869/files/liver-mr.zip\",\n",
     "):\n",
     "    # download the zip file and extract it\n",
     "    r = requests.get(url)\n",
@@ -88,7 +108,7 @@
     "\n",
     "\n",
     "if not qa_dir.exists() or not (qa_dir / \"ai-segmentations-dcm\").exists():\n",
-    "    download_inference()\n"
+    "    download_inference()"
    ]
   },
   {
@@ -129,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -152,6 +172,7 @@
     "    },\n",
     ")\n",
     "df[\"CorrectedSegmentation\"].fillna(\"\", inplace=True)\n",
+    "df.replace({\"rad1\": \"Radiologist\", \"ne1\": \"Non-expert\"}, inplace=True)\n",
     "# get validation subset\n",
     "val_df = df[df[\"Validation\"]]\n",
     "validation_size = len(val_df[\"SeriesInstanceUID\"].unique())\n",
@@ -161,9 +182,9 @@
     ")\n",
     "\n",
     "# get validation done by different reviewers\n",
-    "rad_df = val_df.loc[val_df[\"Reviewer\"] == \"rad1\"]\n",
+    "rad_df = val_df.loc[val_df[\"Reviewer\"] == \"Radiologist\"]\n",
     "ne_df = val_df.loc[\n",
-    "    (val_df[\"Reviewer\"] == \"ne1\")\n",
+    "    (val_df[\"Reviewer\"] == \"Non-expert\")\n",
     "    & (val_df[\"AISegmentation\"]).isin(rad_df[\"AISegmentation\"])\n",
     "]\n",
     "\n",
@@ -180,45 +201,33 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We caluclate the Cohen-Kappa score between the two reviewers. Cohen-Kappa is a measure of agreement between raters that takes into account the possibility of the agreement occurring by chance. This tells us how much we can trust the scores given by the non-expert reviewer for the portion of the dataset the Radiologist did not review.\n",
-    "\n",
-    "Kappa value interpretation Landis & Koch (1977):\n",
-    "\n",
-    "| Value     | Interpretation |\n",
-    "| --------- | -------------- |\n",
-    "| <0        | No agreement   |\n",
-    "| 0 — .20   | Slight         |\n",
-    "| .21 — .40 | Fair           |\n",
-    "| .41 — .60 | Moderate       |\n",
-    "| .61 — .80 | Substantial    |\n",
-    "| .81–1.0   | Perfect        |\n"
+    "We caluclate the Kendall-𝜏 score between the two reviewers. Kendall-𝜏 is a measure of correlation between raters of ordinal data. This tells us how much we can trust the scores given by the non-expert reviewer for the portion of the dataset the Radiologist did not review.\n",
+    "\n",
+    "For this dataset, there is a significant correlation between the two reviewers. \n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cohen's Kappa: 0.55\n",
+      "Kendall's 𝜏: 0.69, p-value: 0.07\n",
       "Percentage Agreement: 71.43%\n"
      ]
     }
    ],
    "source": [
-    "rad_scores = rad_df.LikertScore.values\n",
-    "ne_scores = ne_df.LikertScore.values\n",
-    "# Calculate Cohen's Kappa\n",
-    "kappa = cohen_kappa_score(rad_scores, ne_scores, labels=[1, 2, 3, 4, 5])\n",
-    "\n",
-    "print(f\"Cohen's Kappa: {kappa:.2f}\")\n",
+    "tau, p_value = stats.kendalltau(rad_df.LikertScore.values, ne_df.LikertScore.values)\n",
+    "print(f\"Kendall's 𝜏: {tau:.2f}, p-value: {p_value:.2f}\")\n",
     "\n",
     "# Calculate percentage agreement\n",
-    "total_cases = len(rad_scores)\n",
-    "matching_cases = sum(1 for r1, r2 in zip(rad_scores, ne_scores) if r1 == r2)\n",
+    "\n",
+    "total_cases = len(rad_df.LikertScore)\n",
+    "matching_cases = np.sum(rad_df.LikertScore.values == ne_df.LikertScore.values)\n",
     "percentage_agreement = (matching_cases / total_cases) * 100\n",
     "\n",
     "print(f\"Percentage Agreement: {percentage_agreement:.2f}%\")"
@@ -226,24 +235,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f845fcbb880>"
+       "<seaborn.axisgrid.FacetGrid at 0x7f3b2faa7f70>"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 740.75x600 with 1 Axes>"
+       "<Figure size 640.75x500 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -258,8 +267,6 @@
     "            df2.loc[(reviewer, score), \"SeriesInstanceUID\"] = 0\n",
     "\n",
     "df2.reset_index(inplace=True)\n",
-    "# change rad1 to radiologist\n",
-    "df2.replace({\"rad1\": \"Radiologist\", \"ne1\": \"Non-expert\"}, inplace=True)\n",
     "\n",
     "g = sns.catplot(\n",
     "    data=df2,\n",
@@ -267,13 +274,51 @@
     "    x=\"LikertScore\",\n",
     "    y=\"SeriesInstanceUID\",\n",
     "    hue=\"Reviewer\",\n",
-    "    height=6,\n",
     "    orient=\"v\",\n",
+    "    palette=revewer_cmap,\n",
     ")\n",
     "# g.despine(left=True)\n",
     "g.set_axis_labels(\"Likert Score\", \"Counts\")\n",
     "g.legend.set_title(\"\")\n",
-    "g.set(title=f\"Likert Score by Reviewer\\nCohen's Kappa: {kappa:.2f}\")\n"
+    "g.set(title=f\"Likert Score by Reviewer\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Likert Score Distribution for Radiologist')"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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444476rUdR/9t6npNm/tbXV07CNEMV8r18PBo8A6qe/fu9vmuUaNGYcqUKXjyySexevVq+879u+++w5w5czBq1CjMmDEDQUFBMBgMmD9/fo0JaUdo6NLn5uLl5YXFixdj165d2LhxI7Zs2YKffvoJS5cuxccff6zJMub6cN64qidJkvDmm29iwIABePTRR2usJGnVqhV8fX2hqioGDRpU63+XrgaqaxuOEB8fDwDIyckBUPVtIzs7G4WFhXU+JiwsDKqqIjU1tcbtubm5KC4uRlhY2FW3GxkZifLy8jpfg0u/qTaEoihYuXIlvL297RNldQkICMDtt9+Ot99+Gxs3brxs1Y4jP9yqql628zl9+jQA2F+z6m/kl650qe0bZn1ra9WqFby9ve3butipU6cgyzLatWtXr+e6FtV/y9q2f/r06Ub9rWtjMBjwxBNPIDs7275CCwDWrFmDiIgIzJs3D7fddhuGDh2KQYMGwWq11nh8WFgYcnJyLht6rK3+SzXmsxEWFobU1NTLvgCcOnUKwO+vY2hoKHJycmA2m2vcLy0t7ar1AVWBP3DgQDz33HP46aef8Pjjj2Pnzp32/ZQzBprLhwJQ9W1n3rx5SEhIwKxZs3DgwAEAVW/YMWPGYM2aNfZvsxer77BJ9aFjbcvkalPXmHX1GGf1ofHo0aMhhMC8efMuu2/1t8Thw4cDABYuXFjj55988kmNn1/JjTfeiH379mHLli2X/ay4uBg2m+2qz1EbRVHw6quv4uTJk5g+fTpatGhR530LCgpq/NvX1xeRkZE1lg5Wv86OatVw8U5KCIHFixfDZDLZh9HCwsJgMBgum1P58ssvL3uu+tZmMBgwePBgrF+/vsYZ8Lm5uVi5ciUSExOv+Do1Vnx8PIKCgrBkyZIar+2mTZtw8uTJOleHNUb//v3RvXt3LFy40L7Tr/4WfPHRzm+//XbZstxhw4bBZrPVeM0VRcHnn39+1e025rMxbNgw5OTk4KeffrLfZrPZsGjRIvj4+KBv374AgCFDhqCyshJfffWV/X6qqtZ4b9Wlti971auuqv82jn7PO4JTDR8tX7681h3X3XfffdXHenl5Yf78+bj77rtx3333YdGiRYiOjsaTTz6JXbt24c4778Qdd9yBzp07o6ioCIcPH8aOHTvw66+/XvW5Y2NjYTAYsGDBApSUlMDDwwMDBgyo8yjjoYceQnh4OK677jpERETAbDZj+/bt2LBhAxISEuxDXAMGDMCtt96KRYsWITU1FUOHDoWqqkhKSkL//v0xbdo0dO3aFRMmTMDSpUtRXFyMvn374uDBg1ixYgVGjRqFAQMGXLX+GTNm4JdffsGsWbMwYcIExMXFwWw249ixY1izZg3Wr19/1QnckpISfPfddwCqlvNVn9GclpaG8ePHX3WZ5/jx49GvXz/ExcUhICAABw8exJo1a2pMKMbFxQGoWqI5ZMgQ+3LXa+Hp6YktW7bg2WefRffu3bFlyxZs3LgRs2bNsv+ufn5+GDt2LD7//HNIkoSIiAhs3Lix1hMMG1LbY489hu3bt2PKlCmYMmUKDAYDli5dioqKihon+DUFk8mEp556Cs899xymTZuG8ePH25ekhoWFXbYE21FmzJiBRx99FN988w0mT56MESNGYO3atXj44YcxYsQIZGRkYMmSJejcubN9DgqoOp+ld+/eeOutt5CZmYnOnTtj7dq19foC1pjPxl133YWlS5dizpw5OHz4MMLCwrBmzRrs3bsXzz//vD24R40ahe7du+Nf//oX0tLS0LFjR/zyyy8oKioCcOVv+u+//z727NmD4cOHIywsDHl5efjiiy8QEhJiP6qOjIyEv78/lixZAl9fX/j4+KB79+6XzYc1J6cKhdq+oQHAxIkT6/X4Fi1a4H//+x+mTZuGP/3pT1i8eDHat2+PZcuW4f3338e6devw5ZdfIiAgAJ07d673iTqtW7fGyy+/jPnz5+OFF16Aoij47LPP6gyFV199FevXr8eqVauQnZ0NIQQiIiIwa9Ys3HfffTUmw1977TXExMTg66+/xuuvvw4/Pz/Ex8fXaOj26quvIjw8HCtWrMDPP/+M4OBgPPDAA7WuWqqNt7c3Fi1ahPnz52P16tX49ttv0aJFC3To0AF//vOf63VG7Llz5/DMM88AqFpt1KZNG/Ts2RMvvfQSBg8efNXHT58+Hb/88gu2bduGiooKhIaG4rHHHsOMGTPs9xk9ejSmT5+OH3/8Ed9//z2EENccCgaDAR999BFeeuklvPHGG/D19cUjjzyChx9+uMb9XnzxRdhsNixZsgQeHh4YO3YsnnnmmRqrUhpaW5cuXbB48WK89dZbmD9/PoQQ6N69O954443LzlFoChMnToSXlxcWLFiAN998Ez4+Phg1ahSefvrpGucSONLo0aMRGRmJjz/+GHfeeScmTpyI3NxcLF26FFu3bkXnzp3xxhtvYPXq1TW+iMmyjA8//BD/+Mc/8P3330OSJPuJj7fddttVt3utnw0vLy8sWrQIb775JlasWIHS0lJERUXhtddeq7G/qZ4H+fvf/44VK1ZAlmXccMMNePjhhy9b4XWpkSNHIjMzE8uXL0dBQQECAwPRr1+/Gp85k8mEf/7zn3j77bfx0ksvwWaz4bXXXtM0FCTRHLNZREQ68vPPP+Phhx/GF198cdW5NFejizkFIqKmYrFYavxbURQsWrQILVq0sA8r6olTDR8RETmbV155BRaLBb169UJFRQXWrl2Lffv24YknnnD4MmlnwOEjIqIr+OGHH/DJJ58gNTUVVqsV7du3x+TJk+t11rUrYigQEZEd5xSIiMiOoUBERHYMBSIismMoEBGRHUOBiIjsGApERGTHUCAiIjuGAhER2TEUiIjIjqFARER2DAUiIrJjKBARkR1DgYiI7BgKRERkx1AgIiI7hgIREdkxFIiIyI6hQEREdgwFIiKyYygQEZEdQ4GIiOwYCkREZMdQICIiO4YCERHZMRSIiMiOoUBERHYMBSIismMoEBGRHUOBiIjsGApERGTHUCAiIjuGAhER2TEUiIjIjqFARER2DAUiIrJjKBARkR1DgYiI7BgKRERkx1AgIiI7o9YFEDmaqgqoqgAkQJIkGGTJYc8tRNVzCwFAAgyyBEly3PMTaY2hQC7HpqiQJMAg/36gq6oCRWVW5BSYcT6/HPlFFpRaKlFurkS51YZySyXKLbYL/1XCbLVBUUWd25AAmIwyfLxM8PEyXv6/nkb4+3qgdaAP2rbyQVBLL/h4ma5aJ5Gzk4QQdX8yiDRUtVP9/Zu+xWpD2vkSnM4qQmZOKXIKzMgpNCO30IyCEmvV0YGGvDwMCA7wtv/XNtAHkSF+iAr1R9tWvpAv/B42RYUsSfZ/EzkThgI5BeVCAMiyhEqbivTzJTiVWYS088VIPVuCtPPFyC20aF3mNTMaZIS3aYH2IX6IDPFHZIgfOocHIDjAG0BVUHAoipwBQ4E0IRQbJEPV6KVQFVQqAp+sPIKU1AKcziqCTXGPt6W/rweiIwMR0z4Q3aJaIaZ9K3iaDFXzFhAceqJmx1CgZiFUFQAgyTIqC7NhPrUPlrSjMKcfhV/CcAQMvQsT5qzEhbu5LYMsoWNYS8R1DEJ8pyD07NIanh5G2BQVRgMDgpoeJ5qpyVQfDQjFBnPqYZQf34Pyk/tgKzhb436WjBTIBgP6dg3BriPnNKrWOSiqwPH0QhxPL8S3m07CaJDQLSoIfWLbol9cCMJat4AqqlY/OXJVFVE1HimQQwlFgWQwwFach7Jjv6L85F5YUg9DVFrrfIxk8kKHpxZhw94M/PvLfc1YretpE+iNxK5t0bdbW/To0hoeJgMURYWBRxHkIDxSoEarPiKwlRai9NAmlB7egopzp+v/+EoLKnLS0LVDcBNWqQ/ZBWas2nEGq3acgafJgL7d2mJE73AkxraFQZagCs5DUOMwFOiaVB8RqJYylB7ZitLDW2FJOwrg2g48LWmH0abHDY4tUueslQq2/paFrb9lwdfbhEEJ7TAiMRwJnYLtJ9fJXM1EDcRQoHoTQgBCAEJFWfJOlB7ajPJTvwGqrdHPbclIQcu+4xHRtgXSz5c6oFr3UmauxLpf07Du1zS08vfCkB6hGNUvElGhLTlJTQ3COQW6KqEqkGQDbMW5KNr9E0oObIBaXuzQbRj8gtB+9n/x1c/HsGjVUYc+tzuLjgzE+MEdMKxnOGRZgnSh9QdRXRgKVCehKoAkw3xyH4r2rIL51H5ANN2a0chHP8LJPIGn3tvSZNtwV/6+Hri+byRuHhKF1oE+nJymOnH4iGqo+o4goFrNKNm7FsX71sFWeL5Ztm1JO4KIqD7Nsi13U1xWgRUbT+DbTSfQO6YNbhrSEX1i23JoiS7DUCAAgBAqAAlqeTEKt3+D4n3rrriMtClY0pMR1HUgvDyMsFQ0fp6CLicEkJScjaTkbES09cMd13fB8F7hEELwyIEAcPjI7QlVhSTLsBXnomDbcpT+tgFCqdSkFo92nRD+p9cx96t9WLsrTZMa3FFIkA8mjeyCUX0jAYDh4OYYCm6qOgwq88+iYOvXKD28BVAVbYuSDejw9OfYnZKHVz/+Vdta3FBQSy9MGNEZNw7sAINB5hnTborDR26m+juArSgH+Rs+R1nyziadPG4QVYE16wQ6h0dpXYlbyiuy4KPvDmHZ+mOYOKIzbhnaqep6EDxycCsMBTciVBWqtRwFm5egeO9a7Y8MamFJO4LAAdFal+HWikor8MnKI1i57TTuHtcNI3qHc7WSG+Ff2Q0IVYGwVaJwx7dIe/9BFO9Z5ZSBAFxojmc0Ir5TkNaluL2cAjPeWpyEx/+9CcmpBQAAxd3b2LoBzinomFAUQJZRenAT8jd+AaUkT+uSrkr2aoEOTy7Equ2n8cHyA1qXQxfp260tZt4Sj3bBvgB4EpxecfhIh4QQkCQJ1nMnkbvqv6g4X//mdFpTLaWoyMtCXEceKTib3UfOIyk5G2MHtMe9N8XBwyhzSEmHGAo6UzVUVIHcnxeiZN/PuNYGdVqypB1GSLfhWpdBtVBVgZ+2n8GOg2dx/20JGNIzDKoqeL1pHWHM60T1lc3Kknch/cNHULJvHVwxEICqeQWThwnBLb20LoXqUFBixb8W7cFLC3Ygv9gCVXXN9xpdjqGgA0JVoZQW4OySvyN7xVtQSgu1LqlRrBnJkCQJ1/WJ0LoUuoqk5GzM+td6rNh0AqoqoCiciHZ1DAUXJlQFQqgo+vUHpP/nzzCf3Kt1SQ5RmX8WirkUvWLaaF0K1YO1QsGnK4/gsX9vxJmzxeDaFdfGUHBRQlWglBYg67O/IH/9Z83ep6ipWdKPokNIC63LoAY4nVWMJ9/djCXrUqqOGrh81SUxFFyMuHD2cenhbUj/7+OwZiRrXFHTsGQko4W3CUYj36KuRFEFvliTgjnvb0V+sZXB4IL4iXMhQlEgKq04v+LfyPn+XQhrudYlNRlLejIk2YCB8e20LoWuwdEz+Xj49V+waW8mAHAi2oUwFFyEEAKWrGPImP84yo5s1bqcJldx7hSEomBAAkPBVZmtNvz7y73416LdsFYqnIR2ETxPwckJVQUkoGDTEhRuX+E8zeuamLBVwHr+NGIiGAqubuv+LKScKcDT0/sgpn0gZJ4J7dR4pODEhKJAtZbh7OKXUbhtudsEQjVL2hEE+3toXQY5QE6hGc+9vxU/bD4FAFC5QslpMRSclBAqKrLPIGPBk7CkHtK6HE1YM1JgMJnQKayl1qWQAyiqwEffH8Lri/bAZlM5nOSkGApOquS3Dchc+LxLNLFrKpbMqpVVw3uHa1wJOdKW/Zl44p1NyC+2MBicEEPBiQhVhVBV5K5egNwfPwAU975OsVJaCFtxLrp3Dta6FHKw1HMlePTtjThyOp8nuzkZhoKTEIoCtcKMs1+8jOKk1VqX4zTMqYcRFuyjdRnUBErKK/Hi/O34YcsprUuhizAUnIBQFChlhcj6ZI7bzh/UxZKRAk9PI/x8TFqXQk1AVQUWfHcIC749WPVvHjVojqGgMaEqqMzLROYnz6AyP0vrcpxOVXM8GcN7cV5Bz77fcgr/WrQbqip4opvGeJ6ChoSqwpJ2FOeW/ROiwnzZz3/NKMGywzlIK7SivFJFsI8RAyP8MbVHG/h6GDSouPlV5KRDrbCgT7e2WLnNdS4WREBJ1gEUZ+6FtSgTSmU5PHyDEdBhCPwj+tR61bat+7NQVFKBv8zozwv4aIihoBEhBMqObkf293MBtfYJ5dIKBV2DfXBr1yD4expwptCKxb9l40yhBf+4IaqZK9aIUGHNPIZOoV20roQaqODUZph8AtG623gYPFqgLOc4zh/4GjZLIYKib6j1MQdP5uKZuVvwygOD0MLHBCODodkxFDRStOt75K9fhCtdCGdkx4Aa/+4e0gImWcJ7O7OQV16JIDcZZzenH0FAZDfIMsD+aq4jrN8fYfDwtf/bJ7gz1MoyFJzaglZdrock1b7DP3O2GE+8uwmvPDAIIa18eMTQzPhqayDvl8+Rv/4zXMuV0fw9q4aNbG407mrNSIFsMKJXNK+v4EouDoRqnv5hUG0WCKXiio/NKTDjqXc3I/VcCc9laGYMhWaW98siFO1Y0aDHKKpAhaLiRJ4ZXxzIwYBwP7Rt4T7tHyyZxyGEiiE9QrUuhRrJnH8aRq+WkI1Xv9RqqbkSz3+4jcHQzDh81IyqAuHbBj/unm9SkFdeNe/QJ7QFnh3qXpepFBVmVOZmoGuHIK1LoUYw559GSdZvaN3tpno/puxCMPzjwcFoH+LHoaRmwFe4mVxrIADAK9d3wNs3dsSjA0ORVmTFSxtSobjR8BFQdRJb2wD3OTrSm0pzIbKSFsMnuBMCogY36LFlPGJoVgyFZtCYQACAqEAvxLb2wdgurfC36yLx27kybE8vdlyBLsCakQKThwdCgy8fpybnplSakfnrxzB4+KBd4vQ6J5ivhMHQfBgKTayxgXCpqEAvGGUJZ4uvPFGnN5aMFADAiESexOZKVKUSmb9+ArXSgrB+M2AweV/zczEYmgdDoQkVbPnKoYEAAMm5ZthUgRA/9xpKsRVlQykrQk+uQHIZQlVwNulzVJRmI6z/DJi8G98CvcxciRc+3IZz+eUMhibCieYmIISKkv2/oGDz0kY9zysb09AlyAtRgV7wMMg4XWDB14dzERXohYERfg6q1nWY048iMrKX1mVQPWUfWoGy7KNo3e0mqDYLzAWp9p95+odBNlzb7qfUXIm//Gc73n5sGPx8PDj57GAMBQcTqgLzqf3IXTW/0c8VE+SNTWeK8NWhXAgBtG1hwtgugbi9WzBMbvhBsKYfRavofvA0ybBW8luisyvLOQ4AyDmy8rKfRY2cA9mn1TU/d06hGS/+ZzvemD0MnpIEWeYlPh1FEmxm7jBCVVBx7jSyPv8rRKVV63J0xzO0C8L++E+88+VerN+TrnU55AQSOgXj/x4YCFmWeO1nB3G/r5tNRKgKbEW5OLv07wyEJmI9dxrCVon+8SFal0JO4uDJXLz1RRIDwYEYCg4gVAWqpQxnF78Etdy9loo2K9UG69mT6BIRoHUl5ES27s+yX4+BGo+h0EhCCEAInF3yKmxF2VqXo3uW9KNo5UYtPqh+vt9yCj9sOcWL9DgAQ6GRJElCzo8foOLsSa1LcQuWjGTIRiNiOwRqXQo5mf99fwjJZ/K5VLWRGAqNIISKol9/ROnBTVqX4jaqT2Ibxiux0SUUVeC1T3ejqKwCCnusXzOGwjUSqgJLRgry1i/UuhS3oppLUFlwDvGdgrUuhZxQYakVr368C0K9MLRLDcZQuAZCVaCUFyN7+RuAqmhdjtuxpB1Gu1ZXb71M7ul4eiHmfb2/1kt+0tUxFBqoemL5/FevQSkr0roct2RJT4GHhwmBfp5al0JOav3udPy47RRUN+sm7AgMhQaSJAm5q+bDyollzVgykiFJEq5LdK/rSlDDfPTdIRxLK4CNE88NwlBoAKEqKD28FSW//aJ1KW6tMi8LqrUcvWPZHI/qZlMEXv98DyptKo8YGoChUE9CVaCUFTmkpxE1loA5/SiiQtyvKSA1TE6BGXO/2s/eSA3AUKgvSUb2in9DtZZrXQkBsKYnw8/bBCPfwXQVW/ZnYkNSOpep1hM/UvUghIrC7d/Akn5E61LoAktGMiSDAX3j2mldCrmA/3xzAPnFVgZDPTAUrkIoCirOn2n0tRHIsaxZJyBUBYO6h2pdCrmAcosNbyzaAwkcRroahsIVCCEghILsFW/zfAQnI2wVqMhORddItrug+jl6Jh9Lf07hSW1XwVC4AkmSkLfuE1Tmn9W6FKqFJe0IgluyOR7V35J1x3Aqs4j9ka6AoVAHoVS1sSjZu07rUqgOlowUGE0mtG/HVUhUP6oq8O7SfTzb+QoYCnWRgJwfPwTAQ01nZclIBgBc15snsVH9nc4qxnebT/LchTowFGpRtdpoBSpzeclHZ6aU5MNWko/uXdgcjxpm8Zpk5BdbGAy1YChcouqymjko3LZc61KoHiyphxEe7KN1GeRirBUK5i3jSW21YShcQpINyPnxQwhbhdalUD1YMlPg5WmCj5dR61LIxSQlZ2Pr/kxOOl+CoXARoSooObARljO83qursKQnQ5JlDOdFd+gazP/2ICpsKpepXoShcBFRWcGL5riYiuxUqJVW9I1rq3Up5IIKS6z4dOVhrctwKgyFC4QQKNjyFdTyYq1LoYYQKqxZx9EptKXWlZCLWrMzFWdzy9gC4wKGAqpWGykl+Sjes0rrUugaWNKOIqCFSesyyEUpqsD/fjgMg8zdIcBQAABIkoy89Z9BKJVal0LXwJKRDNlgRE8uTaVr9Ovhczh8Ko+TzmAoQKgKrOdOoezINq1LoWtkzTwGIQSG9grTuhRyYR99dwgGg9vvEhkKkmxA3rpPwDOXXZdqLUdlXiZiOwRpXQq5sBMZhdi0N8PtjxbcOhSEYkPZ8d2wpPE6Ca7OknYYIYGeWpdBLu6zn464/ddDtw4FyDLy1y/SugpyAEtGCkweHmgT6K11KeTCsgvM+H7zSShu3P7CbUNBKApKD21FZV6m1qWQA1gyUgAA1yWyOR41zvINJ9x6CMltQwGyjMKty7SughzEVnAOirkEvWLaaF0Kubjisgqs3HrKbc9bcMtQEKqCiuxUVOZnaV0KOZAl7Sjat22hdRmkAys2noSiuOcQkluGgiQb4Nm2AyKf/hyB102Dm74MumNJPwpfbyM8jPx7UuMUllqxascZtxxGcrtPj6Iq2JN5AC9veAfHCtMROGgCIp/5HEFj7wNkdtp0ZZaMFEiyAQO7t9O6FNKBbzedANyws7bb7QUNsgErjq7G8bzTOJydgi5BUZjUbRx6JY6Fb4+RMB/Zjpw1C4AKi9alUgNVnDsFodgwMD4Um/ZyAQE1Tm6hBRuSMjCidziMbnRSm1uFgqIqSMk9heN5p+23Hc87jde2vI8OAeGY2O1G9E8YDu+4wbAcT0Lujx9CtZRqWDE1hFAqYT13Cl0i2EabHGP5L8cxqm+k1mU0K7cKBYNswA8p62r92ZnCDLy9fQHC/EJwW7cxGBrTDxFd+sBy5iByVn4AtTS/maula2FJO4qgvlFal0E6kZFdij1Hz6NXdGu3aYHhHr8lqlpj55UXYO/ZQ1e8X2bJOby/ayFm//g3/HJ6BzyjuiPiz/9Bu+mvwBjInv3OzpKRDIPRhOjIAK1LIZ1YufWU2wQC4E6hAIHVxzfW+wpL2WW5WJD0BR5e+QJWHd8AY1gXhM2ai9A//hOm1u51OOlKrJlVJ7HxSmzkKPtSspFTUO42V2dzm1BQhcCG0zsa/LgCcxE+278cs354Ht8lrwXaRCLsvrcQdt/b8Ajt0gSVUmMoZUWoLMxGfCe20SbHUAWwcttpuEkmuEco2FQFO9KTUGwtuebnKLGWYsnB7zHr++fw1aGVsAW0Rui9/0D4rLnwjurhwGqpsSxphxEWxB5I5Dg//5oG1U36IblFKBhlA9Yc3+SQ5yqvNOObI6sw64fnsWj/NzD7+iFk8l8Q8fCH8Inu75BtUONYMlLg4WlCS18PrUshnSguq8CW/ZmwucHJbLoPBVWoSC/KwrG8Uw59XqvNih+PrcdDPzyPj5KWoNjDhJA7nkHE7AVo0X2EQ7dFDWPJSIYkSRjRm83xyHF+3HbaLc5X0P1vKEHCquMbmuz5K1Ub1p3cjEdWvoj3dy1EnqSgzc1/RsTjn8C/z7gm2y7VrTInA2qFGYnd2ByPHCclrQBnzhZD1fnkgu5DQREqtqclNct2Np3ZiUd/+hv+vX0BzlWWInjMDEQ++RkCBt/e5NuniwlY0lPQsZ2f1oWQzvz8a6ruL9Ko61BQVAX7zh5CeaW52bYphMCO9L14cvUr+Ofm95FanotWI6aw+V4zs2QchZ+PB2S+3ORAW/ZnQdJ5PyRdn9FskA3YmvqrZtvfe/YQ9p49hPg2MZgUNw7dBk2AX99xKPvtF+St+xRQbZrVpneW9GTIBgP6dg3BriPntC6HdCK/2ILDp/IQG9UKBp1+49B1KFhtFUjKOqh1GTiUnYJD2SmIDuqI2+PGoVefG+Hb83o232tC1qwTEELFoB7tGArkUBuS0hHXMUjrMpqMPqMOVUNHuzL2oUKp1LoUu2N5p/Da5nl4Zs3fsefsIbRIGI7IJz5Fm4lPQfbixWEcSVRaUJGdjq7tW2ldCunMtgNndX3Ogm6PFAyyAdvSdmtdRq0ubr43odtYDOnaHxHRfWE5cwA5Kz9k8z0HsaQdRpseo7Qug3SmzFyJpJRsJMa00WVPJP39RheUVZTjwLmjWpdxRZkl5zBv16eY/ePfsOHMDnhG9ahqvjft/9h8zwEsGSkwenggvA2PwsixNiZl6DIQAJ2Ggk1VsD09CYpwjbMPs8ty8d89Vc33Vh/fCGN4NJvvOYAlIxkAcF0iT2Ijx/r1yDlUVCpal9EkdBkKRtmApMwDWpfRYAXmIizc/zUe/OEFfJ+8js33GkkpzoWttBA9urA5HjmWtULBgRO5UFTX+OLZELoMBZtqw+HsY1qXcc2KrSX48uB3tTTfew9eHbprXZ5LsaQdQUQbX63LIB3afeQcJB2etKC7UFBVFUeyj8OqVGhdSqNd3Hzv89++gcXXH+2m/JXN9xrAkpEMb08TvDx0u6aCNJKUnA2ZoeACJDjFuQmOZLVZsTJlPR680HyvxMPj9+Z7CcO1Ls+pWTOSIckyhvYK1boU0pnz+eXIytXfNdx1FwqyJGPfVS656aqqm+89vPIFvL9rIfIlBW1umV3VfC/xRq3Lc0rW82eg2iowIC5E61JIh3YdOqe7dtq6C4XssjycK83RuowmVd18b/ZPf8O/t39U1Xxv7ExEsPne5VQF1qwT6BQeoHUlpEN7ks/rrp22rgZabarikquOrlVV870k7EhPQmJoAibFjUenEVPgN2gCSvesQsGGLwHo61vMtbCkH0VgaLTWZZAOHTmVD2ulAk+TQetSHEZXEWeUDdh/7ojWZWgiKesgnlv3T7yy8V0cL8xA4KCJiHzmcwSNmQnIusr+BrNkJEM2GhHfSb/9akgbNkXFb8dydLU0VXd7i5Tck1qXoKmD55Nx8HwyYoI74vZu49DT3nxvG3JWLQBsVq1LbHbWjKrlycN6huHQyTyNqyG9OXw6D4mx+ulAoKtQyCo+36zXTnBmKbmn8I/N8xAVGIGJ3W5Ev4QR8I4bAsuxPcj96T9QLfpbNVEX1VKKivwsXXe2JO0kn8mHQdbP0lTdhIJNVXAkx3VPWGsqpwvS8da2/yLMPwQTYi9qvnf6AHJ+dJ/me5a0IwiJHaZ1GaRDx9MLoSiqbnoh6eO3AGCQZKTkntK6DKeVWVyz+Z5Xx+rmey/DGKCfQ9+6WNKTYfIwIbill9alkM5U2lSczCyC0Mm1m3UTCpIkuf18Qn383nzvRaw+sQnG8BiEPTgXoffqu/meNSMFkiRhRGK41qWQDh0+lQdFJ9dY0E0olFaU6f78BEfKNxdi4b5lvzffa3uh+d7Mt3TZfK8yPwuKpQy9u+r/qIia39Ez+bo5X0EXv4Wqqjiac0LrMlxSdfO9B79/HssOrYQtsA1C731Nl833LOlH0SGE11Ygxzt6Rj9zc7oIBQHgGOcTGqWsshzL7c33ll/SfK+v1uU5hCX9KFp4m2A06uJtT06ksMSK3EJ9rHzUxafDIMtIK8rUugxduLj53v/2Vjffm4OI2Qvg6+LN96wZKZBkAwbGt9O6FNKhk5mFurh2sy5CAQDSi85qXYKuVKo2rD1R1Xzvg18/Q76kou0tsxHx+Mcu23zPevYkhKJgQAJDgRwv9WyJLkJBF+cpWG0VyC3Xz5ieM1GEio2nd2DTmZ0YEN4bd8SNR/jYmWg5YjKKd3yLou3faF1ivQlbBSrOn0ZMBEOBHC/tfIkuhiZ1EQoZxTxKaGrVzfd2pu9F79AETIobh07XTUXLwRNRsnsVCja6RvM9c/pRBPdur3UZpEOpZ4u1LsEhXD7WbKqCM4UZWpfhNgQEkrIO/N58rygTgYOrm+/NcPrme9b0ZBhMJnQMbal1KaQzmTmlHD5yBrIkIb0oS+sy3NLlzffGwbfnKJgPb0POaudsvmfJTAYAjEgMx6msIo2rIT2ptKnILihHSJBrXxNcB6EgMxQ09nvzvUhM7HYj+ve4Dt7xQ2A5tvtC870yrUu0U0oLYSvORffOwVqXQjp0KrMIbQJ9ILtwgzyXDwWAcwrO4nRBGt7aNh9h/iGYGHsjBncdgIjofrCc+g05P34AtaxQ6xIBAObUwwjrMlDrMkiH0s6XoF9cCGS4bii4/JyCoiooNOtjgkcvMovPYe6uT/Doj3/DhjM74dWpJyJm/9dpmu9ZM1Pg6WmEn49J61JIZ7Lzy12+jbbLh0KhpRgCrj+5o0fny3Lx3z2La2m+9xpMrSM0q8uSngxJkjG8F5vjkWPlFpohSQwFTfH8BOd3efO99gi77+2q5nvtmr/5XkVOOtQKC/p00/6ohfQlRwetLlw6FBRVQXYZL6/oKmo23/uxqvneH/+B8Afeg1f7hOYrRKiwZh5DpzD/5tsmuQU99D9y6VAQEMgrL9C6DGqgquZ7P2HWD89j8W8rYPFriXZT/4bwhz+AT5fmab5nST8Kfx8TXPxIn5yMpUJBuaVS6zIaxaVDQZZkhoILs9qs+CHlZzz4w/P4eO9SlHp4IuTOC8334pu2+Z4lIxmywYjeMW2adDvkfvKLLVqX0CguHwq5DAWXV6lUYs2JTXj4xxd/b75362xEPPYx/BPHNsk2LZnHIYTAkB6hTfL85L7O55W79KU5Xf48hXwzQ0EvFFWxN98bGJ6ISXHjED72vgvN975zaPM9UWFGZW4GunYIcthzEgFVk82KKmA0uObYpMuHQonVec6WJccQQmB7+h7sSE9C79AE3BE3Hh2boPmeOe0w2iaMbHzBRBcpLquAK6+Sd/lQKK90/dl+ql11872krANIaNsVk+LGI3bwRPj1G4+y/euR9/NCQLVd8/NbM1LQMnEsQoN9kZXLLxfkGOWWSrjwCc2uHwpmm2tP6lD9/N58rxMmdRuHHn3HwbdX45rvWdJ/b473xZoUR5dMbqrcYnPps5pdeqLZaqtw6QkdariU3JP4++a5eHbta0g6dwR+Pa5D5FML0Wbik5C9Gtad0laUDaW8GD2jWzdRteSOyi2VLn1Ws0sfKVicsDUzNY/q5nvh/u0wodvYa26+Z0k7gsjIXk1bLLmVcsu1D2k6A5c+UuB8AmUUn8XcnZ/g0Z9ewsaLmu+FTH2pXs33LOnJ8PEywdPk0h8FciLlVoaCZhgKVO18aQ7m71mMR1b+BWtObIIpIrZezfcsGcmQZBlDeoQ1Y7WkZ2VmntGsmbKKcq1LICeTZy7Ap/uW4aEfnscPKT9f1HzvTXi063zZ/a3nTkMoNvSPD9GgWtIjM48UtCGEgJVzClSHImsJvjjwrb35ntIqBKF/fO1C87343++o2mA9exJdwgM0q5X0xVqpaF1Co7hsKACAypVHdBX25nvfP4fFv317ofneSwh/+AN4X2i+Z0k7glZ+HhpXSnqhqq69X3LZ1UcCAqoDzmol92CxWfFDyjqsPrERI6MGYUK3sWh35xxUluTDfHwPZKMRsR0CcfQM26ZQ47j6MnlJuOhvoKoqdmbsxTs7/qd1KeSCDLIBw9r3w+3dxqFNi2Coqoq8IgvO5vHMZmocgywjrqPr9tRy2SMFosZQVAUbTu/AxgvN926LHY1A7wC0D/fSujRyca584hrgyqEguf6LT9qrbr63PX2P1qWQTvh6+OCTCW9pXcY1c+GJZgmyK5dPRLoku3I3PLhwKEgAZB4pEJGTkSWX3a0CcOVQkCQYZNcd/SIifTLIBq1LaBSXDQUA8PXw1roEIqIavI2uvVjBtUPB5KN1CURENfi4+JdVlw4Fb5NrJzIR6Q+PFDTEUCAiZ+Nj4pGCZryMnlqXQERUg6t/WXXpUJAlGR4Gk9ZlEBHZ+Zi8oKiu25fNpUMBcP1DNSLSFx+TN4QLN+t0+VDgCiQiciY+Hq69T3L5UAj0bql1CUREdq28Wrp0Cx7XrfyCIJ9ArUsgIrJr0yIIsuy6u1bXrRyATVUYCkTkVIJ8WmldQqO4dCgAgqFARE5DlmT4e7bQuoxGcelQMEgGBLt4KhORfgR6t2SXVC1JkoQ2vq572Tsi0pdgHYxcuHQoAEAr7wCtSyAiAgAEebv+yIXLh4K3yYvtLojIKQT5BEJRFa3LaBSXDwUACPVrq3UJREQI9WsDoXURjaSLUIhoGap1CUREaB8YDiOvvKYtm2pjKBCRUwj3b6d1CY3m8qFgkAyIZCgQkcaCfAJ1Mb/p8qEgSRLaB4RrXQYRubkIf318OXX5UACqThhx9UvgEZFri2gZ6tLXUaimi1AAgPCWrj+WR0SuK6JlOwiXX3ukk1AQQnBegYg01SEwwuVXHgE6CQVFKOjYqr3WZRCRmzLJRl2sPAJ0EgpG2YhurbtoXQYRuamowEhdHCUAOgkFoOqsZl6vmYi0EBPcCapw/UlmQEehIEkSugRFaV0GEbmhrsEdIVx/jhmAjkJBURXEBHfUugwickOxbbrA4MKX4LyYPn4LVF3xKJbzCkTUzNq2aI0WHr5al+EwugkFSZLQpVUHl7/qERG5lq7BnbQuwaF0tQf1MHqgfUCY1mUQkRuJDu4Im2rTugyH0VUoqEJFfJsYrcsgIjfSMyQORtmodRkOo6tQAIDE0AStSyAiN9GuRRu09nX9S3BeTFehIEsyYoI7sTkeETWLnu3idHN+QjVdhQIAGGQD4ttyCImIml5iaAJ00AOvBt2Fgk1V0LtdvNZlEJHOeRo80K1NNGSdnJ9QTV+/DQCjbECfsO5al0FEOhfXJlo3/Y4uprtQAICWXv5cmkpETapXaDxsqqJ1GQ6ny1BQVBW9OIRERE2oT2h3Him4ClmSMCgiUesyiEinogIjEeQTqHUZTUKXoSBJEjoERqBdizZal0JEOjSkfV8oOhw6AnQaCkBV19TB7ftqXQYR6YwkSRjWvh8MOhw6AnQcCrIkY3iH/lqXQUQ6ExvcGS29/LUuo8noNhQkSULbFq0RFRihdSlEpCND2vfV5aqjaroNBaBqCGlIJIeQiMgxDLIBgyL76HLVUTVdh4JBNmBo+/6QIGldChHpQM+Qbrq/FryuQwEAArz9Edu6s9ZlEJEODG3fT7erjqrpPhQUVcENnYZqXQYRuTh/Tz/0C++l21VH1XQfCgbZgAERvdHS00/rUojIhV0XNRCypP+haN2HAlC1Emlkx8Fal0FELkqSJIztMsIt5ifdIxQgYWyX4ZDcIOWJyPF6hcQhyCfQLfYh7hEKkoRA7wD0bsdLdRJRw43tMkL3E8zV3CIUgKoJ5xu7jNC6DCJyMW19g9EjpJvuJ5iruU0oGGQDuofEom2L1lqXQkQuZFSnobq7DvOVuE0oAFVHC2N5tEBE9eRp8MANnYa6zVEC4GahYJANuKHTUPh5+GpdChG5gJEdB8Pb5KV1Gc3KrUIBqLqGM48WiOhqDLIBt8WO1rqMZud2oSBLMsZHXw9Po6fWpRCRExsS2ReB3gFusQz1Ym4XCgDgZfLCaLa+IKI6SJKE27vd6FYTzNXcMhQkALfFjoGHwaR1KUTkhAZFJCLErw1kyf12ke73G6PqW0ALD1+M4tECEV1CgoQ74m9yy6MEwE1DodrE2LEw8WiBiC4yIKIXQv3auuVRAuDGoSBJElp4+mJcl+u0LoWInIRBkjGl+wSoqnseJQBuHApA1Uqk2+PGwc+zhdalEJETGNVpKNr4BkGW3XfX6L6/+QUm2YhJceO0LoOINOZt8sIfEm7RugzNuX0oGGQDRncajnYt2mhdChFp6LauY+Bt8nK78xIu5fahUEVgao+JWhdBRBoJ8gnEzV1Hue3k8sX4CqDqaKFfeA90De6sdSlEpIEpCbe5xVXV6oOhcIGiKrin1yStyyCiZhYVGIGhHfq5VSfUK2EoXGCQDejUqj1GRA3UuhQiaiYSJMxMnOw2V1WrD4bCRYQQuKfnJC5RJXITozoNQZegKB4lXIShcBFJkuBl9MQ9PTmMRKR3AV7+mNZjIoQQWpfiVBgKlzDIBgzr0B8JbbtqXQoRNaE/9b4LHgaT2y9BvRRDoRaqquKBvtPYF4lIp3q1i8eAiN4cNqoFQ6EWsiwj2CcQt3e7UetSiMjBPI2eeKDPVLftgno1DIU6yJKMW7uOQUTLUK1LISIHujP+JgR4+/NEtTrwVbkigT/3v5eHmEQ6ERPcCeOjRzIQroCvzBUYZAMiA8JxZ9xNWpdCRI3kbfLCYwNngIuNroyhcBWyJOG22DHo1rqL1qUQUSPMTJyMAK+WMLhxW+z64KtTDwICswf+Cb4mH61LIaJrMKR9Xwxt34+BUA98hepBlmS09PTD/X2maF0KETVQa59WuL/PVJ6kVk8MhXoyyAYMjEzEsA79tS6FiOpJkiTMHjgDJtnIk9TqiaHQAEIIzEycjLa+wVqXQkT1MCF2LKLZ26hBGAoNIEkSTLIRzwx9EJ4GD63LIaIr6BESi7vib+YRQgMxFBrIIBsQ6heCB/tN17oUIqpDG99gPD7oPghwHqGhGArXwCDLGBTZBzfFXK91KUR0CU+DB569cDTPk9Qajq9YI0zrMZHdVImczIP9piPUL4TzCNeIodAYAnhi0H1o7dNK60qICMBNMddjUGQfno/QCHzlGkGWZXgZPfHs0IfgwTbbRJpKaNsV03pM1LoMl8dQaCSDbEB4y3b484A/cpUDkUZC/driiUH3gfPKjcdQcABZktEvrCfu7XmH1qUQuZ1Ar5b4y4hH4WX0hMxho0bjK+ggkiThxujrcGvX0VqXQuQ2vE1eeGHEbAR4+XNi2UEYCg42tccEDG3fT+syiHTPKBvxzJAHEebXloHgQAwFBxNC4KF+96B721itSyHSLQkSHu53N2Jbd2YgOBhDwcEkSYIkAU8PmYWowAityyHSpWk9JmBQZB+enNYE+Io2AVmSYZQNeHH4bIT5hWhdDpGu3Np1NG7uegNX+zURhkITMcgG+Ji88fL1TyLUr63W5RDpwq1dR2Nqjwlal6FrDIUmZJAN8DV54/+uf4rBQNRIDITmwVBoYgwGosZjIDQfhkIzYDAQXTsGQvNiKDQTBgNRwzEQmp8keDXrZqWoCsorzXh101ycLkjTuhwip3Vn/E2YFDde6zLcDkNBA4qqwKYqeGPrf3Dg/FGtyyFyKrIk4/4+UzCy42CtS3FLDAWNqEKFEMAHvy7EltRftS6HyCl4GjzwxKD70KNdHGSeh6AJhoKGhBCQJAmLf1uB75LXal0Okab8PFvg+WGPoENABC+SoyGGgpNYdWwDPt2/DPxzkDtq4xuMv4x4FME+gexlpDGGgpMQQmBXxj7M2/UpKpRKrcshajYdAyPx/PA/w9fkzUBwAgwFJ6IKFWmFWfjXlg+QZy7QuhyiJjekfV882PduyJLEQHASDAUnU71k9fWt/0FK7kmtyyFqEpIkYUrCbbg1drR9bo2cA0PBCamqCgGBj/d+hXUnN2tdDpFDtfDwxaMDZ6B7264MAyfEUHBS1d+eNp3ZiQV7vuA8A+lCVGAEnh7yIAJ5+UynxVBwcqpQkVF8Dm9s+RDny3K1Lofoml0XNRD39ZkCCZw/cGYMBRegqAoqVRs+SvoSm8/s0rocogbxMXnj/j5TMCiyD+cPXABDwUVUf5h2pCXhv3u+QFlludYlEV1VbOsueHTgn9DS049HBy6CoeBiFFVBsbUU7+74H47kHNe6HKJaGWQD7oy7CbfFjoEQAjLPUHYZDAUXpKoqJEnCd8lrsfTQD1BUReuSiOza+bXF4wNnIDIgnP2LXBBDwYWpQiCtMBNzd32C9KIsrcshNydBwqhOQ3FPr0kwSDKHi1wUQ8HFVR0lSPgueQ2WH1mFShdYupq/7yzSV1zeMrz1kEiEju6sQUXUWOH+7fBgv+noEhTFyWQXx1DQCVWoyC0vwPzdn+Pg+WSty7mi6lCImt4DBi+j/XaTvyc8WnppWBk1lMlgwu3dbsStXUcDAI8OdMB49buQK5AlGcHegfjLiEex5cyv+HT/MpRYS7Uu64p8Qv1g9PXQugy6Rgltu+KBPlMR7NsKssSJZL1gKOhI9QqPQZGJ6B0aj8/2f40Np3doXBXpjZ9nC9zb8w4M7dAPqqoyEHSGw0c6VT2uezI/FZ/uW+ZUzfWqh4+MvibYyivhEeCFVomhaDOkPSSZY9HOyiQbMbbLdZgUNw4eBhOHinSKoaBziqrAIBvwa8ZvWPzbNzhbmq11SSg+nofyjGL4hPtDkoCi5Fzk7c5EUN8whN8Uo3V5dAkJEgZF9sG0HhPQyjuAk8g6x1BwE9WrlNae3ISvD//kdPMNWWtOIGdHOro9OQgmP0+ty6ELYlt3wb297kBUYARUwaEid8BQcDOKqqJSrcTywz/hp+MbnGYJa3lmMY7P34OoaT3gHx2kdTluL9SvLab3mIjEsO72o01yD5xodjMGWYZB9sTk7rfh5phR+C55Ldae3AKrzap1aeQEIlqGYkLsWAyKTLRfL5yB4F54pODGhBAQEDBXWrEy5WesPr5Rs0Z7WauPI2dnBoePNNIxMBK3x41D37AePDJwcwwFAlB18luFUolVxzbgx2O/oNha0mTbOrlwP/w6BsKrrS8AoDg5F3lJWQgeEIGwG7s02Xbpcl2DO2NS3Dh0D4llGBAAhgJdQlFVqELBupNbsPr4RpwrzXH4NjJ/Oobi43moLLYCAvAM8karxFAE9w/nypZmIEkSereLx21dxyCmdSeGAdXAUKBaVe8oDpw7itXHN2Lv2UNQhap1WdQI/p5+GNlxEMZ2HoFWPgEMA6oVQ4GuqHrHUWAuxOrjm/DLqW0oasKhJXK8mOCOGNN5BAZG9IYkSZAg8YiM6sRQoHqpnpQWQmBnxj78fHILjuQcB98+zsnX5INBkYkY22UEIlqG8qiA6o2hQA1WvYMptBRjS+qv2Jq6G6cL0rQuy+15GjyQGNodQ9r3Ra92cZAlGQKCJ5xRgzAUqFGqA+J8aS42n9mJrWl7cLbkvNZluQ2DJKN7SDcMad8X/cN6wsPowaMCahSGAjmEEAKqUGGQDThTmIEdaUnYe/YQUgsztC5NdzyNnohvE4PeofEYFJEIXw8f2FQFRgYBOQBDgRyuKiAEDLKMIksx9mQdxL6sQzh4Phlmm0Xr8lxSuxZt0Cs0HomhCYht3QVG2cAgoCbBUKAmV73zUlQFKbmnkJR1EAfPH0VqUSYnquvgY/JGTHAn9Azphj5h3dHaN8i+JJhzBNSUGArUrC7esVlsVqTknsKR7GNIyT2JkwVpbtuDKcgnENFBHdG1dSfEt4lBuH87SJLEowFqdgwF0pQqVAhR1ahPFSoyi88hOecEThWkIb3oLNKLs2Cu1M+QkwQJwT6BCG8ZisiWoegSFIWY4E5o6eUHALCpNhhl9qkk7TAUyOnYVBsMksF+glWhuRipRRlIK8xEevFZpBdlIav4vFPPT0iQEOjdEhEt2yHcvyoA2geEI9w/BB7GqutSV1/jwiBzOIicB0OBXIIQAopQanyLttisyC8vRHZZLvLKC5BbXoA8cwHyyguQby5EeYUZ5ZVmWJUKh9UhSRJ8jN7wNnnBz7MFgn0CEeQTiCDvAAT5tEJr3yC09m2Flp5+9mWhqlChCsFhIHIJDAVyeVWBUTVXUduOVxUqLDYrLDarPShKK8qhCKXO55QgwdPoAV+TD3w8vOFj9IKX0dP+Lb/m8wuoQoEEmd/6yeUxFIiIyI5fa4iIyI6hQEREdgwFIiKyYygQEZEdQ4GIiOwYCkREZMdQICIiO4YCERHZMRSIiMiOoUBERHYMBSIismMoEBGRHUOBiIjsGApERGTHUCAiIjuGAhER2TEUiIjIjqFARER2DAUiIrJjKBARkR1DgYiI7BgKRERkx1AgIiI7hgIREdkxFIiIyI6hQEREdgwFIiKyYygQEZEdQ4GIiOwYCkREZMdQICIiO4YCERHZMRSIiMiOoUBERHYMBSIismMoEBGRHUOBiIjsGApERGTHUCAiIjuGAhER2TEUiIjIjqFARER2DAUiIrJjKBARkR1DgYiI7BgKRERk9/9odEfgy7lScQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pie_df = (\n",
+    "    rad_df[\"LikertScore\"].value_counts().reset_index().sort_values(by=\"LikertScore\")\n",
+    ")\n",
+    "plt.pie(\n",
+    "    pie_df[\"count\"].values,\n",
+    "    labels=pie_df[\"LikertScore\"].values,\n",
+    "    labeldistance=0.9,\n",
+    ")\n",
+    "plt.title(\"Likert Score Distribution for Radiologist\")"
    ]
   },
   {
@@ -289,7 +334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -367,15 +412,101 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
     "add_metrics_to_df(rad_df)\n",
     "add_metrics_to_df(ne_df)\n",
     "\n",
-    "xdf = pd.concat([rad_df, ne_df])\n",
-    "xdf.replace({\"rad1\": \"Radiologist\", \"ne1\": \"Non-expert\"}, inplace=True)"
+    "xdf = pd.concat([rad_df, ne_df])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>dice</th>\n",
+       "      <th>hausdorff_distance_95</th>\n",
+       "      <th>mean_surface_distance_tol_7</th>\n",
+       "      <th>mean_surface_distance</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Reviewer</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Non-expert</th>\n",
+       "      <td>0.900939</td>\n",
+       "      <td>33.208145</td>\n",
+       "      <td>0.847362</td>\n",
+       "      <td>6.434494</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Radiologist</th>\n",
+       "      <td>0.910815</td>\n",
+       "      <td>14.663781</td>\n",
+       "      <td>0.885720</td>\n",
+       "      <td>3.651561</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 dice  hausdorff_distance_95  mean_surface_distance_tol_7  \\\n",
+       "Reviewer                                                                    \n",
+       "Non-expert   0.900939              33.208145                     0.847362   \n",
+       "Radiologist  0.910815              14.663781                     0.885720   \n",
+       "\n",
+       "             mean_surface_distance  \n",
+       "Reviewer                            \n",
+       "Non-expert                6.434494  \n",
+       "Radiologist               3.651561  "
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "xdf[\n",
+    "    [\n",
+    "        \"Reviewer\",\n",
+    "        \"dice\",\n",
+    "        \"hausdorff_distance_95\",\n",
+    "        \"mean_surface_distance_tol_7\",\n",
+    "        \"mean_surface_distance\",\n",
+    "    ]\n",
+    "].replace([np.inf, -np.inf], np.nan).dropna().groupby(\"Reviewer\").mean()"
    ]
   },
   {
@@ -387,22 +518,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f845d7d0520>"
+       "<seaborn.axisgrid.FacetGrid at 0x7f39b2a683a0>"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 1 Axes>"
       ]
@@ -412,7 +543,8 @@
     }
    ],
    "source": [
-    "g = sns.catplot(data=xdf, x=\"Reviewer\", y=\"dice\", kind=\"box\")\n",
+    "g = sns.catplot(data=xdf, x=\"Reviewer\", y=\"dice\", kind=\"box\", palette=revewer_cmap)\n",
+    "g.set(title=\"Dice Coefficient by Label and Reviewer\")\n",
     "g.set_axis_labels(\"Reviewer\", \"DSC\")"
    ]
   },
@@ -425,22 +557,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f845d3b3a00>"
+       "<seaborn.axisgrid.FacetGrid at 0x7f39b03bee30>"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 1 Axes>"
       ]
@@ -450,7 +582,13 @@
     }
    ],
    "source": [
-    "g = sns.catplot(data=xdf, x=\"Reviewer\", y=\"mean_surface_distance_tol_7\", kind=\"box\")\n",
+    "g = sns.catplot(\n",
+    "    data=xdf,\n",
+    "    x=\"Reviewer\",\n",
+    "    y=\"mean_surface_distance_tol_7\",\n",
+    "    kind=\"box\",\n",
+    "    palette=revewer_cmap,\n",
+    ")\n",
     "g.set_axis_labels(\"Reviewer\", \"Normalized Surface Dice\\n(tolerance=7mm)\")"
    ]
   },
@@ -463,22 +601,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f845d041b10>"
+       "<seaborn.axisgrid.FacetGrid at 0x7f39b2adf160>"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 26,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 1 Axes>"
       ]
@@ -488,7 +626,9 @@
     }
    ],
    "source": [
-    "g = sns.catplot(data=xdf, x=\"Reviewer\", y=\"hausdorff_distance_95\", kind=\"box\")\n",
+    "g = sns.catplot(\n",
+    "    data=xdf, x=\"Reviewer\", y=\"hausdorff_distance_95\", kind=\"box\", palette=revewer_cmap\n",
+    ")\n",
     "g.set_axis_labels(\"Reviewer\", \"95% Hausdorff Distance (mm)\")"
    ]
   },
@@ -501,22 +641,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        Radiologist: Kendall-τ: 0.97, p-value: 0.01\n",
+      "        Non-expert: Kendall-τ: 0.91, p-value: 0.01\n",
+      "        \n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
        "[Text(0.5, 19.049999999999997, 'Likert Score'), Text(37.0, 0.5, 'DSC')]"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 27,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -526,16 +675,39 @@
     }
    ],
    "source": [
+    "x = rad_df[[\"LikertScore\", \"dice\"]].dropna()\n",
+    "rad_tau, rad_p_value = stats.kendalltau(x.LikertScore.values, x.dice.values)\n",
+    "x = ne_df[[\"LikertScore\", \"dice\"]].dropna()\n",
+    "ne_tau, ne_p_value = stats.kendalltau(x.LikertScore.values, x.dice.values)\n",
+    "\n",
+    "print(\n",
+    "    f\"\"\"\\\n",
+    "        Radiologist: Kendall-\\u03C4: {rad_tau:.2f}, p-value: {rad_p_value:.2f}\n",
+    "        Non-expert: Kendall-\\u03C4: {ne_tau:.2f}, p-value: {ne_p_value:.2f}\n",
+    "        \"\"\"\n",
+    ")\n",
+    "\n",
     "# plot likert score vs dice\n",
-    "g = sns.swarmplot(data=xdf, x=\"LikertScore\", y=\"dice\", hue=\"Reviewer\")\n",
+    "g = sns.swarmplot(\n",
+    "    data=xdf, x=\"LikertScore\", y=\"dice\", hue=\"Reviewer\", palette=revewer_cmap\n",
+    ")\n",
     "g.set(xlabel=\"Likert Score\", ylabel=\"DSC\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        Radiologist: Kendall-τ: 0.97, p-value: 0.01\n",
+      "        Non-expert: Kendall-τ: 0.91, p-value: 0.01\n",
+      "        \n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -543,13 +715,13 @@
        " Text(37.0, 0.5, 'Normalized Surface Dice\\n(tolerance=7mm)')]"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 29,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -559,18 +731,47 @@
     }
    ],
    "source": [
-    "# plot likert score vs dice\n",
+    "x = rad_df[[\"LikertScore\", \"mean_surface_distance_tol_7\"]].dropna()\n",
+    "rad_tau, rad_p_value = stats.kendalltau(\n",
+    "    x.LikertScore.values, x.mean_surface_distance_tol_7.values\n",
+    ")\n",
+    "x = ne_df[[\"LikertScore\", \"mean_surface_distance_tol_7\"]].dropna()\n",
+    "ne_tau, ne_p_value = stats.kendalltau(\n",
+    "    x.LikertScore.values, x.mean_surface_distance_tol_7.values\n",
+    ")\n",
+    "\n",
+    "print(\n",
+    "    f\"\"\"\\\n",
+    "        Radiologist: Kendall-\\u03C4: {rad_tau:.2f}, p-value: {rad_p_value:.2f}\n",
+    "        Non-expert: Kendall-\\u03C4: {ne_tau:.2f}, p-value: {ne_p_value:.2f}\n",
+    "        \"\"\"\n",
+    ")\n",
+    "\n",
+    "# plot likert score vs nsd\n",
     "g = sns.swarmplot(\n",
-    "    data=xdf, x=\"LikertScore\", y=\"mean_surface_distance_tol_7\", hue=\"Reviewer\"\n",
+    "    data=xdf,\n",
+    "    x=\"LikertScore\",\n",
+    "    y=\"mean_surface_distance_tol_7\",\n",
+    "    hue=\"Reviewer\",\n",
+    "    palette=revewer_cmap,\n",
     ")\n",
-    "g.set(xlabel=\"Likert Score\", ylabel=\"Normalized Surface Dice\\n(tolerance=7mm)\")\n"
+    "g.set(xlabel=\"Likert Score\", ylabel=\"Normalized Surface Dice\\n(tolerance=7mm)\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "        Radiologist: Kendall-τ: -0.81, p-value: 0.03\n",
+      "        Non-expert: Kendall-τ: -0.80, p-value: 0.03\n",
+      "        \n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -578,13 +779,13 @@
        " Text(32.375, 0.5, '95% Hausdorff Distance (mm)')]"
       ]
      },
-     "execution_count": 22,
+     "execution_count": 30,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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pKYm6detSt25d2rRpw+bNm5k2bRqBgYEAGI1GFi9eTHh4OPXr16du3bqMHj2ajIwMzp07B8ChQ4cwGo106NDB1K6jo6OpM+F29u/fD8BDDz1ktr9z5878+eefJCUl5Xrdvn37CA0NNQUigOrVq1OrVi1Tm9nDYX8PVg4ODrRp0+aONdWpU4fY2FjGjh3Lzz//THJy8h3PLyiFKhTdzcmTJ4FbvT5/V716ddLT000fnJMnTxIQEIDBYDA7LzAw0NSGiIgUb38eSzAbMsvNtRtp/HksId9rcXNz46uvvmLlypVMnz4dPz8/xowZY5rr+umnn/K///2Pdu3aMWfOHFauXMnEiROBW/OBAK5evYqzszPe3t5mbZcuXfqO946Li8PZ2dks3ACUKVMGo9FoGrL6p/j4eMqUKZNjf+nSpYmLizOrqWTJkmbn+PreufetefPmTJs2jWPHjjFw4EDCwsJ45ZVXiI2NveN1+a1QDZ/dTfZfgpeXl9n+7O3s4/Hx8Tn+ggC8vb1zHZK7F0aj8bapWkRE8i41NZWsrCwyMzNzTCK+F9djUyw+LzPTw+r73E1WVhYGg4E6deoAt5anV61alT59+hAREcHrr7/Oxo0badOmjWlqCNyaZ5t9fWZmJqVLlyY9PZ2YmBizYHTt2jUA0+8qKyvL7DovL69cr7t69SoGgwF3d3cyMzMxGo0YjUZTO97e3ly7di3H38G1a9eoVq2aWU2xsbFm37t3qwmga9eudO3alRs3brBt2zamTp2Ko6MjkydPNvvdWfIZyMzMJCsri+TkZNO9/s5oNOboKMlNkQpFhUF6ejpRUVH2LkNEpFhzcnIy9ZBYy8PNsmExDzcjKSmWBShrZM8l+vs9atSoQadOnVizZg0DBw4kOTkZBwcHs3O++eYbANLS0khJSaFmzZoAbNy40TR/JzMzk++++86s/eypJNnX1a1bF4D169fz+OOPm9rfuHEjQUFBpvtmB6PsdurXr8/q1au5cuWKqfPh9OnTHD16lIcffpiUlBTuu+8+ADZv3myaEJ2VlWVaFX67mv6uRIkSdOnShe3bt3P8+HHTcScnJ5KSkiz6u0lNTSUjI+OOo0EuLi53badIhaLshJuQkICfn59pf3x8vNlxLy8vLl26lOP6uLi4HN2O98rZ2blAZsCLiPxbpaamcuHCBVxdXXFzc7O6nQZ1XCntE8312PTbnlO6lDMN6pTG0eHuvQjWyl7x/M+fZfjw4WzZsoUVK1bQokULlixZwqpVq6hWrRrr1q3j/PnzwK0vczc3N+rUqUP79u157733MBqNVKhQgWXLlplCV3b72V/+2dfVr1+fDh06MGPGDLKyskzt//7770RERJiuc3R0xGAwmLYHDBjAunXrGD58OEOGDCEtLY0PP/yQ8uXL07NnT9zc3Khbty7t27dn+vTpZGRkUKFCBVauXElaWppZW/+sadasWcTFxdG0aVNKly7N0aNH2bVrF08//bTpmurVq/PDDz8QGhpKiRIlCAgIwMPj9j16Tk5OVKlSBVdX1xzHjh8/btnflUVnFRLZE9JOnjxp+nP2trOzM5UrVzadt2vXrhzdZadOnTIlbWtldzWKiEj+cHBwwMHBAUdHRxwdHa1ux9ERBveuluvqs2yDe1XDxTl/vwodHBwwGAw5fpYaNWoQHh7OsmXL+P7774mNjSUiIgKATp068dprrzFs2DDT7wJgypQpvPnmm7z33nu4uLjw2GOPERoayrRp00znZC9a+vt17777LjNmzGDhwoXExsYSGBjIzJkzzSZpGwwGszorVarEkiVLmDZtGmPGjMHBwYEWLVowduxYs2ks2TW9++67pppq1qzJ0qVLb1tTgwYN+PTTT9m0aROJiYmUK1eOgQMH8uyzz5qumThxIu+88w5Dhw4lJSWFzz77jNDQ0Fx/x46Ojjg4OFCiRIlcg7QlQ2cABmNuDwMqBLKX5P/z+QvZD2189913TfueeOIJPD09zZbk9+nTh08++YT7778fuBWIOnfuzIwZM6xekp89yz44ONiq60VE5O5SUlI4deoUAQEBeeopypbbc4rKlHJhUC/7PaeouHvqqadwcHBgyZIlBXK/u31mLP3+LlQ9RcnJyaYX5EVHR5OYmMimTZsAaNasGb6+vowYMYLRo0dTpUoVQkNDiYyM5ODBg3z++eemdho2bEjLli159dVXGTNmDK6urrz//vsEBQXd9XkOIiJSvDRv6EuzBqX481gCN+LTKOXlQp37SubrkNm/yebNm7l48SI1a9YkOTmZ9evXs2/fPmbPnm3v0u5ZoQpF169f57///a/Zvuzt7G6zrl27kpyczIIFC5g/fz4BAQFERETQsGFDs+s++OADpkyZwsSJE8nIyKBly5a89tprepq1iMi/kKODgeAgr7ufKPfM3d2dtWvXcvr0adLT0wkMDGT69Ol3fX5SYVRoh88KIw2fiYjkP1sPn0nxZ6vhsyL18EYRERGR/KJQJCIiIoJCkYiIiAigUCQiIiICKBSJiIiIAApFIiIiIkAen1MUExPDjRs3MBgMlCpVilKlStmqLhEREZECdU+hKCkpiU2bNrF161YOHDjAjRs3zI6XKlWKkJAQ2rdvz0MPPaR3hImIyL/erFmziIiIoEmTJixdutTs2Ntvv83WrVvZtm2bnaor3BYvXkxAQAAPPvhggdzPolB048YN5s+fz7Jly0hLSyMoKIh27dpRuXJlvLy8MBqNxMfHc/78ef744w8mTJjAW2+9RZ8+fRg8eDC+vnq3jIiI/Lvt27ePPXv23PalppLTZ599RuvWrQtXKGrbti1Vq1bllVdeoVOnTncNOTExMWzevJkVK1awfPlyfv31V5sUKyIiUhS5u7tTo0YN5syZo1BkgZSUFLs8zdyiidYzZ87k66+/5oknnrCo18fX15cnnniCNWvW8OGHH+a5SBERkbzIMhqJis9g1/V0ouIzyLLDG66ee+45du/efceOgujoaF544QUaN25MSEgIAwcO5K+//jI7p23btrz55pssXbqUNm3a0LhxY5577jliYmIsquP777+nZ8+e1K9fn7CwMF5//XWSkpIAyMjIoHv37vTq1YvMzEzTNfPnz6devXocOXIEuDUk2LBhQw4ePEiPHj0IDg6mc+fObN++/Z7uB7Bnzx6CgoL4/vvveeGFF2jUqBH//e9/adu2LdHR0SxdupSgoCCCgoJYvXq1RT+jtSwKRa1atbL6Bnm5VkREJK/23cjgxYNJTD2awkenUpl6NIUXDyax70ZGgdbRpk0b6tSpc9u3xycmJtKvXz/+/PNPJk2axPTp07lx4wZ9+/bl4sWLZudu27aNbdu2MXHiRMaPH8/evXt566237lrDpk2bePbZZ6lZsyYRERG8/PLLfPvtt4wfPx4AJycnpk+fzpEjR/joo48AOHLkCDNnzuSFF16gVq1aprbS09MZNWoUjz32GBEREVStWpXhw4ebhbi73e/vJkyYQOXKlZk9ezYDBgwgIiICPz8/OnXqxPLly1m+fDmtW7e+68+YF3plvIiIFFv7bmQw60RKjv030o3MOpHCiOpuNClVcF+Fzz77LCNGjODgwYPUr1/f7Njq1au5cOECGzZsoHr16gA0bdqUNm3a8OmnnzJ27FjTuUajkblz5+Li4gLc6mGaN28eWVlZODjk3t9hNBqZNm0a4eHhvP3226b9fn5+DBkyhOeee4777ruP6tWr8+KLL/Luu+/SvHlzXn/9derXr8+gQYPM2ktPT+fZZ5+lR48eALRs2ZKOHTsyb948ZsyYYfH9srVt25aXX37Z7B4uLi6UKVOGkJAQS3/FeWL1JyE6Opo1a9Zw/vx54uLiMP6jK9JgMDB37tw8FygiImKNLKORz8+m3vGcpWdTaeTjiIPBUCA1dejQgZo1azJ79mzmzZtndmzfvn2mUJLNx8eH+++/n/3795ud27RpU1MgAqhevTrp6elcv34dPz8/MjMzzb6XnZycOHXqFNHR0bz66qtkZPxfL1mzZs1wcHDg8OHDppDy9NNPs3XrVp5++mmcnJz45ptvcg1bHTp0MP3Z0dGR9u3b89133wHc0/2AfO8FsoRVoWj9+vWMHTuWjIwMvLy88PT0zHGOoYA+YJK/0rKMXEnNwsfZAU8n/Z2KSNHxV0ImN9LvPHcoJt3IXwmZ1PYqmN4ig8HAsGHDePHFF/njjz/MjsXHx1OmTJkc15QuXZpjx46Z7fPy8jLbzg5Iqam3QmCHDh2Ijo42Hd+6davpMTrPP/98rrX9fYjOYDDQpUsXfvnlF9q2bUvlypVznO/s7Iy3t3eOWq9evQpwT/fLvtberPoUzJgxg4CAAGbOnElAQICta5JCYsvlNL6+kMbNTHAyQIvSTvSr4oqzg8KRiBR+sXcJRPd6nq107tyZWbNmMWfOHCpUqGDa7+3tzalTp3Kcf/369Rzh427mzp1LWlqaabts2bKmwDRx4sQcQ3fZ52S7fPky77//PnXq1GHz5s3s2rWL5s2bm52fnp5OXFycWW3ZPVVwq5fL0vtB4ehMsSoU3bhxg4EDByoQFWP7bmSw9Nz//QuVYYQd1zJwdTDwVBVXO1YmImIZH2fLvmQtPc9WHBwcGDZsGGPHjqVZs2am/Y0bN2bz5s2cPHmSwMBAAOLi4ti5cye9e/e+p3sEBQXl2BcYGEi5cuU4d+4cTz311B2vHz9+PN7e3ixdupSXX36ZV199lXXr1uUYGfr2229Nc4oyMzP57rvvaNCgwT3f73acnZ1NYa4gWBWK6tevn6PbS4qXbVfSc93/w7V0elVyUW+RiBR6QSUdKeVsuOMQmq+zgaCSjgVY1S3dunVj9uzZ7Nmzh4oVKwLQvXt3Fi9ezNChQxk5ciSurq7MnTsXJycnnn766Tzf02AwMHbsWEaPHk1SUhKtW7emRIkSXLhwgR07djBq1CgCAgL48ssv2blzJ59//jnu7u68+eabdO3alcmTJzN16lRTe87OzsydO5fU1FQqVarEl19+yaVLl0yr6yy9350EBgaye/dufv75Z7y8vKhUqVK+vlLMqhfCvvrqq3zzzTds2rTJ1vVIIRGXkft/RFKyIDWrgIsREbGCg8FA37v0bD9VxbXAJln/naOjI0OGDDHb5+npyZIlS6hVqxYTJkxg9OjReHt78/nnn1O+fHmb3Ldz587Mnz+fU6dO8dJLL/Hcc8/xySefULFiRcqUKcPZs2eZNm0aAwcOpFGjRsCtuT5vvfUWa9asMU2ihluhaMaMGaxatYrnn3+e06dPM3PmTLNl+3e73928+OKLlCtXjhEjRtCjR49cn4NkSwbjP5eNWWjNmjWMHz+eEiVKUK5cuRyz0g0GA998841NiiwsDh06BEBwcLCdK8l/n51JZevVnL1FlUo48HZdvdNORPJPSkoKp06dIiAgwCZPNd53I4PPz6aa9Rj5Ot+aClCQy/GLk1mzZrFo0SIOHDhg71KAu39mLP3+turTsHTpUiZPnoyrqytVqlTJdfWZFG1dyjmzLzaDuL/9R8TRAL0qutzhKhGRwqdJKSca+TjyV0ImselGfP7/kJk9eoikcLMqFM2bN4+GDRsyb948SpYsaeuapBAo7erApNol+PZKOqduZlHG1UA7P2eqeRT82LuISF45GAwFtuxeii6rPiEJCQl069ZNgaiYK+XiQK9KWmkmIiLmRowYwYgRI+xdhs1ZNdG6WbNmHD161Na1iIiIiNiNVaHojTfeYO/evSxYsMD0xEoRERGRosyq4bPw8HCMRiMzZsxgxowZuLq65rr67J/vahEREbGUlYuj5V/IVp8Vq0JRp06dCsXjuEVEpPhxdnYGICkpiRIlSti5GikKkpKSgP/77FjLqlD09ydaioiI2JKjoyM+Pj5cuXIFAHd3d/2PuOTKaDSSlJTElStX8PHxwdExbyuktT5RREQKnXLlygGYgpHInfj4+Jg+M3mRp1C0d+9ezp07R3x8fI7xPIPBwDPPPJOX5kVE5F/KYDBQvnx5ypYtS3p67u9iFIFbQ2Z57SHKZlUoioqKYuTIkZw9e/a2k5sUikREJK8cHR1t9oUncjdWhaLx48cTExPDpEmTqF+/vh7iKCIiIkWeVaHo+PHjvPDCC/Tq1cvW9YiIiIjYhVUPb6xatapWAoiIiEixYlUoGjFiBEuXLuXy5cu2rkdERETELqwaPuvYsSOpqak89NBDhIWFUa5cuVwnwr322mt5LlBERESkIFgVin755RfeeOMNkpOT2b59e67nGAwGhSIREREpMqwKRW+99Raenp7MnDmTBg0a4Onpaeu6RERERAqUVXOKzp49y8CBA2nRooUCkYiIiBQLVoWiGjVqkJCQYOtaREREROzGqlA0ZswYli9fzsGDB21dj4iIiIhdWDWnaNGiRXh4eNC7d29q1KhB+fLlcXAwz1cGg4G5c+fapEgRERGR/GZVKDp69CgA5cuX5+bNmxw/fjzHOXq4o4iIiBQlVoWibdu22boOEREREbuyak6RiIiISHFjUSi6ePGi1TfIy7UiIiIiBcWiUNShQwfGjRt3T6vNfv31V1555RU6duxodXEiIiIiBcWiOUVffPEFH3zwAb169aJChQqEhYVRt25dKlWqhJeXF0ajkfj4eM6fP8/hw4fZvXs3ly9fJjQ0lKVLl+b3zyAiIiKSZwaj0Wi09OSoqChWrVrFtm3buHDhwq0G/v8qs+xmypcvT7t27Xj88cepXbt2PpQMW7du5aOPPuL48eN4eHjQuHFjRo8eTeXKlc3OW7lyJQsXLuTChQsEBAQwatQo2rRpY/V9Dx06BEBwcHCe6hcREZGCY+n39z2For+7fPkyJ0+eJDY2FgAfHx8CAwPx9/e3pjmL7dmzh2eeeYZHH32Ubt26ERsby4cffkhWVhbr1q3Dzc0NgA0bNvDSSy8xbNgwwsLCiIyMZNWqVSxdupSQkBCr7q1QJCIiUvRY+v1t1ZJ8AH9//3wPQLnZsGEDFSpU4J133jH1Uvn6+vL0009z+PBhmjRpAsDMmTPp0qULI0eOBCAsLIyjR48ye/ZsFixYUOB1i4iISOFW5JbkZ2Rk4OHhYfZwyJIlSwL/N4R37tw5Tp8+TefOnc2uDQ8PZ9euXaSlpRVcwSIiIlIkFLlQ1L17d06cOMHSpUtJSEjg3LlzzJgxgzp16tCoUSMATp48CUBAQIDZtdWrVyc9PZ1z584VeN0iIiJSuFk9fGYvTZo0ISIigpdeeok333wTgNq1a7Nw4UIcHR0BiIuLA8DLy8vs2uzt7OPWMBqNJCUlWX29iIiIFCyj0WjR68eKXCjKfv5Rr169aN26NbGxscyZM4chQ4bwxRdfmCZa55f09HSioqLy9R4iIiJiWy4uLnc9p8iFosmTJxMWFsbYsWNN+0JCQmjdujVr166ld+/eeHt7A5CQkICfn5/pvPj4eADTcWs4OztTo0YNq68XERGRgpXbi+tzY5NQlJCQgLu7u2n4Kj+dOHGCdu3ame0rV64cpUqV4uzZswAEBgYCt+YWZf85e9vZ2TnH84zuhcFgwN3d3errRUREpGBZMnQGeZhofejQIQYOHEiDBg0IDQ3ll19+ASAmJoZnn32WPXv2WNv0HVWoUIE///zTbF90dDQ3btygYsWKAFSuXJlq1aqxadMms/MiIyNp3ry5RV1oIiIi8u9iVSj69ddfefLJJzlz5gwPP/wwWVlZpmO+vr4kJiayfPlymxX5d3369OG7775j8uTJ7Ny5k8jISIYNG0bp0qXNluCPGDGC9evXM3PmTPbs2cPrr7/OwYMHee655/KlLhERESnarBo+e//996levTorVqwgMTGRlStXmh0PDQ1lzZo1Ninwn/r374+Liwtffvklq1atwsPDg5CQED744ANKlSplOq9r164kJyezYMEC5s+fT0BAABERETRs2DBf6hIREZGizapQdOjQIV588UVcXFxyHafz9/fn2rVreS4uNwaDgSeeeIInnnjiruf27NmTnj175ksdIiIiUrxYNXzm5ORkNmT2T5cvX9ZkZBERESlSrApFDRo0YPPmzbkeS0pKYvXq1TRt2jRPhYmIiIgUJKtC0QsvvMDhw4cZMmQIP/zwAwB//fUXK1eupHv37sTExGhCs4iIiBQpBmP2W1Tv0a5du3jjjTc4c+aM2f4qVaowefJkmjVrZpMCC5NDhw4BEBwcbOdKRERExFKWfn9b/fDG5s2bs3nzZqKiojh9+jRGo5HKlStTr149ix+SJCIiIlJY5PmJ1rVr16Z27dq2qEVERETEbqyaU7R+/Xqzd4/907hx44iMjLS6KBEREZGCZlUoWrx48R1fleHq6sqnn35qdVEiIiIiBc2qUHTq1Kk7DpnVqlWLkydPWl2UiIiISEGzKhQZjUYSEhJuezw+Pp6MjAyrixIREREpaFaFojp16rB+/XrS0tJyHEtLS2PdunWafC0iIiJFilWhaPDgwRw7doz+/fuzbds2zp07x7lz59i6dSv9+vXj+PHjDBkyxNa1ioiIiOQbqx/euHr1at5++22SkpJM+4xGIx4eHowbN44ePXrYrMjCQg9vFBERKXry/eGN3bt3p2PHjvz888+cPXsWuPU06xYtWuDp6WltsyIiIiJ2kaeHN3p6etKpUydb1SIiIiJiN3kKRYmJiVy4cIH4+HhyG4Vr2rRpXpoXERERKTBWhaIbN27w1ltvsWXLFjIzM4Fb84my33mW/eeoqCjbVSoiIiKSj6wKRRMmTGD79u3069ePJk2a4OXlZeu6RERERAqUVaHo559/5umnn+aVV16xdT0iIiIidmHVc4rc3NyoWLGirWsRERERsRurQtHDDz/Md999Z+taREREROzGquGzTp06sXfvXgYOHEjv3r0pV64cjo6OOc6rW7dungsUERERKQhWhaInn3zS9OedO3fmOK7VZyIiIlLUWBWKpkyZYus6REREROzKqlD02GOP2boOEREREbuyaqK1iIiISHFj9Ws+UlNT2bx5M3/++ScJCQlkZWWZHTcYDLzzzjt5LlBERESkIFgViqKjo+nfvz/R0dF4eXmRkJCAt7c3CQkJZGZmUqpUKdzd3W1dq4iIiEi+sWr4bNq0aSQmJrJixQo2bdqE0Wjk/fff58CBA4wePRo3Nzc+/vhjW9cqIiIikm+sCkW7d+/miSeeoH79+jg4/F8TLi4uDBo0iLCwMA2diYiISJFiVShKSUkxvebD09MTg8FAQkKC6XjDhg3Zv3+/bSoUERERKQBWhaLy5ctz+fJlAJycnPD39+e3334zHT9+/Diurq42KVBERESkIFg10TosLIytW7cyfPhw4NZzi+bPn098fDxZWVl88803PPLIIzYtVERERCQ/WRWKhgwZwqFDh0hLS8PFxYVhw4Zx5coVNm/ejIODA127dmXs2LG2rlVEREQk3xiMRqPR3kUUFYcOHQIgODjYzpWIiIiIpSz9/rZqTtG4ceP4/fffb3v84MGDjBs3zpqmRUREROzCqlC0Zs0azp49e9vj58+f5+uvv7a2JhEREZECly/vPrty5Qpubm750bSIiIhIvrB4ovV3333H1q1bTdsrVqxg586dOc5LSEhg586d1KtXzzYVioiIiBQAi0PRiRMn2LRpE3DrZa+///47hw8fNjvHYDDg7u5O06ZNtfpMREREihSrVp/VqlWL6dOn061bt/yoqdD6t60+S03L4sd91zl2OpGypV1p19wPHy9ne5clIiJyTyz9/rbqOUVHjhyx5jIpQhJvZvDqjD85E51s2rdq8wXe/G9talT1sGNlIiIi+cOqidaJiYlcvHjRbN/ly5f58MMPmT59OgcPHrRJcWI/a769aBaIAG4mZbJwxWn7FCQiIpLPrOopmjhxIufPn2fFihXArZDUu3dvLl26hIODA5999hkLFy4kNDTUpsVKwdl3KDbX/VEnEkm8mYGnh1UfHRERkULLqp6i/fv307p1a9P22rVruXLlCsuWLeOXX34hKCiIuXPn2qpGsQM319w/Gk6OBpydDQVcjYiISP6zKhTduHEDf39/0/a2bdto3LgxISEheHp68uijj2reURHXtrlfrvvvb+SLq4tjAVcjIiKS/6wKRV5eXly7dg2AlJQU9u/fT4sWLUzHHR0dSUlJsU2FYhcdW/oR/qA/Dn/7hNS7ryRD+lSzW00iIiL5yaqJIQ0bNuSLL74gMDCQH3/8kdTUVNq1a2c6fvr0abOeJCl6DAYDQ5+oRvdO5Tl+5ib+pV0JrKJVZyIiUnxZ1VM0evRonJycGDFiBCtWrOCZZ57hvvvuAyAzM5NNmzbRtGlTmxb6T2vWrOHRRx8lODiY0NBQBg0aZNY7tW3bNh5++GGCg4Pp1KkTq1atytd6iis/X1eaN/RVIBIRkWLPqp6iqlWrsmnTJk6cOIGnpyeVKlUyHUtOTmbChAnUqlXLZkX+09y5c1mwYAHDhg0jJCSEGzdusGvXLjIzMwHYt28fw4cPp0ePHrz66qvs3r2b8ePH4+HhwUMPPZRvdYmIiEjRZdUTre3p5MmTdOvWjTlz5vDggw/mes7AgQO5efMmy5YtM+176aWXiIqKIjIy0up7/9ueaC0iIlIc2PSJ1nv37gUwDYllb99NfgyhrV69mkqVKt02EKWlpbFnzx5Gjx5ttj88PJz169dz/vx5s54tEREREbAwFPXr18/0ElgXFxfT9u0YjUYMBgNRUVE2KzTb77//Ts2aNZkzZw5LliwhISGBevXqMW7cOBo0aMDZs2dJT08nMDDQ7Lrq1asDt3qaFIpERETknywKRZ999hkALi4uZtv2cPXqVQ4fPszRo0d5/fXXKVGiBB999BEDBgxgy5YtxMXFAbceG/B32dvZx61lNBpJSkrKUxsiIiJScLI7a+7GolDUrFmzO24XpOxQ8uGHH5omczdo0IC2bdvy+eef07Jly3y9f3p6er70gImIiEj+ye7YuZM8vcDq5s2b3Lx5Ew8PDzw8CmbJtpeXFz4+Pmar23x8fKhTpw7Hjx+nS5cuACQkJJhdFx8fD4C3t3ee7u/s7EyNGjXy1IaIiIgUnOPHj1t03j2Hor/++ouFCxeyc+dOYmJiTPtLly5Ny5YtGTBgADVr1rzXZi1Wo0YNzp49m+ux1NRUqlSpgrOzMydPnqRVq1amYydPngTIMdfoXhkMBtzd3fPUhoiIiBQcS4bO4B4f3hgZGUnPnj1Zt24dHh4etG3blq5du9K2bVvc3d35+uuv6dGjB5s3b7aqaEu0adOG2NhYsyGsGzdu8Mcff1C3bl1cXFwIDQ3NUUNkZCTVq1fXJGsRERHJlcXPKbp48SLh4eH4+/szdepUQkJCcpxz4MABxo4dy5UrV9i4cSPlypWzdb1kZWXRq1cv4uLiGDVqFK6ursyfP5/Tp0+zfv16/Pz82LdvH/3796dXr1507tyZPXv2MGfOHN5//306d+5s9b31nCIREZGix9Lvb4t7irIfhPjJJ5/kGojg1jvRFi1ahNFoNHtwoi05ODgwf/58QkJCmDhxIi+++CKenp4sXboUP79bb3Zv0qQJs2bNYv/+/QwcOJD169czefLkPAUiERERKd4snlO0Z88eOnToQPny5e94XsWKFenYsSO7d+/Oc3G34+vry/Tp0+94Trt27cxeUisiIiJyJxb3FJ0+fdriYaPg4GBOnz5tbU0iIiIiBc7iUJSYmJjjgYi3U7JkSRITE60uSkRERKSgWRyKMjIycHCw7HQHBwfTG+tFREREioJ7ek7Rjh07uHbt2l3PO3z4sNUFiYiIiNjDPYWi9evXs379eovOtfRBSSIiIiKFgcWhaOvWrflZh4iIiIhdWRyKKlasmJ91iIiIiNjVPb3mQ0RERKS4UigSERERQaFIREREBFAoEhEREQEsDEVbt27l8uXL+V2LiIiIiN1YFIqGDx/OL7/8Ytpu166dluiLiIhIsWJRKPLw8CA+Pt60HR0dTVJSUr4VJSIiIlLQLHpOUf369fnoo4+4fv06JUuWBO7+yg+DwcAzzzxjkyJFRERE8pvBaDQa73bSmTNnGDNmDL/99tutiwwG7naZwWAgKirKJkUWFocOHQIgODjYzpWIiIiIpSz9/raop6hq1aosW7aM1NRUrl+/Ttu2bXn11Vdp165d3isVERERKQQsCkWfffYZrVq1IiAggAoVKjB8+HDCwsL06g8REREpNiyaaD1lyhQOHz5s2p49ezZ//fVXvhUlIiIiUtAsCkVeXl5cv37dtG3BNCQRERGRIsWi4bPQ0FBmzZpFVFSUafXZ119/ze+//37H61577bW8VygiIiJSACxafXb9+nXeeecd9uzZY+ox0uozERERKQpsuvqsdOnSvPfee6btWrVqMX36dLp165aHEkVEREQKj3t+IWx6ejrjxo2jfPny+VGPiIiIiF3ccyhycHBg2rRp/Pnnn/lRj4iIiIhd3HMocnR0pEKFCqSlpeVHPSIiIiJ2cc+hCKBv376sWLGC2NhYG5cjIiIiYh8WTbT+p6ysLFxcXOjQoQOdOnWiYsWKuLm5mZ2jF8KKiIhIUWLRkvx/qlWr1t0b1pJ8ERERKQRsuiT/n7Zu3WrNZSIiIiKFllWhSC+CFRERkeLGqlCULSkpib179xIdHQ3cCktNmzbF3d3dJsWJiIiIFBSrQ9GSJUv44IMPSEpKMnvlh4eHB6NGjaJv3742KVBERESkIFgVir7++mvefvttQkJC6N+/P4GBgQCcPHmSJUuW8Pbbb+Pp6cmjjz5qy1pFRERE8o1Vq88eeeQRvLy8WLx4MY6OjmbHMjMzeeaZZ4iPj2ft2rU2K7Qw0OozERGRosfS72+rHt546tQpHnrooRyBCG498fqhhx7i1KlT1jQtIiIiYhdWhaKSJUty/vz52x4/f/48np6eVhclIiIiUtCsCkUPPvggn3/+ORs2bMhxLDIykqVLl9KmTZs8FyciIiJSUKyaUxQTE0Pfvn05deoUZcqUoVq1agCcPn2aa9euERgYyJIlS/D19bV1vXalOUUiIiJFT74+0drX15c1a9awbNkyfvjhBy5cuABAzZo1GTx4ML1798bV1dWapkVERETswqqeon8r9RSJiIgUPfm6+kxERESkuLFo+Kx///733LDBYODTTz+95+tERERE7MGiUJTbCNulS5c4d+4cJUuWpHLlysCtpfjx8fFUqVKFcuXK2bZSERERkXxkUShasmSJ2fa+fft47rnneOutt3jsscdwcrrVTEZGBqtXr+bdd99lypQptq9WREREJJ9YNado2rRpdO/enZ49e5oCEYCTkxO9evWie/fuTJ061WZFioiIiOQ3q0LRX3/9ZRoyy02lSpU4evSo1UWJiIiIFDSrQlHZsmWJjIwkIyMjx7GMjAwiIyMpW7ZsnosTERERKShWhaJBgwaxf/9+evXqxcqVK9mzZw979uxhxYoV9OrViwMHDjBw4EBb15qrmzdv8sADDxAUFGR6DkG2lStX0qlTJ4KDg3n44YfZvn17gdQkIiIiRY9VT7Tu3bs3Dg4OfPDBB0yYMAGDwQDcWqXm6+vLpEmT6NWrl00LvZ05c+aQmZmZY/+GDRuYMGECw4YNIywsjMjISIYPH87SpUsJCQkpkNpERESk6MjTE60zMjI4fPiw6TUfFSpUoF69emaTr/PTiRMn6NGjB2PGjOH111/nq6++Mj2tslOnTtSrV4/33nvPdH6fPn0oWbIkCxYssOp+eqK1iIhI0ZOv7z4zXezkREhIiN16XiZPnkyfPn0ICAgw23/u3DlOnz7Nyy+/bLY/PDycadOmkZaWhouLS0GWKiIiIoWcVXOKoqKiWL9+vdm+H3/8kaeeeoqePXsWyJOsN23axNGjR3n++edzHDt58iRAjrBUvXp10tPTOXfuXL7XVxycv5TMzM9OMuLNg7wZ8Re//Rln75JERETyjVU9RdOnT8fNzY2uXbsCt3pmhg8fjo+PD2XLlmXq1Km4ubnRu3dvmxabLTk5malTpzJq1Cg8PT1zHI+Lu/Xl7eXlZbY/ezv7uDWMRiNJSUlWX19UXLiSyoQPjpOUkgXA2QvJ/PpHLM8/VZkWjXzsW5yIiMg9MBqNpvnPd2JVKDpy5IjZ6rK1a9fi4ODAmjVr8PX1ZeTIkSxbtizfQtHcuXMpXbo0jz/+eL60fyfp6elERUUV+H0L2jc7MklKMZ9uZjTC0m/OUcrtgkUfLhERkcLCkmkzVoWihIQEfHx8TNs7duygRYsW+Pr6AtCiRQt++OEHa5q+q+joaBYtWsTs2bNJSEgAMPXcJCUlcfPmTby9vU11+vn5ma6Nj48HMB23hrOzMzVq1LD6+qJi0bqjQGqO/TfioVKVmnh5FsxkehERkbw6fvy4RedZ9c3m5+fHiRMnALhy5Qp//PEH3bt3Nx2/efMmDg5WTVe6q/Pnz5Oens6QIUNyHOvfvz8NGjQwrTg7efIkgYGBpuMnT57E2dn5jk/jvhuDwYC7u7vV1xcV5fxKcP5SzlDk6e5ImdKeODnmz9+viIiIrVk6umFVKGrXrh2ff/45aWlp/P7777i4uNChQwfT8bu9BiQvateuzWeffWa2LyoqiilTpjBp0iSCg4OpXLky1apVY9OmTbRv3950XmRkJM2bN9fKMwt0a1OO/Ydj+ecDG8Jb+ysQiYhIsWRVKBo5ciQxMTGsXbuWkiVLMmXKFMqUKQNAYmIimzZt4qmnnrJpodm8vLwIDQ3N9VjdunWpW7cuACNGjGD06NFUqVKF0NBQIiMjOXjwIJ9//nm+1FXchNTx5sUBNVj6zTkuXU3F092R8Nb+9Olayd6liYiI5AurQpGHh4fZQxH/zt3dnR9++AE3N7c8FZZXXbt2JTk5mQULFjB//nwCAgKIiIigYcOGdq2rKHmgaWlaNfEl4WYG7iUc1UMkIiLFWp6eaP1voydai4iIFD35+kTriIiIu55jMBhyfbCiiIiISGFk81BkMBhMD0lSKBIREZGiwuqHN/5TVlYW0dHRfPHFF+zdu9fql66KiIiI2IPNZs46ODhQuXJlxowZQ9WqVZk8ebKtmhYRERHJd/mynKhp06bs2LEjP5oWERERyRf5EooOHz6cb0+0FhEREckPVs0p+vrrr3PdHx8fz759+9iyZQs9e/bMS10iIiIiBcqqUDR27NjbHitVqhRDhgzRyjMREREpUqwKRVu3bs2xz2Aw4OXlhaenZ56LEhERESloVoWiihUr2roOEREREbvSbGgRERERrOwpAtixYweLFy/mzz//JCEhgdxeoRYVFZWn4kREREQKilU9RZs3b2bYsGFcu3aN8PBwsrKy6NKlC+Hh4bi5uREUFKSJ1iIiIlKkWNVTNG/ePOrXr88XX3xBXFwcX375JY8//jjNmzfn/Pnz9O7dm0qVKtm6VhEREZF8Y1VP0YkTJwgPD8fR0REnp1u5KiMjA4BKlSrxxBNP6N1nIiIiUqRYFYrc3NxwdnYGwMvLCxcXF65evWo6XqZMGc6fP2+bCkVEREQKgFWhKCAggBMnTpi2a9euzdq1a8nIyCA1NZX169dTvnx5mxUpIiIikt+sCkUdOnRg69atpKWlATBs2DB++eUXmjZtSlhYGPv27WPIkCE2LVREREQkPxmMua2lt0L2O88cHR158MEHCQsLs0WzhcqhQ4cACA4OtnMlBedyShankzIp4+JAdU9He5cjIiJyzyz9/rb6OUX/1KRJE5o0aWKr5sTOsoxGFp9J5YdrGWSn5hoeDvy3Rgm8nA12rU1ERCQ/6InWkqvvr2aw42+BCOD4zSw+P5tqt5pERETyk8U9RcOGDbunhg0GA3Pnzr3ngqRw+Pl6eq7798VmkJppxNVRvUUiIlK8WByKjh49arZtNBq5dOkSpUuXxsXFJcf5BoO+NIuytKzc92caIcMIrgVbjoiISL6zOBRt27bNbDsmJob777+f6dOn07x5c5sXJvYV4uPI2eScyaimpwMeTgq8IiJS/Fg9p0g9QcVbZ38Xqrqbfzw8naBvFfURiYhI8WSz1WdSvLg7GZhYqwS/3Mjg5M0syrgYaFnGGU/1EomISDGlUCS35eRg4P7Sztxf2t6ViIiI5D8tyRcRERHhHnqKYmNjzbbj4uIAuHnzZo5j2Xx8fKytS0RERKRAWRyKwsLCcp1cPWLEiNteExUVZV1VIiIiIgXM4lD0/PPPa8WZiIiIFFsWh6I79QiJiIiIFHWaaC0iIiKCQpGIiIgIoFAkIiIiAigUiYiIiAAKRSIiIiKAQpGIiIgIYKN3n/3yyy+sW7eOy5cvU6ZMGcLDw2nZsqUtmhYREREpEHnuKVq2bBlDhw4lPT2dWrVqERcXx9ChQ1m0aJEt6hMREREpEBb3FCUmJuLp6Zlj/6effsp7771H27ZtTftmzJjB4sWLGTBggG2qFBEREclnFvcUdezYkZUrV1p0rsFg0CtBREREpEixuKfojTfeYNq0aXz55ZeMHz+exo0bA9CvXz9eeuklHnroIcqWLcupU6f47rvvGDVqVL4VLSIiImJrBqPRaLT05LS0NBYuXMiCBQto3bo1Y8aMoVy5cuzcuZMNGzZw5coVypQpQ6dOnWjdunU+lm0fhw4dAiA4ONjOlYiIiIilLP3+vqdQlO3y5ctMmzaNbdu2MWDAAAYPHoybm5t1lRYhCkUiIiJFj6Xf31atPvP39+e9997j448/5vvvv+ehhx5i/fr11jQlIiIiUijc03OKLly4wE8//URycjINGjSgUaNGfPXVV3z11VdMnTqVzz//nNdee4169erlV70iIiIi+cLinqLt27fTuXNn5s+fz9q1a3nyySf53//+h8FgoGfPnmzatImGDRvy5JNPMm7cOK5fv56fdYuIiIjYlMWh6N1336VTp0589913rF69mqlTp7J48WIuX74MgKenJ2PGjGHt2rVcv36djh075kvBGzdu5Nlnn+WBBx4gJCSERx55hK+++op/To1auXIlnTp1Ijg4mIcffpjt27fnSz0iIiJSPFgcii5dukSjRo1M240aNcJoNJpCUbaAgADmz5/PjBkzbFfl3yxevJgSJUowduxY5s6dywMPPMCECROYPXu26ZwNGzYwYcIEOnfuzIIFCwgJCWH48OH89ttv+VKTiIiIFH0Wrz4bMmQI0dHRvPnmm3h5efHRRx/x008/8f3331OiRIn8rtMkJiYGX19fs30TJkwgMjKSvXv34uDgQKdOnahXrx7vvfee6Zw+ffpQsmRJFixYYPW9tfpMRESk6LH56rO33noLPz8/+vbtS7du3Th06BAffvhhgQYiIEcgAqhduzaJiYkkJSVx7tw5Tp8+TefOnc3OCQ8PZ9euXaSlpRVUqSIiIlKEWLz6zN/fn8WLF5OamkpqaipeXl75Wdc92b9/P/7+/nh6erJ//37g1jDe31WvXp309HTOnTtH9erV7VGmiIiIFGL3tCQfwNXVFVdX1/yoxSr79u0jMjKSMWPGABAXFweQI7Rlb2cft5bRaCQpKSlPbYiIiEjBMRqNFr2T9Z5D0T8dPHiQnTt3EhcXR6lSpWjVqhW1a9fOa7MWuXTpEqNGjSI0NJT+/fsXyD3T09OJiooqkHuJiIiIbbi4uNz1HItD0eDBgxk0aBChoaEAZGRk8Morr7Bx40az5fDvv/8+vXv35o033rj3iu9BfHw8gwcPxsfHh1mzZuHgcGt6lLe3NwAJCQn4+fmZnf/349ZydnamRo0aeWpDRERECs7x48ctOs/iUPTjjz/y8MMPm7Znz55NZGQkvXr14j//+Q/ly5fn7NmzzJ07l+XLl1O3bl169ux575VbICUlhaFDh5KQkMDy5cspWbKk6VhgYCAAJ0+eNP05e9vZ2ZnKlSvn6d4GgwF3d/c8tSEiIiIFx5KhM7Dy3Wdw6+GI7dq148033yQgIAA3Nzdq1qzJ+++/T0hICMuXL7e26TvKyMhg5MiRnDx5koULF+Lv7292vHLlylSrVo1NmzaZ7Y+MjKR58+YWdZ+JiIjIv49Vc4qSkpK4du0anTp1yvV4x44dmTlzZp4Ku51Jkyaxfft2xo4dS2JiotkDGevUqYOLiwsjRoxg9OjRVKlShdDQUCIjIzl48CCff/55vtQkIiIiRd89haLs7idXV1ecnZ1vO4zk6uqa47UbtvLzzz8DMHXq1BzHtm7dSqVKlejatSvJycksWLCA+fPnExAQQEREBA0bNsyXmkRERKTou6dQ9N577zFv3jzT9l9//UX79u1znHf27FnKlCmT9+pysW3bNovO69mzZ77NaRIREZHix+JQ1LRpU7PtkJAQLl68mOO8tLQ01q9fn+N8ERERkcLM4lC0ZMkSi85LS0tjxowZVKhQweqiRERERApanh/e+E+enp40a9bM1s2KiIiI5CurQlFycjLHjh3j8uXLpKSk4O7uTrVq1fROMRERESmy7ikUnT59mhkzZvD999+Tnp6e43i5cuV4+umn6d+/v+kJ0yIiIiJFgcWh6MiRI/Tr14/MzEzuv/9+3NzcOHjwIFevXmXQoEFkZWXx888/M3XqVHbt2sXs2bNxcrL56JyIiIhIvrA4tUyfPh1vb2++/PJL0zvF0tPTeeWVV/jpp59YuXIlo0aNIjIykpdffpnFixczaNCgfCtcRERExJYsHuM6cOAATz75pNlLVp2dnXn22Wc5fPgwx44dAyA8PJzHHnuMNWvW2L5aERERkXxicSgyGAy5zhNydHTEaDSSkJBg2hcSEsL58+dtU6GIiIhIAbA4FIWEhLBs2TLi4+NN+4xGIwsXLsTZ2Zn77rvPtD82NhYPDw/bVioiIiKSjyyeUzRq1CieeuopOnToYJpo/dtvv3H69GmGDh1KyZIlTef+/PPP1KlTJ18KFhEREckPFoeievXq8cUXX/Dhhx/yww8/kJaWRkBAAK+//jp9+vQxO/f555/H39/f5sWKiIiI5BeDMb9eZ18MHTp0CIDg4GA7VyIiIiKWsvT7W09YFBEREUGhSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBinkoOnHiBP/5z38ICQmhRYsWTJs2jbS0NHuXJSIiIoWQk70LyC9xcXE8/fTTVKtWjVmzZnH58mWmTp1KSkoKEydOtHd5IiIit5VlNOJgMNz2uNFoxHCb41lZRhwc7v3Yndq86z3vUm9RUWxD0bJly7h58yYRERH4+PgAkJmZyaRJkxg6dCj+/v72LVCkENr9WwxfbbzA2YvJVClfgh6dKxAW4mvvsiSf7L+RwbqLaUSnZFHRzYFu5V1oXKrYfi0UCScSM1kZncaRhEw8naCNnzOPlHfBycFAYoaRZedS2XMjgywjNC7lRJ9KLvi6OGA0Glm95SLrt10iJi6doABP+j5Sifq1vAH49Y9Yln5znuNnbuLn68LD7crxcLvyAFy+lsonq86w92AsTk4GHmxWhqe7V8ajhBPp6Vl8se483/58lZtJGdSv5cXT3asQWNkDgJ+vp7PuYhoXU4yUdzPQrbwLLUo72+33l1cGo9FotHcR+eGpp57C29ubOXPmmPbFx8fTrFkz3nnnHbp3737PbR46dAiA4OBgm9UpUljs/i2GKR8dM9tnMMDYofcpGBVD+29kMPNEitk+AzCiupuCkZ1cTsli4p9JpGSZ72/j58TTVVyZFJXMqSTzg/6uBt6p687y9dGsiIw2O+bkZOB/L9clPT2LV2f8SdY/2u3/WGW6tPZn+KSDXI0xn1pS976SvPNSHd7/5ATf77lmdszD3ZEPXwvmJA7MOZma4+d4LtCVUN/CFYws/f4utp/8kydP8vjjj5vt8/Lyws/Pj5MnT1rdrtFoJCkpKa/liRQ6Kzacz7HPaIQVkeepX9PNDhVJflobnZVjnxH4JjqF2q7FerppobX5UlaOQATw47UMarhkcCqXr57LqUZ2XLjJ+m0XcxzLyDCyZst5UtOycgQigK+/vYizY2aOQATwx7EEduy5yI5fruU4djMpkw3bozkeVDbXn2PdhVSC3dJzPWYvdxsazFZsQ1F8fDxeXl459nt7exMXF2d1u+np6URFReWlNJFC6ezFjNz3X0jWZ74YijbeR25rbaJTsoiK+qvgCxJOGCsCnjn2Zxhhf/R1oHSu1/1+5ipJuaUp4OTZWNJz/1eb+MQMDv6ZM0xl2/PrOW43lvTXiWtcrVqG3D5DlwrpZ8jFxeWu5xTbUJRfnJ2dqVGjhr3LELG5KuWPc+Jccs79FUpQu7Y+88VNxZNZnEnJZb+bA7UDaxd8QcLRK1mcztkxg4sBWlQuza9nc7+uaYAfBzyvE5+YmeNYUGAp0tKzuHojZ2dAaR9nmob4s/fPnL3EAK3vr8ruw2fIzMyZjOoFleV4CQdO5vxPBpVLOFA7oHB9ho4fP27RecU2FHl5eZGQkJBjf1xcHN7e3la3azAYcHd3z0tpIoVSry6VmDrvmNn/GRoM0Du8kj7zxdAjFTOYdSKFv3/dGYBHKrrh7l5svxoKtU4Vsvg5NpmEDPMQ0snfmSZlXal7I5k/EsyDTzV3B1qUL8GNzhX5eKV5anJzdaBH58qkZ2Sx91ACaenmvUm9u1SibVgZ1n9/nbMXzNNNaINSNGvgT/iDKazbdsnsmK+3M13bVuRMloEZx3J+hh6rVPg+Q5YMnUExDkWBgYE55g4lJCRw9epVAgMD7VSVSOEVFuLL2KH38dWmC5y7mEzl8iXo+VAFQjXJulhqXMqJEdXdWH8pjejkLCqWcKBbORcaaZK13fi6OPBarRJ8fSGNqIRMvJwMtPZzpq3frb+T/9ZwY92lNPbE/N/qs0fKu+BgMPBwu/KU9HBiw/bLXItNo1agJ727VKRSuRIAvDO6Nis2RHPs9E3KlnalW7tytGpyazju7Rdrs2xDNHt+u4GLswMPNC1Nj4cqADCgRxX8S7vy7c9XSLiZQUgdb/p0qYh3SWfqA6Pvc2PDpXTTCsYu5Zyp5110P0PFdvXZvHnz+Oijj9ixY4dpbtHKlSt5/fXX2b59u1VL8rX6TEREpOix9Pu72C4x6NOnDx4eHjz//PP89NNPrFq1imnTptGnTx89o0hERERyKLahyNvbm08//RRHR0eef/553nvvPXr06MHYsWPtXZqIiIgUQkV34M8C1atXZ/HixfYuQ0RERIqAYttTJCIiInIvFIpEREREUCgSERERARSKRERERACFIhERERFAoUhEREQEUCgSERERARSKRERERIBi/vBGW0tPT8doNJreoSIiIiKFX1paGgaD4a7nKRTdA0t+oSIiIlK4GAwGi77DDUaj0VgA9YiIiIgUappTJCIiIoJCkYiIiAigUCQiIiICKBSJiIiIAApFIiIiIoBCkYiIiAigUCQiIiICKBSJiIiIAApFIiIiIoBCkYiIiAigUCQiIiICKBSJiIiIAApFchsbN27k2Wef5YEHHiAkJIRHHnmEr776Cr0/uHjasWMHffv2JSwsjHr16tGuXTumTJlCQkKCvUuTAnDz5k0eeOABgoKCOHTokL3LERtbvXo1QUFBOf5599137V1aoeNk7wKkcFq8eDEVK1Zk7NixlCpVip07dzJhwgQuXbrE8OHD7V2e2FhsbCz169enX79++Pj4cOzYMWbNmsWxY8dYtGiRvcuTfDZnzhwyMzPtXYbks4ULF1KyZEnTtr+/vx2rKZwUiiRXc+fOxdfX17TdvHlzYmNj+eSTT3juuedwcFAnY3HyyCOPmG2Hhobi4uLChAkTuHz5sv7jWYydOHGCL774gjFjxvD666/buxzJR3Xr1jX777rkpG82yVVu/+LUrl2bxMREkpKS7FCRFDQfHx8A0tPT7VuI5KvJkyfTp08fAgIC7F2KiN0pFInF9u/fj7+/P56envYuRfJJZmYmqamp/PHHH8yePZu2bdtSqVIle5cl+WTTpk0cPXqU559/3t6lSAHo2rUrtWvXpl27dsybN09DprnQ8JlYZN++fURGRjJmzBh7lyL5qE2bNly+fBmAVq1a8d5779m5IskvycnJTJ06lVGjRul/dIo5Pz8/RowYQYMGDTAYDGzbto0PPviAy5cvM3HiRHuXV6goFMldXbp0iVGjRhEaGkr//v3tXY7ko/nz55OcnMzx48eZO3cuw4YN45NPPsHR0dHepYmNzZ07l9KlS/P444/buxTJZ61ataJVq1am7ZYtW+Lq6sqnn37KsGHDKFu2rB2rK1w0fCZ3FB8fz+DBg/Hx8WHWrFmaYF3M1apVi4YNG9KzZ0/mzJnDnj17+Pbbb+1dlthYdHQ0ixYt4oUXXiAhIYH4+HjTXMGkpCRu3rxp5wolv3Xu3JnMzEyioqLsXUqhop4iua2UlBSGDh1KQkICy5cvN1vKKcVfUFAQzs7OnD171t6liI2dP3+e9PR0hgwZkuNY//79adCgAStWrLBDZSL2pVAkucrIyGDkyJGcPHmSpUuXakn2v9Dvv/9Oenq6JloXQ7Vr1+azzz4z2xcVFcWUKVOYNGkSwcHBdqpMCkpkZCSOjo7UqVPH3qUUKgpFkqtJkyaxfft2xo4dS2JiIr/99pvpWJ06dXBxcbFfcWJzw4cPp169egQFBeHm5saRI0f4+OOPCQoKon379vYuT2zMy8uL0NDQXI/VrVuXunXrFnBFkp8GDhxIaGgoQUFBAGzdupUVK1bQv39//Pz87Fxd4aJQJLn6+eefAZg6dWqOY1u3blXvQTFTv359IiMjmT9/PkajkYoVK9KzZ08GDhyoACxSxAUEBLBq1SouXbpEVlYW1apV49VXX6Vfv372Lq3QMRj1MisRERERrT4TERERAYUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBKRAnT+/HmCgoJYvXq1ad/YsWNp2LChHasSEblFoUhEbGL16tUEBQVx6NAhe5eSq+PHjzNr1izOnz9v8TX79u1j0KBBtGrViuDgYFq3bs2wYcNYt25dPlYqIvai13yISIGpWLEiBw8exMmp4P/Tc/z4cSIiImjWrJlFr6nZuHEjo0aNonbt2vTv3x9vb2/Onz/P3r17WbFiBd26dSuAqkWkICkUiUiBMRgMuLq6Fug9U1NTcXZ2vufrIiIiqFGjBsuXL8/x/rfr16/bqry7MhqNpKam4ubmVmD3FPm30vCZiBSY3OYU5SYqKoqwsDD69evHzZs3Abh8+TLjxo3j/vvvp169enTp0oWvvvrK7Lo9e/YQFBTEhg0beP/992nVqhUNGjTgs88+47///S8A/fv3JygoiKCgIPbs2XPbGs6ePUtwcHCuL8QtXbq02XZWVhaffvop3bp1Izg4mLCwMAYOHGg2lJiRkcHs2bNp37499erVo23btsyYMYO0tDSzttq2bcvQoUP58ccf6d69O/Xr12fZsmUAxMfH8/bbb/Pggw9Sr149OnTowPz588nKyrrj71NELKOeIhEpVA4ePMigQYOoV68ec+bMwc3NjWvXrtGrVy8MBgNPPfUUvr6+/PDDD4wfP57ExESeeeYZszbmzJmDs7MzAwcOJC0tjZYtW9KvXz+WLFnCsGHDCAwMBKB69eq3raNChQrs2rWLS5cuUa5cuTvWPH78eFavXs0DDzxAjx49yMzMZN++ffz+++8EBwcD8Nprr7FmzRo6derEf/7zHw4ePMi8efM4ceIEs2fPNmvv1KlTvPTSS/Tu3ZtevXoREBBAcnIyffv25fLly/Tp04fy5ctz4MABZsyYwdWrVxk/frwVv20R+TuFIhEpNPbv38+QIUNo0qQJs2bNMvXSvP/++2RmZrJu3TpKlSoFwBNPPMGLL75IREQEffr0MRteSk1NZdWqVWb7mjRpwpIlS7j//vsJDQ29ay2DBw9m/PjxtG/fnkaNGtG4cWNatGhBo0aNcHD4v0723bt3s3r1avr168drr71m2j9gwACMRiMAR44cYc2aNfTs2ZPJkycDmMLdokWL2L17N2FhYaZrz5w5w8KFC2nVqpVp35w5czh37hxr1qyhWrVqAPTp04eyZcvy8ccfM2DAAMqXL2/x71pEctLwmYgUCrt372bQoEE0b97cLBAZjUa2bNlC27ZtMRqNxMTEmP5p2bIlCQkJ/PHHH2ZtPfroo3meg9OjRw8WLlxIaGgov/76K3PmzOGpp56iY8eO/Prrr6bztmzZgsFgYPjw4TnaMBgMAOzYsQOA//znP2bHBwwYYHY8W6VKlcwCEcCmTZto3LgxXl5eZr+D+++/n8zMTPbu3Zunn1dE1FMkIoVAamoqQ4cOpW7dunzwwQdmq9NiYmKIj49n+fLlLF++PNfrY2JizLYtWV1miVatWtGqVSuSk5P5448/iIyMZNmyZQwbNoyNGzdSunRpzp49S9myZfHx8bltO9HR0Tg4OFClShWz/X5+fnh5eREdHX3X+s+cOcNff/1F8+bNc73HP38HInLvFIpExO5cXFx44IEH2LZtGz/++CNt2rQxHcueRPzwww/z2GOP5Xp9UFCQ2batV2qVKFGCJk2a0KRJE0qVKkVERAQ//PDDbeu5neyeo7vJrf6srCxatGjBoEGDcr0me0hNRKynUCQidmcwGHj33Xd57rnn+O9//8uCBQtM8358fX3x8PAgKyuL+++/P0/3sIV69eoBcPXqVQCqVKnCTz/9RGxs7G17iypWrEhWVhZnzpwxm9x97do14uPjqVix4l3vW6VKFZKSkvL0OxCRO9OcIhEpFFxcXIiIiCA4OJhhw4Zx8OBBABwdHenUqRObN2/m6NGjOa6zdNioRIkSACQkJFh0/q5du3Ldnz3/JyAgAICOHTtiNBqJiIjIcW72ROsHH3wQgE8//dTs+CeffGJ2/E46d+7MgQMH+PHHH3Mci4+PJyMj465tiMidqadIRGxq1apVuX5x9+/f/67Xurm5MW/ePPr378/gwYNZsmQJNWvW5KWXXmLPnj306tWLnj17UqNGDeLi4vjjjz/YtWsXv/zyy13brl27No6OjixYsICEhARcXFwICwvL8cyhbM899xyVKlWiTZs2VK5cmeTkZHbu3Mn27dsJDg42DfGFhYXxyCOPsGTJEs6cOUOrVq3Iyspi//79hIaG0rdvX2rVqsVjjz3G8uXLiY+Pp2nTphw6dIg1a9bQvn17s5VntzNw4EC2bdvGsGHDeOyxx6hbty7JyckcPXqUzZs3s3XrVnx9fe/ajojcnkKRiNjUl19+mev+7t27W3S9p6cnH3/8MX379mXAgAEsXbqUqlWrsnLlSmbPns23337Ll19+iY+PDzVq1GD06NEWtevn58ekSZOYN28e48ePJzMzk88+++y2oWjy5Mls3bqVjRs3cuXKFYxGI5UrV2bYsGEMHjzYbDL4lClTCAoK4quvvmLatGmULFmSevXqmb3odvLkyVSqVIk1a9bw3XffUaZMGYYOHZrrqrXclChRgiVLljBv3jw2bdrE119/jaenJ9WqVWPEiBGULFnSonZE5PYMxuz+XREREZF/Mc0pEhEREUGhSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREUChSERERARQKBIREREBFIpEREREAIUiEREREQD+HxZ1oEaDon0aAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -594,8 +795,30 @@
     }
    ],
    "source": [
+    "x = rad_df[[\"LikertScore\", \"hausdorff_distance_95\"]].dropna()\n",
+    "rad_tau, rad_p_value = stats.kendalltau(\n",
+    "    x.LikertScore.values, x.hausdorff_distance_95.values\n",
+    ")\n",
+    "x = ne_df[[\"LikertScore\", \"hausdorff_distance_95\"]].dropna()\n",
+    "ne_tau, ne_p_value = stats.kendalltau(\n",
+    "    x.LikertScore.values, x.hausdorff_distance_95.values\n",
+    ")\n",
+    "\n",
+    "print(\n",
+    "    f\"\"\"\\\n",
+    "        Radiologist: Kendall-\\u03C4: {rad_tau:.2f}, p-value: {rad_p_value:.2f}\n",
+    "        Non-expert: Kendall-\\u03C4: {ne_tau:.2f}, p-value: {ne_p_value:.2f}\n",
+    "        \"\"\"\n",
+    ")\n",
+    "\n",
     "# plot likert score vs dice\n",
-    "g = sns.swarmplot(data=xdf, x=\"LikertScore\", y=\"hausdorff_distance_95\", hue=\"Reviewer\")\n",
+    "g = sns.swarmplot(\n",
+    "    data=xdf,\n",
+    "    x=\"LikertScore\",\n",
+    "    y=\"hausdorff_distance_95\",\n",
+    "    hue=\"Reviewer\",\n",
+    "    palette=revewer_cmap,\n",
+    ")\n",
     "g.set(xlabel=\"Likert Score\", ylabel=\"95% Hausdorff Distance (mm)\")"
    ]
   },

From 057e46c8ca26709a0c52bab0ea927a63cd1e0e18 Mon Sep 17 00:00:00 2001
From: Jeff VanOss <jeff.vanoss@bamfhealth.com>
Date: Fri, 6 Oct 2023 17:08:52 +0000
Subject: [PATCH 2/3] update dependencies

---
 poetry.lock | 325 ++++++++++++++++++++++++++++------------------------
 1 file changed, 174 insertions(+), 151 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index df5b2af..2bdb914 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -211,87 +211,102 @@ files = [
 
 [[package]]
 name = "charset-normalizer"
-version = "3.2.0"
+version = "3.3.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 category = "main"
 optional = false
 python-versions = ">=3.7.0"
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 [[package]]
@@ -557,18 +572,18 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "executing"
-version = "1.2.0"
+version = "2.0.0"
 description = "Get the currently executing AST node of a frame, and other information"
 category = "main"
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [package.extras]
-tests = ["asttokens", "littleutils", "pytest", "rich"]
+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
 
 [[package]]
 name = "filelock"
@@ -589,46 +604,54 @@ typing = ["typing-extensions (>=4.7.1)"]
 
 [[package]]
 name = "fonttools"
-version = "4.42.1"
+version = "4.43.1"
 description = "Tools to manipulate font files"
 category = "main"
 optional = false
 python-versions = ">=3.8"
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 [[package]]
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 category = "main"
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 python-versions = ">=3.6"
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@@ -826,7 +849,7 @@ parso = ">=0.8.3,<0.9.0"
 [package.extras]
 docs = ["Jinja2 (==2.11.3)", "MarkupSafe (==1.1.1)", "Pygments (==2.8.1)", "alabaster (==0.7.12)", "babel (==2.9.1)", "chardet (==4.0.0)", "commonmark (==0.8.1)", "docutils (==0.17.1)", "future (==0.18.2)", "idna (==2.10)", "imagesize (==1.2.0)", "mock (==1.0.1)", "packaging (==20.9)", "pyparsing (==2.4.7)", "pytz (==2021.1)", "readthedocs-sphinx-ext (==2.1.4)", "recommonmark (==0.5.0)", "requests (==2.25.1)", "six (==1.15.0)", "snowballstemmer (==2.1.0)", "sphinx (==1.8.5)", "sphinx-rtd-theme (==0.4.3)", "sphinxcontrib-serializinghtml (==1.1.4)", "sphinxcontrib-websupport (==1.2.4)", "urllib3 (==1.26.4)"]
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
-testing = ["Django (<3.1)", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "joblib"
@@ -1243,14 +1266,14 @@ files = [
 
 [[package]]
 name = "packaging"
-version = "23.1"
+version = "23.2"
 description = "Core utilities for Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
-    {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
+    {file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
+    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
 ]
 
 [[package]]
@@ -1440,14 +1463,14 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa
 
 [[package]]
 name = "platformdirs"
-version = "3.10.0"
+version = "3.11.0"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "platformdirs-3.10.0-py3-none-any.whl", hash = "sha256:d7c24979f292f916dc9cbf8648319032f551ea8c49a4c9bf2fb556a02070ec1d"},
-    {file = "platformdirs-3.10.0.tar.gz", hash = "sha256:b45696dab2d7cc691a3226759c0d3b00c47c8b6e293d96f6436f733303f77f6d"},
+    {file = "platformdirs-3.11.0-py3-none-any.whl", hash = "sha256:e9d171d00af68be50e9202731309c4e658fd8bc76f55c11c7dd760d023bda68e"},
+    {file = "platformdirs-3.11.0.tar.gz", hash = "sha256:cf8ee52a3afdb965072dcc652433e0c7e3e40cf5ea1477cd4b3b1d2eb75495b3"},
 ]
 
 [package.extras]
@@ -2157,26 +2180,26 @@ testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jar
 
 [[package]]
 name = "setuptools-scm"
-version = "8.0.3"
+version = "8.0.4"
 description = "the blessed package to manage your versions by scm tags"
 category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "setuptools-scm-8.0.3.tar.gz", hash = "sha256:0169fd70197efda2f8c4d0b2a7a3d614431b488116f37b79d031e9e7ec884d8c"},
-    {file = "setuptools_scm-8.0.3-py3-none-any.whl", hash = "sha256:813822234453438a13c78d05c8af29918fbc06f88efb33d38f065340bbb48c39"},
+    {file = "setuptools-scm-8.0.4.tar.gz", hash = "sha256:b5f43ff6800669595193fd09891564ee9d1d7dcb196cab4b2506d53a2e1c95c7"},
+    {file = "setuptools_scm-8.0.4-py3-none-any.whl", hash = "sha256:b47844cd2a84b83b3187a5782c71128c28b4c94cad8bfb871da2784a5cb54c4f"},
 ]
 
 [package.dependencies]
 packaging = ">=20"
 setuptools = "*"
 tomli = {version = ">=1", markers = "python_version < \"3.11\""}
-typing-extensions = {version = "*", markers = "python_version < \"3.11\""}
+typing-extensions = "*"
 
 [package.extras]
 docs = ["entangled-cli[rich]", "mkdocs", "mkdocs-entangled-plugin", "mkdocs-material", "mkdocstrings[python]", "pygments"]
 rich = ["rich"]
-test = ["pytest", "rich", "virtualenv (>20)"]
+test = ["build", "pytest", "rich", "wheel"]
 
 [[package]]
 name = "simpleitk"
@@ -2222,14 +2245,14 @@ files = [
 
 [[package]]
 name = "stack-data"
-version = "0.6.2"
+version = "0.6.3"
 description = "Extract data from python stack frames and tracebacks for informative displays"
 category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "stack_data-0.6.2-py3-none-any.whl", hash = "sha256:cbb2a53eb64e5785878201a97ed7c7b94883f48b87bfb0bbe8b623c74679e4a8"},
-    {file = "stack_data-0.6.2.tar.gz", hash = "sha256:32d2dd0376772d01b6cb9fc996f3c8b57a357089dec328ed4b6553d037eaf815"},
+    {file = "stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695"},
+    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
 ]
 
 [package.dependencies]
@@ -2326,14 +2349,14 @@ telegram = ["requests"]
 
 [[package]]
 name = "traitlets"
-version = "5.10.1"
+version = "5.11.2"
 description = "Traitlets Python configuration system"
 category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "traitlets-5.10.1-py3-none-any.whl", hash = "sha256:07ab9c5bf8a0499fd7b088ba51be899c90ffc936ffc797d7b6907fc516bcd116"},
-    {file = "traitlets-5.10.1.tar.gz", hash = "sha256:db9c4aa58139c3ba850101913915c042bdba86f7c8a0dda1c6f7f92c5da8e542"},
+    {file = "traitlets-5.11.2-py3-none-any.whl", hash = "sha256:98277f247f18b2c5cabaf4af369187754f4fb0e85911d473f72329db8a7f4fae"},
+    {file = "traitlets-5.11.2.tar.gz", hash = "sha256:7564b5bf8d38c40fa45498072bf4dc5e8346eb087bbf1e2ae2d8774f6a0f078e"},
 ]
 
 [package.extras]
@@ -2366,14 +2389,14 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.0.5"
+version = "2.0.6"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "urllib3-2.0.5-py3-none-any.whl", hash = "sha256:ef16afa8ba34a1f989db38e1dbbe0c302e4289a47856990d0682e374563ce35e"},
-    {file = "urllib3-2.0.5.tar.gz", hash = "sha256:13abf37382ea2ce6fb744d4dad67838eec857c9f4f57009891805e0b5e123594"},
+    {file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"},
+    {file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"},
 ]
 
 [package.extras]
@@ -2405,14 +2428,14 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 
 [[package]]
 name = "wcwidth"
-version = "0.2.7"
+version = "0.2.8"
 description = "Measures the displayed width of unicode strings in a terminal"
 category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "wcwidth-0.2.7-py2.py3-none-any.whl", hash = "sha256:fabf3e32999d9b0dab7d19d845149f326f04fe29bac67709ee071dbd92640a36"},
-    {file = "wcwidth-0.2.7.tar.gz", hash = "sha256:1b6d30a98ddd5ce9bbdb33658191fd2423fc9da203fe3ef1855407dcb7ee4e26"},
+    {file = "wcwidth-0.2.8-py2.py3-none-any.whl", hash = "sha256:77f719e01648ed600dfa5402c347481c0992263b81a027344f3e1ba25493a704"},
+    {file = "wcwidth-0.2.8.tar.gz", hash = "sha256:8705c569999ffbb4f6a87c6d1b80f324bd6db952f5eb0b95bc07517f4c1813d4"},
 ]
 
 [metadata]

From e6fbc21581fd850b19cdc3657e7b5886960b1dbe Mon Sep 17 00:00:00 2001
From: Jeff VanOss <jeff.vanoss@bamfhealth.com>
Date: Mon, 16 Oct 2023 19:05:27 +0000
Subject: [PATCH 3/3] update graphs

---
 .pre-commit-config.yaml |   1 +
 model_performance.ipynb | 193 +++++++++++++++++++++++++---------------
 2 files changed, 122 insertions(+), 72 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index c0a2782..b98be3c 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -4,6 +4,7 @@ repos:
     hooks:
       - id: trailing-whitespace
       - id: end-of-file-fixer
+        exclude_types: [jupyter, csv]
       - id: check-yaml
       - id: check-merge-conflict
       - id: debug-statements
diff --git a/model_performance.ipynb b/model_performance.ipynb
index f3ea381..d090a70 100644
--- a/model_performance.ipynb
+++ b/model_performance.ipynb
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -59,7 +59,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -93,13 +93,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
     "def download_inference(\n",
     "    extract_dir=\"qa-results\",\n",
-    "    url=\"https://zenodo.org/record/8400869/files/liver-mr.zip\",\n",
+    "    url=\"https://zenodo.org/record/10009368/files/liver-mr.zip\",\n",
     "):\n",
     "    # download the zip file and extract it\n",
     "    r = requests.get(url)\n",
@@ -149,7 +149,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -208,7 +208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -235,22 +235,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f3b2faa7f70>"
+       "<seaborn.axisgrid.FacetGrid at 0x7fad618675e0>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640.75x500 with 1 Axes>"
       ]
@@ -260,32 +260,32 @@
     }
    ],
    "source": [
-    "df2 = val_df.groupby([\"Reviewer\", \"LikertScore\"]).count()\n",
-    "for reviewer in val_df[\"Reviewer\"].unique():\n",
-    "    for score in range(1, 6):\n",
-    "        if (reviewer, score) not in df2.index:\n",
-    "            df2.loc[(reviewer, score), \"SeriesInstanceUID\"] = 0\n",
-    "\n",
-    "df2.reset_index(inplace=True)\n",
-    "\n",
     "g = sns.catplot(\n",
-    "    data=df2,\n",
-    "    kind=\"bar\",\n",
+    "    data=val_df,\n",
+    "    kind=\"count\",\n",
     "    x=\"LikertScore\",\n",
-    "    y=\"SeriesInstanceUID\",\n",
+    "    order=[1, 2, 3, 4, 5],\n",
     "    hue=\"Reviewer\",\n",
-    "    orient=\"v\",\n",
+    "    hue_order=[\"Radiologist\", \"Non-expert\"],\n",
     "    palette=revewer_cmap,\n",
     ")\n",
-    "# g.despine(left=True)\n",
-    "g.set_axis_labels(\"Likert Score\", \"Counts\")\n",
-    "g.legend.set_title(\"\")\n",
-    "g.set(title=f\"Likert Score by Reviewer\")"
+    "g.set_axis_labels(\"\", \"Counts\")\n",
+    "g.set(title=f\"Likert Score by Reviewer\\nKendall's \\u03c4: {tau:.2f}\")\n",
+    "g.set_xticklabels(\n",
+    "    labels=[\n",
+    "        \"Strongly\\nDisagree\",\n",
+    "        \"Disagree\",\n",
+    "        \"Neither Agree\\nnor Disagree\",\n",
+    "        \"Agree\",\n",
+    "        \"Strongly\\nAgree\",\n",
+    "    ],\n",
+    "    rotation=60,\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -294,7 +294,7 @@
        "Text(0.5, 1.0, 'Likert Score Distribution for Radiologist')"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -334,7 +334,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -412,7 +412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -424,7 +424,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -440,59 +440,98 @@
        "        vertical-align: top;\n",
        "    }\n",
        "\n",
-       "    .dataframe thead th {\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
        "        text-align: right;\n",
        "    }\n",
        "</style>\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
+       "    <tr>\n",
+       "      <th></th>\n",
        "      <th></th>\n",
-       "      <th>dice</th>\n",
-       "      <th>hausdorff_distance_95</th>\n",
-       "      <th>mean_surface_distance_tol_7</th>\n",
-       "      <th>mean_surface_distance</th>\n",
+       "      <th colspan=\"2\" halign=\"left\">dice</th>\n",
+       "      <th colspan=\"2\" halign=\"left\">hausdorff_distance_95</th>\n",
+       "      <th colspan=\"2\" halign=\"left\">mean_surface_distance</th>\n",
+       "      <th colspan=\"2\" halign=\"left\">mean_surface_distance_tol_7</th>\n",
        "    </tr>\n",
        "    <tr>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>label</th>\n",
        "      <th>Reviewer</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th rowspan=\"2\" valign=\"top\">liver</th>\n",
        "      <th>Non-expert</th>\n",
-       "      <td>0.900939</td>\n",
-       "      <td>33.208145</td>\n",
-       "      <td>0.847362</td>\n",
-       "      <td>6.434494</td>\n",
+       "      <td>0.90</td>\n",
+       "      <td>0.15</td>\n",
+       "      <td>33.21</td>\n",
+       "      <td>47.96</td>\n",
+       "      <td>6.43</td>\n",
+       "      <td>10.12</td>\n",
+       "      <td>0.85</td>\n",
+       "      <td>0.2</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Radiologist</th>\n",
-       "      <td>0.910815</td>\n",
-       "      <td>14.663781</td>\n",
-       "      <td>0.885720</td>\n",
-       "      <td>3.651561</td>\n",
+       "      <td>0.91</td>\n",
+       "      <td>0.18</td>\n",
+       "      <td>14.66</td>\n",
+       "      <td>25.98</td>\n",
+       "      <td>3.65</td>\n",
+       "      <td>6.88</td>\n",
+       "      <td>0.89</td>\n",
+       "      <td>0.2</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                 dice  hausdorff_distance_95  mean_surface_distance_tol_7  \\\n",
-       "Reviewer                                                                    \n",
-       "Non-expert   0.900939              33.208145                     0.847362   \n",
-       "Radiologist  0.910815              14.663781                     0.885720   \n",
+       "                   dice       hausdorff_distance_95         \\\n",
+       "                   mean   std                  mean    std   \n",
+       "label Reviewer                                               \n",
+       "liver Non-expert   0.90  0.15                 33.21  47.96   \n",
+       "      Radiologist  0.91  0.18                 14.66  25.98   \n",
        "\n",
-       "             mean_surface_distance  \n",
-       "Reviewer                            \n",
-       "Non-expert                6.434494  \n",
-       "Radiologist               3.651561  "
+       "                  mean_surface_distance        mean_surface_distance_tol_7  \\\n",
+       "                                   mean    std                        mean   \n",
+       "label Reviewer                                                               \n",
+       "liver Non-expert                   6.43  10.12                        0.85   \n",
+       "      Radiologist                  3.65   6.88                        0.89   \n",
+       "\n",
+       "                        \n",
+       "                   std  \n",
+       "label Reviewer          \n",
+       "liver Non-expert   0.2  \n",
+       "      Radiologist  0.2  "
       ]
      },
-     "execution_count": 23,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -500,13 +539,23 @@
    "source": [
     "xdf[\n",
     "    [\n",
+    "        \"label\",\n",
     "        \"Reviewer\",\n",
     "        \"dice\",\n",
     "        \"hausdorff_distance_95\",\n",
-    "        \"mean_surface_distance_tol_7\",\n",
     "        \"mean_surface_distance\",\n",
+    "        \"mean_surface_distance_tol_7\",\n",
     "    ]\n",
-    "].replace([np.inf, -np.inf], np.nan).dropna().groupby(\"Reviewer\").mean()"
+    "].replace([np.inf, -np.inf], np.nan).dropna().groupby([\"label\", \"Reviewer\"]).agg(\n",
+    "    {\n",
+    "        \"dice\": [\"mean\", \"std\"],\n",
+    "        \"hausdorff_distance_95\": [\"mean\", \"std\"],\n",
+    "        \"mean_surface_distance\": [\"mean\", \"std\"],\n",
+    "        \"mean_surface_distance_tol_7\": [\"mean\", \"std\"],\n",
+    "    }\n",
+    ").round(\n",
+    "    2\n",
+    ")"
    ]
   },
   {
@@ -518,16 +567,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f39b2a683a0>"
+       "<seaborn.axisgrid.FacetGrid at 0x7fad619de8f0>"
       ]
      },
-     "execution_count": 24,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -557,16 +606,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f39b03bee30>"
+       "<seaborn.axisgrid.FacetGrid at 0x7fad617386d0>"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -601,16 +650,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<seaborn.axisgrid.FacetGrid at 0x7f39b2adf160>"
+       "<seaborn.axisgrid.FacetGrid at 0x7fad6173b8e0>"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -641,7 +690,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -659,7 +708,7 @@
        "[Text(0.5, 19.049999999999997, 'Likert Score'), Text(37.0, 0.5, 'DSC')]"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -696,7 +745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -715,7 +764,7 @@
        " Text(37.0, 0.5, 'Normalized Surface Dice\\n(tolerance=7mm)')]"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -760,7 +809,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -779,7 +828,7 @@
        " Text(32.375, 0.5, '95% Hausdorff Distance (mm)')]"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     },