2214 lines (2213 with data), 329.3 kB

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   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "df = pd.read_csv(\"/Users/amulya/Desktop/Biomedical-Text-Extraction-main/pubmed/Csv_files/final_pubmed_v3.csv\")"
   ]
  },
  {
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   "id": "857bfbde-aa37-4d28-96f9-6950216990ab",
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       "      <th>Unnamed: 0</th>\n",
       "      <th>Title</th>\n",
       "      <th>Abstract</th>\n",
       "      <th>Journal</th>\n",
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       "      <th>Name</th>\n",
       "      <th>...</th>\n",
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       "      <td>Nov</td>\n",
       "      <td>Zhou Zigui, Tian Xuewen</td>\n",
       "      <td>school of exercise and health, shanghai univer...</td>\n",
       "      <td>bmc public health</td>\n",
       "      <td>...</td>\n",
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       "      <td>PUBLIC, ENVIRONMENTAL &amp; OCCUPATIONAL HEALTH|Q1...</td>\n",
       "      <td>school of exercise and health, shanghai univer...</td>\n",
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       "      <td>shanghai university</td>\n",
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       "      <td>38.0</td>\n",
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       "      <td>bmc nephrology</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Taurbekova Binura, Mukhtarova Kymbat, Salpynov...</td>\n",
       "      <td>department of biomedical sciences, school of m...</td>\n",
       "      <td>bmc nephrology</td>\n",
       "      <td>...</td>\n",
       "      <td>2.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>UROLOGY &amp; NEPHROLOGY|Q2|54/126</td>\n",
       "      <td>school of medicine, nazarbayev university, sch...</td>\n",
       "      <td>meta-analysis</td>\n",
       "      <td>nazarbayev university</td>\n",
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       "      <td>29.5</td>\n",
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       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>immune checkpoint landscape of human atheroscl...</td>\n",
       "      <td>immune checkpoint inhibitor (ici) therapies ca...</td>\n",
       "      <td>nature cardiovascular research</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Barcia Durán José Gabriel, Das Dayasagar, Gild...</td>\n",
       "      <td>nyu cardiovascular research center, division o...</td>\n",
       "      <td>nature cardiovascular research</td>\n",
       "      <td>...</td>\n",
       "      <td>9.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>CARDIAC &amp; CARDIOVASCULAR SYSTEMS|Q1|13/220</td>\n",
       "      <td>nyu cardiovascular research center, department...</td>\n",
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       "      <td>york university</td>\n",
       "      <td>351–400</td>\n",
       "      <td>32.4</td>\n",
       "      <td>375.5</td>\n",
       "      <td>Low (0-50)</td>\n",
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       "      <td>yale university</td>\n",
       "      <td>10</td>\n",
       "      <td>94.9</td>\n",
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       "      <td>High (75-100)</td>\n",
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       "      <th>4</th>\n",
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       "      <td>determining the quality of life and associated...</td>\n",
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       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Gül Şenay, Demir Ayşe Sılanur, Karadağ Ayişe, ...</td>\n",
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       "      <td>26.8</td>\n",
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       "   Unnamed: 0                                              Title  \\\n",
       "0           0  prevalence and association of sleep duration a...   \n",
       "1           1  the impact of pparγ and apoe gene polymorphism...   \n",
       "2           2  immune checkpoint landscape of human atheroscl...   \n",
       "3           3  ezrin drives adaptation of monocytes to the in...   \n",
       "4           4  determining the quality of life and associated...   \n",
       "\n",
       "                                            Abstract  \\\n",
       "0  this study aimed to examine the prevalence of ...   \n",
       "1  globally, diabetic kidney disease (dkd) has be...   \n",
       "2  immune checkpoint inhibitor (ici) therapies ca...   \n",
       "3  ezrin, an actin-binding protein, orchestrates ...   \n",
       "4  this study aimed to determine the quality of l...   \n",
       "\n",
       "                          Journal Language  Year Month  \\\n",
       "0               bmc public health      eng  2024   Nov   \n",
       "1                  bmc nephrology      eng  2024   Nov   \n",
       "2  nature cardiovascular research      eng  2024   Nov   \n",
       "3            cell death & disease      eng  2024   Nov   \n",
       "4     journal of tissue viability      eng  2024   Nov   \n",
       "\n",
       "                                             Authors  \\\n",
       "0                            Zhou Zigui, Tian Xuewen   \n",
       "1  Taurbekova Binura, Mukhtarova Kymbat, Salpynov...   \n",
       "2  Barcia Durán José Gabriel, Das Dayasagar, Gild...   \n",
       "3  Gudneppanavar Ravindra, Di Pietro Caterina, H ...   \n",
       "4  Gül Şenay, Demir Ayşe Sılanur, Karadağ Ayişe, ...   \n",
       "\n",
       "                                        Affiliations  \\\n",
       "0  school of exercise and health, shanghai univer...   \n",
       "1  department of biomedical sciences, school of m...   \n",
       "2  nyu cardiovascular research center, division o...   \n",
       "3  department of pediatrics, school of medicine, ...   \n",
       "4  faculty of nursing, hacettepe university, anka...   \n",
       "\n",
       "                             Name  ... Impact_Factor Impact_Factor_5Years  \\\n",
       "0               bmc public health  ...           3.5                  3.9   \n",
       "1                  bmc nephrology  ...           2.2                  2.6   \n",
       "2  nature cardiovascular research  ...           9.4                  9.4   \n",
       "3            cell death & disease  ...           8.1                  8.6   \n",
       "4     journal of tissue viability  ...           2.4                  2.9   \n",
       "\n",
       "                                    Journal_Category  \\\n",
       "0  PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH|Q1...   \n",
       "1                     UROLOGY & NEPHROLOGY|Q2|54/126   \n",
       "2         CARDIAC & CARDIOVASCULAR SYSTEMS|Q1|13/220   \n",
       "3                             CELL BIOLOGY|Q1|33/205   \n",
       "4                                  NURSING|Q1|35/191   \n",
       "\n",
       "                                        Universities  Study_Type_Extracted  \\\n",
       "0  school of exercise and health, shanghai univer...               Unknown   \n",
       "1  school of medicine, nazarbayev university, sch...         meta-analysis   \n",
       "2  nyu cardiovascular research center, department...  clinical development   \n",
       "3  school of medicine, yale university, school of...               Unknown   \n",
       "4  hacettepe university, koc university, school o...               Unknown   \n",
       "\n",
       "  Standardized_University     Rank Research_Score Rank_Median  \\\n",
       "0     shanghai university  501–600           38.0       550.5   \n",
       "1   nazarbayev university  501–600           29.5       550.5   \n",
       "2         york university  351–400           32.4       375.5   \n",
       "3         yale university       10           94.9        10.0   \n",
       "4    hacettepe university  601–800           26.8       700.5   \n",
       "\n",
       "  Research_Score_Category  \n",
       "0              Low (0-50)  \n",
       "1              Low (0-50)  \n",
       "2              Low (0-50)  \n",
       "3           High (75-100)  \n",
       "4              Low (0-50)  \n",
       "\n",
       "[5 rows x 23 columns]"
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   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6722dc95-c903-472b-9359-5bbd1c845d6b",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Profiling GMM Clusters\n",
      "Cluster Profiles for GMM_Cluster:\n",
      "\n",
      "             Impact_Factor_5Years  Research_Score\n",
      "GMM_Cluster                                      \n",
      "0                        3.358442       28.812121\n",
      "1                        5.511864       63.382627\n",
      "2                       21.829545       63.150000\n",
      "Silhouette Score for GMM Clustering: 0.3877705258707141\n"
     ]
    },
    {
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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Preprocessing: Select relevant numerical features and handle missing values\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.cluster import KMeans, DBSCAN\n",
    "from sklearn.mixture import GaussianMixture\n",
    "from sklearn.metrics import silhouette_score\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "# Define numerical features\n",
    "numerical_features = ['Impact_Factor_5Years', 'Research_Score']  # Replace with your actual column names\n",
    "\n",
    "data_subset = df[numerical_features].copy()\n",
    "# data_subset = data_subset.fillna(data_subset.mean())  # Fill missing values with mean (or other strategy)\n",
    "\n",
    "# Standardize the data\n",
    "scaler = StandardScaler()\n",
    "data_scaled = scaler.fit_transform(data_subset)\n",
    "\n",
    "# Step 2: Gaussian Mixture Model (GMM) Clustering\n",
    "gmm = GaussianMixture(n_components=3, random_state=42)\n",
    "gmm_labels = gmm.fit_predict(data_scaled)\n",
    "df['GMM_Cluster'] = gmm_labels\n",
    "\n",
    "# Step 3: Profile the Clusters\n",
    "def profile_clusters(data, cluster_col, features):\n",
    "    cluster_profiles = data.groupby(cluster_col)[features].mean()\n",
    "    print(f\"Cluster Profiles for {cluster_col}:\\n\")\n",
    "    print(cluster_profiles)\n",
    "    return cluster_profiles\n",
    "\n",
    "# Profile GMM Clusters\n",
    "print(\"Profiling GMM Clusters\")\n",
    "gmm_profiles = profile_clusters(df, 'GMM_Cluster', numerical_features)\n",
    "\n",
    "# Evaluate GMM Clustering\n",
    "silhouette_gmm = silhouette_score(data_scaled, gmm_labels)\n",
    "print(f\"Silhouette Score for GMM Clustering: {silhouette_gmm}\")\n",
    "\n",
    "# Visualize GMM Clusters with actual features\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.scatterplot(\n",
    "    x=df['Research_Score'], \n",
    "    y=df['Impact_Factor_5Years'], \n",
    "    hue=gmm_labels, \n",
    "    palette='coolwarm', \n",
    "    alpha=0.7\n",
    ")\n",
    "plt.title('Gaussian Mixture Model (GMM) Clustering')\n",
    "plt.xlabel('Research Score')\n",
    "plt.ylabel('Impact Factor (5 Years)')\n",
    "plt.legend(title='Cluster')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "03606304-0eb7-4ae2-b849-45f6a7c97722",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-2.125774594213408\n",
      "15\n"
     ]
    }
   ],
   "source": [
    "# print the converged log-likelihood value\n",
    "print(gmm.lower_bound_)\n",
    " \n",
    "# print the number of iterations needed\n",
    "# for the log-likelihood value to converge\n",
    "print(gmm.n_iter_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ff42b635-4d7c-48d0-9667-b453ddc052b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature Weights Based on Cluster-Centric Variance Ratios:\n",
      "Impact_Factor_5Years    0.784521\n",
      "Research_Score          0.215479\n",
      "dtype: float64\n",
      "\n",
      "Scoring Equation:\n",
      "Score = 0.7845 * Impact_Factor_5Years + 0.2155 * Research_Score\n"
     ]
    }
   ],
   "source": [
    "# Calculate total variance for each feature\n",
    "total_variance = df[numerical_features].var()\n",
    "\n",
    "# Calculate between-cluster variance\n",
    "cluster_means = gmm_profiles.mean(axis=0)\n",
    "between_cluster_variance = gmm_profiles.var()\n",
    "\n",
    "# Calculate within-cluster variance\n",
    "within_cluster_variance = total_variance - between_cluster_variance\n",
    "\n",
    "# Calculate importance ratios\n",
    "importance_ratios = between_cluster_variance / total_variance\n",
    "\n",
    "# Normalize importance ratios to sum to 1\n",
    "weights = importance_ratios / importance_ratios.sum()\n",
    "\n",
    "print(\"Feature Weights Based on Cluster-Centric Variance Ratios:\")\n",
    "print(weights)\n",
    "\n",
    "# Develop the scoring equation\n",
    "impact_factor_weight = weights['Impact_Factor_5Years']\n",
    "research_score_weight = weights['Research_Score']\n",
    "#rank_median_weight = weights['Rank_Median']\n",
    "\n",
    "print(\"\\nScoring Equation:\")\n",
    "print(f\"Score = {impact_factor_weight:.4f} * Impact_Factor_5Years + \"\n",
    "      f\"{research_score_weight:.4f} * Research_Score\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "350be4a6-83ae-4479-af2e-df98d4581e7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the scoring equation\n",
    "df['Score'] = (\n",
    "    impact_factor_weight * df['Impact_Factor_5Years'] +\n",
    "    research_score_weight * df['Research_Score'] \n",
    "    #rank_median_weight * df['Rank_Median']\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "cabc3e0b-c157-4ce6-9eec-dac0ec0fcba1",
   "metadata": {},
   "outputs": [
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       "      <th>Title</th>\n",
       "      <th>Abstract</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Language</th>\n",
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       "      <th>Month</th>\n",
       "      <th>Authors</th>\n",
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       "      <th>Name</th>\n",
       "      <th>...</th>\n",
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       "      <td>eng</td>\n",
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       "      <td>Taurbekova Binura, Mukhtarova Kymbat, Salpynov...</td>\n",
       "      <td>department of biomedical sciences, school of m...</td>\n",
       "      <td>bmc nephrology</td>\n",
       "      <td>...</td>\n",
       "      <td>UROLOGY &amp; NEPHROLOGY|Q2|54/126</td>\n",
       "      <td>school of medicine, nazarbayev university, sch...</td>\n",
       "      <td>meta-analysis</td>\n",
       "      <td>nazarbayev university</td>\n",
       "      <td>501–600</td>\n",
       "      <td>29.5</td>\n",
       "      <td>550.5</td>\n",
       "      <td>Low (0-50)</td>\n",
       "      <td>0</td>\n",
       "      <td>8.396389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>immune checkpoint landscape of human atheroscl...</td>\n",
       "      <td>immune checkpoint inhibitor (ici) therapies ca...</td>\n",
       "      <td>nature cardiovascular research</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Barcia Durán José Gabriel, Das Dayasagar, Gild...</td>\n",
       "      <td>nyu cardiovascular research center, division o...</td>\n",
       "      <td>nature cardiovascular research</td>\n",
       "      <td>...</td>\n",
       "      <td>CARDIAC &amp; CARDIOVASCULAR SYSTEMS|Q1|13/220</td>\n",
       "      <td>nyu cardiovascular research center, department...</td>\n",
       "      <td>clinical development</td>\n",
       "      <td>york university</td>\n",
       "      <td>351–400</td>\n",
       "      <td>32.4</td>\n",
       "      <td>375.5</td>\n",
       "      <td>Low (0-50)</td>\n",
       "      <td>1</td>\n",
       "      <td>14.356020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>ezrin drives adaptation of monocytes to the in...</td>\n",
       "      <td>ezrin, an actin-binding protein, orchestrates ...</td>\n",
       "      <td>cell death &amp; disease</td>\n",
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       "      <td>Gudneppanavar Ravindra, Di Pietro Caterina, H ...</td>\n",
       "      <td>department of pediatrics, school of medicine, ...</td>\n",
       "      <td>cell death &amp; disease</td>\n",
       "      <td>...</td>\n",
       "      <td>CELL BIOLOGY|Q1|33/205</td>\n",
       "      <td>school of medicine, yale university, school of...</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>yale university</td>\n",
       "      <td>10</td>\n",
       "      <td>94.9</td>\n",
       "      <td>10.0</td>\n",
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       "      <td>27.195850</td>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>determining the quality of life and associated...</td>\n",
       "      <td>this study aimed to determine the quality of l...</td>\n",
       "      <td>journal of tissue viability</td>\n",
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       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Gül Şenay, Demir Ayşe Sılanur, Karadağ Ayişe, ...</td>\n",
       "      <td>faculty of nursing, hacettepe university, anka...</td>\n",
       "      <td>journal of tissue viability</td>\n",
       "      <td>...</td>\n",
       "      <td>NURSING|Q1|35/191</td>\n",
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       "   Unnamed: 0                                              Title  \\\n",
       "0           0  prevalence and association of sleep duration a...   \n",
       "1           1  the impact of pparγ and apoe gene polymorphism...   \n",
       "2           2  immune checkpoint landscape of human atheroscl...   \n",
       "3           3  ezrin drives adaptation of monocytes to the in...   \n",
       "4           4  determining the quality of life and associated...   \n",
       "\n",
       "                                            Abstract  \\\n",
       "0  this study aimed to examine the prevalence of ...   \n",
       "1  globally, diabetic kidney disease (dkd) has be...   \n",
       "2  immune checkpoint inhibitor (ici) therapies ca...   \n",
       "3  ezrin, an actin-binding protein, orchestrates ...   \n",
       "4  this study aimed to determine the quality of l...   \n",
       "\n",
       "                          Journal Language  Year Month  \\\n",
       "0               bmc public health      eng  2024   Nov   \n",
       "1                  bmc nephrology      eng  2024   Nov   \n",
       "2  nature cardiovascular research      eng  2024   Nov   \n",
       "3            cell death & disease      eng  2024   Nov   \n",
       "4     journal of tissue viability      eng  2024   Nov   \n",
       "\n",
       "                                             Authors  \\\n",
       "0                            Zhou Zigui, Tian Xuewen   \n",
       "1  Taurbekova Binura, Mukhtarova Kymbat, Salpynov...   \n",
       "2  Barcia Durán José Gabriel, Das Dayasagar, Gild...   \n",
       "3  Gudneppanavar Ravindra, Di Pietro Caterina, H ...   \n",
       "4  Gül Şenay, Demir Ayşe Sılanur, Karadağ Ayişe, ...   \n",
       "\n",
       "                                        Affiliations  \\\n",
       "0  school of exercise and health, shanghai univer...   \n",
       "1  department of biomedical sciences, school of m...   \n",
       "2  nyu cardiovascular research center, division o...   \n",
       "3  department of pediatrics, school of medicine, ...   \n",
       "4  faculty of nursing, hacettepe university, anka...   \n",
       "\n",
       "                             Name  ...  \\\n",
       "0               bmc public health  ...   \n",
       "1                  bmc nephrology  ...   \n",
       "2  nature cardiovascular research  ...   \n",
       "3            cell death & disease  ...   \n",
       "4     journal of tissue viability  ...   \n",
       "\n",
       "                                    Journal_Category  \\\n",
       "0  PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH|Q1...   \n",
       "1                     UROLOGY & NEPHROLOGY|Q2|54/126   \n",
       "2         CARDIAC & CARDIOVASCULAR SYSTEMS|Q1|13/220   \n",
       "3                             CELL BIOLOGY|Q1|33/205   \n",
       "4                                  NURSING|Q1|35/191   \n",
       "\n",
       "                                        Universities  Study_Type_Extracted  \\\n",
       "0  school of exercise and health, shanghai univer...               Unknown   \n",
       "1  school of medicine, nazarbayev university, sch...         meta-analysis   \n",
       "2  nyu cardiovascular research center, department...  clinical development   \n",
       "3  school of medicine, yale university, school of...               Unknown   \n",
       "4  hacettepe university, koc university, school o...               Unknown   \n",
       "\n",
       "   Standardized_University     Rank Research_Score Rank_Median  \\\n",
       "0      shanghai university  501–600           38.0       550.5   \n",
       "1    nazarbayev university  501–600           29.5       550.5   \n",
       "2          york university  351–400           32.4       375.5   \n",
       "3          yale university       10           94.9        10.0   \n",
       "4     hacettepe university  601–800           26.8       700.5   \n",
       "\n",
       "  Research_Score_Category GMM_Cluster      Score  \n",
       "0              Low (0-50)           0  11.247839  \n",
       "1              Low (0-50)           0   8.396389  \n",
       "2              Low (0-50)           1  14.356020  \n",
       "3           High (75-100)           1  27.195850  \n",
       "4              Low (0-50)           0   8.049951  \n",
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      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
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  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1d0fccc5-0a9e-4245-92b3-ff53ff3d6d7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "top_count = 10  # Number of top articles you want to see\n",
    "top_tier_df = df.nlargest(top_count, 'Score')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "a027c81d-7838-452d-9c2a-ce04043ab062",
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Title\"},\"tickfont\":{\"size\":14},\"automargin\":true},\"legend\":{\"title\":{\"text\":\"Journal\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Top-Tier Articles by Score\",\"x\":0.5,\"xanchor\":\"center\"},\"barmode\":\"relative\",\"height\":700,\"width\":1300,\"margin\":{\"l\":500,\"r\":50,\"t\":80,\"b\":50}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('b7e9b2dd-ec16-4af8-9188-c6d32c1ac410');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
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       "\n",
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       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "# Example DataFrame of top-tier articles\n",
    "# Replace this with your actual DataFrame\n",
    "df = top_tier_df  # already filtered or sorted by Score\n",
    "\n",
    "fig = px.bar(\n",
    "    df,\n",
    "    x='Score',\n",
    "    y='Title',\n",
    "    orientation='h',\n",
    "    color='Journal',\n",
    "    hover_data=['Study_Type_Extracted', 'Standardized_University'],\n",
    "    title='Top-Tier Articles by Score',\n",
    "    # Make the figure bigger right from the start\n",
    "    width=1300,  \n",
    "    height=700   \n",
    ")\n",
    "\n",
    "# 1. Give extra margin on the left to accommodate long y-axis labels (article titles)\n",
    "fig.update_layout(\n",
    "    margin=dict(l=500, r=50, t=80, b=50),  # Increase left margin significantly\n",
    "    xaxis_title='Score',\n",
    "    yaxis_title='Article Title',\n",
    "    title={\n",
    "        'text': 'Top-Tier Articles by Score',\n",
    "        'x':0.5,              # Center the title\n",
    "        'xanchor':'center'\n",
    "    }\n",
    ")\n",
    "\n",
    "# 2. Adjust y-axis text properties\n",
    "fig.update_yaxes(\n",
    "    automargin=True,         # Allows Plotly to adjust margins if labels are too long\n",
    "    tickfont=dict(size=14)   # Slightly smaller font so titles fit better\n",
    ")\n",
    "\n",
    "# 3. Optionally adjust the x-axis too if needed\n",
    "fig.update_xaxes(automargin=True)\n",
    "\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "84b34a3b-8a6a-4e7e-9653-88d95c976e1d",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Unnamed: 0</th>\n",
       "      <th>Title</th>\n",
       "      <th>Abstract</th>\n",
       "      <th>Journal</th>\n",
       "      <th>Language</th>\n",
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       "      <th>Authors</th>\n",
       "      <th>Affiliations</th>\n",
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       "      <th>GMM_Cluster</th>\n",
       "      <th>Score</th>\n",
       "      <th>Tier</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>233</td>\n",
       "      <td>author correction: intravenous and intracrania...</td>\n",
       "      <td>no abstract</td>\n",
       "      <td>nature</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Monje Michelle, Mahdi Jasia, Majzner Robbie, Y...</td>\n",
       "      <td>department of neurology and neurological scien...</td>\n",
       "      <td>nature</td>\n",
       "      <td>...</td>\n",
       "      <td>department of neurology and neurological scien...</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>stanford university</td>\n",
       "      <td>2</td>\n",
       "      <td>97.8</td>\n",
       "      <td>2.0</td>\n",
       "      <td>High (75-100)</td>\n",
       "      <td>2</td>\n",
       "      <td>63.751795</td>\n",
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       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44</td>\n",
       "      <td>fungal symbiont transmitted by free-living mic...</td>\n",
       "      <td>the gut mycobiota is crucial for intestinal ho...</td>\n",
       "      <td>nature</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Liao Yun, Gao Iris H, Kusakabe Takato, Lin Woa...</td>\n",
       "      <td>joan and sanford i. weill department of medici...</td>\n",
       "      <td>nature</td>\n",
       "      <td>...</td>\n",
       "      <td>cornell university, cornell university, cornel...</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>cornell university</td>\n",
       "      <td>20</td>\n",
       "      <td>88.7</td>\n",
       "      <td>20.0</td>\n",
       "      <td>High (75-100)</td>\n",
       "      <td>2</td>\n",
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       "      <td>High</td>\n",
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       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>342</td>\n",
       "      <td>study design features increase replicability i...</td>\n",
       "      <td>brain-wide association studies (bwas) are a fu...</td>\n",
       "      <td>nature</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Kang Kaidi, Seidlitz Jakob, Bethlehem Richard ...</td>\n",
       "      <td>department of biostatistics, vanderbilt univer...</td>\n",
       "      <td>nature</td>\n",
       "      <td>...</td>\n",
       "      <td>vanderbilt university medical center, the chil...</td>\n",
       "      <td>brain-wide association studies</td>\n",
       "      <td>vanderbilt university</td>\n",
       "      <td>92</td>\n",
       "      <td>48.5</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Low (0-50)</td>\n",
       "      <td>2</td>\n",
       "      <td>53.128673</td>\n",
       "      <td>High</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>227</td>\n",
       "      <td>integrative mapping of human cd8&lt;sup&gt;+&lt;/sup&gt; t...</td>\n",
       "      <td>cd8&lt;sup&gt;+&lt;/sup&gt; t cells exhibit remarkable phe...</td>\n",
       "      <td>nature methods</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Xue Ziwei, Wu Lize, Tian Ruonan, Gao Bing, Zha...</td>\n",
       "      <td>department of rheumatology and immunology of t...</td>\n",
       "      <td>nature methods</td>\n",
       "      <td>...</td>\n",
       "      <td>zhejiang university, university of edinburgh i...</td>\n",
       "      <td>68 studies</td>\n",
       "      <td>zhejiang university</td>\n",
       "      <td>55</td>\n",
       "      <td>75.3</td>\n",
       "      <td>55.0</td>\n",
       "      <td>High (75-100)</td>\n",
       "      <td>2</td>\n",
       "      <td>51.999730</td>\n",
       "      <td>Medium</td>\n",
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       "    <tr>\n",
       "      <th>472</th>\n",
       "      <td>474</td>\n",
       "      <td>probe set selection for targeted spatial trans...</td>\n",
       "      <td>targeted spatial transcriptomic methods captur...</td>\n",
       "      <td>nature methods</td>\n",
       "      <td>eng</td>\n",
       "      <td>2024</td>\n",
       "      <td>Nov</td>\n",
       "      <td>Kuemmerle Louis B, Luecken Malte D, Firsova Al...</td>\n",
       "      <td>institute of computational biology, helmholtz ...</td>\n",
       "      <td>nature methods</td>\n",
       "      <td>...</td>\n",
       "      <td>institute of computational biology, institute ...</td>\n",
       "      <td>scrinshot</td>\n",
       "      <td>stockholm university</td>\n",
       "      <td>185</td>\n",
       "      <td>49.6</td>\n",
       "      <td>185.0</td>\n",
       "      <td>Low (0-50)</td>\n",
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       "      <td>46.461917</td>\n",
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       "     Unnamed: 0                                              Title  \\\n",
       "231         233  author correction: intravenous and intracrania...   \n",
       "44           44  fungal symbiont transmitted by free-living mic...   \n",
       "340         342  study design features increase replicability i...   \n",
       "225         227  integrative mapping of human cd8<sup>+</sup> t...   \n",
       "472         474  probe set selection for targeted spatial trans...   \n",
       "\n",
       "                                              Abstract         Journal  \\\n",
       "231                                        no abstract          nature   \n",
       "44   the gut mycobiota is crucial for intestinal ho...          nature   \n",
       "340  brain-wide association studies (bwas) are a fu...          nature   \n",
       "225  cd8<sup>+</sup> t cells exhibit remarkable phe...  nature methods   \n",
       "472  targeted spatial transcriptomic methods captur...  nature methods   \n",
       "\n",
       "    Language  Year Month                                            Authors  \\\n",
       "231      eng  2024   Nov  Monje Michelle, Mahdi Jasia, Majzner Robbie, Y...   \n",
       "44       eng  2024   Nov  Liao Yun, Gao Iris H, Kusakabe Takato, Lin Woa...   \n",
       "340      eng  2024   Nov  Kang Kaidi, Seidlitz Jakob, Bethlehem Richard ...   \n",
       "225      eng  2024   Nov  Xue Ziwei, Wu Lize, Tian Ruonan, Gao Bing, Zha...   \n",
       "472      eng  2024   Nov  Kuemmerle Louis B, Luecken Malte D, Firsova Al...   \n",
       "\n",
       "                                          Affiliations            Name  ...  \\\n",
       "231  department of neurology and neurological scien...          nature  ...   \n",
       "44   joan and sanford i. weill department of medici...          nature  ...   \n",
       "340  department of biostatistics, vanderbilt univer...          nature  ...   \n",
       "225  department of rheumatology and immunology of t...  nature methods  ...   \n",
       "472  institute of computational biology, helmholtz ...  nature methods  ...   \n",
       "\n",
       "                                          Universities  \\\n",
       "231  department of neurology and neurological scien...   \n",
       "44   cornell university, cornell university, cornel...   \n",
       "340  vanderbilt university medical center, the chil...   \n",
       "225  zhejiang university, university of edinburgh i...   \n",
       "472  institute of computational biology, institute ...   \n",
       "\n",
       "               Study_Type_Extracted Standardized_University  Rank  \\\n",
       "231                         Unknown     stanford university     2   \n",
       "44                          Unknown      cornell university    20   \n",
       "340  brain-wide association studies   vanderbilt university    92   \n",
       "225                      68 studies     zhejiang university    55   \n",
       "472                       scrinshot    stockholm university   185   \n",
       "\n",
       "     Research_Score Rank_Median Research_Score_Category GMM_Cluster  \\\n",
       "231            97.8         2.0           High (75-100)           2   \n",
       "44             88.7        20.0           High (75-100)           2   \n",
       "340            48.5        92.0              Low (0-50)           2   \n",
       "225            75.3        55.0           High (75-100)           2   \n",
       "472            49.6       185.0              Low (0-50)           2   \n",
       "\n",
       "         Score    Tier  \n",
       "231  63.751795    High  \n",
       "44   61.790934    High  \n",
       "340  53.128673    High  \n",
       "225  51.999730  Medium  \n",
       "472  46.461917  Medium  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Tier'] = pd.qcut(df['Score'], q=3, labels=['Low', 'Medium', 'High'])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5a3ca085-f553-492d-8bc6-aeeaf78dee74",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "# Step 1: Create the subplot \"canvas\"\n",
    "fig = make_subplots(\n",
    "    rows=1, cols=2,  # 1 row, 2 columns\n",
    "    subplot_titles=(\"Journal vs. Score\", \"Journal vs. Tier\")\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "14627be1-bf69-43bb-9ff3-0dcf932e6903",
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_high_tier_abstracts(df, tier_column, abstract_column, output_file):\n",
    "    # Filter for \"High\" tier and exclude rows with \"no abstract\"\n",
    "    high_tier_df = df[(df[tier_column] == 'High') & (df[abstract_column].str.lower() != 'no abstract')]\n",
    "    \n",
    "    # Sort by score and select top 10\n",
    "    top_abstracts = high_tier_df.nlargest(10, 'Score')[abstract_column]\n",
    "    \n",
    "    # Save abstracts to a .txt file\n",
    "    with open(output_file, 'w') as file:\n",
    "        for i, abstract in enumerate(top_abstracts, 1):\n",
    "            file.write(f\"Abstract {i}:\\n{abstract}\\n\\n\")\n",
    "    print(f\"Saved top 10 abstracts to {output_file}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b294352b-b6f9-43fc-ba5f-e4924dc83607",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saved top 10 abstracts to top_10_abstracts.txt\n"
     ]
    }
   ],
   "source": [
    "tier_column = 'Tier'\n",
    "abstract_column = 'Abstract'\n",
    "output_abstracts_file = 'top_10_abstracts.txt'\n",
    "extract_high_tier_abstracts(df, tier_column, abstract_column, output_abstracts_file)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bac4b944-ee3f-46df-a6e7-efe498a09d77",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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