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            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.6/75.6 kB\u001b[0m \u001b[31m4.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m77.9/77.9 kB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m318.9/318.9 kB\u001b[0m \u001b[31m15.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.2/49.2 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m141.9/141.9 kB\u001b[0m \u001b[31m8.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m39.9/39.9 MB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m8.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "!pip install ragas langchain_community langchain_groq sentence_transformers xmltodict -q"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "from google.colab import userdata\n",
        "import pandas as pd\n",
        "from langchain_community.document_loaders import PubMedLoader\n",
        "from langchain_community.embeddings import HuggingFaceBgeEmbeddings\n",
        "from langchain_groq import ChatGroq\n",
        "from ragas.testset.generator import TestsetGenerator\n",
        "from ragas.testset.evolutions import simple, reasoning, multi_context"
      ],
      "metadata": {
        "id": "K-YjxivbEsKh"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "os.environ[\"GROQ_API_KEY\"] = userdata.get('GROQ_API_KEY')\n",
        "data_generation_model = ChatGroq(\n",
        "    model=\"llama3-8b-8192\",\n",
        "    groq_api_key=os.environ[\"GROQ_API_KEY\"],\n",
        ")"
      ],
      "metadata": {
        "id": "hqWzQnOyF6Sc"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "critic_model = ChatGroq(\n",
        "    model=\"llama3-8b-8192\",\n",
        "    groq_api_key=os.environ[\"GROQ_API_KEY\"],\n",
        ")"
      ],
      "metadata": {
        "id": "IVWANrlMGIOU"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_name = \"BAAI/bge-small-en\"\n",
        "model_kwargs = {\"device\": \"cpu\"}\n",
        "encode_kwargs = {\"normalize_embeddings\": True}\n",
        "embeddings = HuggingFaceBgeEmbeddings(\n",
        "    model_name=model_name, model_kwargs=model_kwargs, encode_kwargs=encode_kwargs\n",
        ")"
      ],
      "metadata": {
        "colab": {
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        "id": "9ahsbSnWGVov",
        "outputId": "ea1093ef-205f-4153-9c45-df2f64a008a3"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "modules.json:   0%|          | 0.00/349 [00:00<?, ?B/s]"
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        {
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          "data": {
            "text/plain": [
              "config_sentence_transformers.json:   0%|          | 0.00/124 [00:00<?, ?B/s]"
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "README.md:   0%|          | 0.00/90.8k [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "sentence_bert_config.json:   0%|          | 0.00/52.0 [00:00<?, ?B/s]"
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            "text/plain": [
              "config.json:   0%|          | 0.00/684 [00:00<?, ?B/s]"
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/133M [00:00<?, ?B/s]"
            ],
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        {
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              "tokenizer_config.json:   0%|          | 0.00/366 [00:00<?, ?B/s]"
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          "metadata": {}
        },
        {
          "output_type": "display_data",
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            "text/plain": [
              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "1_Pooling/config.json:   0%|          | 0.00/190 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "c005243e31b2474ea2baa6854d9c655e"
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loader = PubMedLoader(\"cancer\",load_max_docs=5)"
      ],
      "metadata": {
        "id": "sWyd-WZ-GlOf"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "documents = loader.load()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YtFpbwBPGzb4",
        "outputId": "de66aec6-6a8b-4089-fb93-facc7203d532"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Too Many Requests, waiting for 0.20 seconds...\n",
            "Too Many Requests, waiting for 0.40 seconds...\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "generator = TestsetGenerator.from_langchain(\n",
        "    data_generation_model,\n",
        "    critic_model,\n",
        "    embeddings\n",
        ")"
      ],
      "metadata": {
        "id": "YFcW2tz6G50n"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "distributions = {\n",
        "    simple : 0.5,\n",
        "    multi_context : 0.4,\n",
        "    reasoning : 0.1\n",
        "\n",
        "}"
      ],
      "metadata": {
        "id": "mA_8YuUYHKJT"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "testset = generator.generate_with_langchain_docs(documents,5,distributions)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 121,
          "referenced_widgets": [
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            "WARNING:ragas.executor:max retries exceeded for MultiContextEvolution(generator_llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), docstore=InMemoryDocumentStore(splitter=<langchain_text_splitters.base.TokenTextSplitter object at 0x7975f14e2650>, nodes=[Node(metadata={'uid': '39151210', 'Title': 'External validation of the Khorana score for the prediction of venous thromboembolism in cancer patients: A systematic review and meta-analysis.', 'Published': '2024-07-31', 'Copyright Information': 'Copyright © 2024 Elsevier Ltd. All rights reserved.'}, page_content=\"BACKGROUND: Venous thromboembolism is the leading cause of death in cancer patients, second only to tumor progression. The Khorana score is recommended by clinical guidelines for identifying ambulatory cancer patients at high risk of venous thromboembolism during chemotherapy. However, its predictive performance is debated among cancer patients.\\nOBJECTIVES: To map the applicability of the Khorana score in cancer patients and to assess its predictive performance across various cancer types, providing guidance for clinicians and nurses to use it more appropriately.\\nDESIGN: Systematic review and meta-analysis.\\nMETHODS: A comprehensive literature search of the electronic database was first conducted on August 30, 2023, and updated on May 20, 2024. Studies examining the Khorana score's predictive performance (including but not limited to the areas under the curve, C-index, and calibration plot) in cancer patients were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was applied to evaluate the methodological quality of the included studies. Data synthesis was achieved via random-effects meta-analysis using the R studio software. The subgroup analysis was performed according to the study design, clinical setting, cancer type, anti-cancer treatment stage, and country.\\nRESULTS: The review incorporated 67 studies, including 58 observational studies and nine randomized controlled trials. All included studies assessed the Khorana score's discrimination, with the C-index ranging from 0.40 to 0.84. The pooled C-index for randomized controlled trials was 0.61 (95\\u202f% CI 0.51-0.70), while observational studies showed a pooled C-index of 0.59 (95\\u202f% CI 0.57-0.60). Subgroup analyses revealed the pooled C-index for lung cancer, lymphoma, gastrointestinal cancer, and mixed cancer patients as 0.60 (95\\u202f% CI 0.53-0.67), 0.56 (95\\u202f% CI 0.51-0.61), 0.59 (95\\u202f% CI 0.39-0.76), and 0.60 (95\\u202f% CI 0.58-0.61), respectively. Inpatient and outpatient settings had the pooled C-index of 0.60 (95\\u202f% CI 0.58-0.63) and 0.58 (95\\u202f% CI 0.55-0.61), respectively. Calibration was assessed in only four studies. All included studies were identified to have a high risk of bias according to PROBAST.\\nCONCLUSION: The Khorana score has been widely validated in various types of cancer patients; however, it exhibited poor capability (pooled C-index<0.7) in accurately discriminating VTE risk among most types of cancer patients either in inpatient or outpatient settings. The Khorana score should be used with caution, and high-quality studies are needed to further validate its predictive performance.\\nREGISTRATION: The protocol for this study is registered with PROSPERO (registration number: CRD42023470320).\", doc_id='9c84e86d-9230-47a2-9f83-6f9d0b1faa2b', wins=3), Node(metadata={'uid': '39151209', 'Title': 'Phase angle as a potential tool to evaluate chronic inflammatory state and predict quality of life deterioration in women with breast cancer and obesity: A narrative review.', 'Published': '2024-06-26', 'Copyright Information': 'Copyright © 2024 Elsevier Inc. All rights reserved.'}, page_content='The interaction between lifestyle--defined more specifically in health care as the personal exposome--and its implications on obesity and breast cancer development highlights the critical role of body composition and inflammation in these patients. There is clear evidence that the personal and internal exposome triggers biochemical, inflammatory, and metabolic reprogramming, which might favor ectopic lipid accumulation within the body, such as muscles. Additionally, the presence of excessive adipose tissue exacerbates these alterations in the internal exposome, resulting in cell damage and modifying body composition. Understanding the nexus between these lifestyle-induced exposome modifications, such as inflammation, and the resultant changes in body composition is crucial to assess the association with breast cancer progression and treatment responses. Various techniques can be used to evaluate body composition; one of those most used currently is bioelectrical impedance analysis. This analysis provides parameters, including phase angle (PhA), by which cellular health and metabolic activity can be assessed. In addition, PhA is a potential indicator of nutritional status and disease prognosis, as it has been linked to survival and quality of life in patients with cancer. Therefore, PhA might be used in daily oncology practice to implement an accurate nutritional intervention, reducing side effects and complications of oncology management, and improving quality of life during treatment and survival, even in patients with breast cancer with obesity or overweight. The aim of this review is to analyze the existing information on the current application of PhA in patients with breast cancer and its potential use as a tool to assess inflammatory response, identify malnutrition, and predict the deterioration of quality of life so that it could be proposed as an early indicator for nutritional interventions in this group of patients.', doc_id='9de57b32-e0dd-4e1a-88e5-25f748a5380b', wins=2), Node(metadata={'uid': '39151183', 'Title': 'High-Risk Histopathological Features of Retinoblastoma following Primary Enucleation: A Global Study of 1426 Patients from 5 Continents.', 'Published': '2024-08-14', 'Copyright Information': 'Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Opthalmic Communications Society, Inc.'}, page_content='PURPOSE: To evaluate high-risk histopathological features (HRHF) following primary enucleation of eyes with retinoblastoma (RB) and assess the patient outcomes across continents.\\nMETHODS: Retrospective study of 1426 primarily enucleated RB eyes from five continents.\\nRESULTS: Of all, 923 (65%) were from Asia (AS), 27 (2%) from Australia (AUS), 120 (8%) from Europe (EUR), 162 (11%) from North America (NA), and 194 (14%) from South America (SA). Based on the continent (AS vs. AUS vs. EUR vs. NA vs. SA), the histopathology features included massive choroidal invasion (31% vs. 7% vs. 13% vs. 19% vs. 27%, p=0.001), post-laminar optic nerve invasion (27% vs. 0% vs. 16% vs. 21% vs. 19%, p=0.0006), scleral infiltration (5% vs. 0% vs. 4% vs. 2% vs. 7%, p=0.13), and microscopic extrascleral infiltration (4% vs. 0% vs. <1% vs. <1% vs. 4%, p=0.68). Adjuvant chemotherapy with/without orbital radiotherapy was given in 761 (53%) patients. Based on Kaplan-Meier estimates in different continents (AS vs. AUS vs. EUR vs. NA vs. SA), the 6-year risk of orbital tumor recurrence was 5% vs. 2% vs. 0% vs. 0% vs. 12% (p<0.001), systemic metastasis was reported in 8% vs. 5% vs. 2% vs. 0% vs. 13% (p=0.001), and death in 10% vs. 3% vs. 2% vs. 0% vs. 11% (p<0.001) patients.\\nCONCLUSION: There is a wide variation in the infiltrative histopathology features of RB across continents, resulting in variable outcomes. SA and AS had a higher risk of orbital tumor recurrence, systemic metastasis, and death compared to AUS, EUR, and NA.', doc_id='7ca56bd7-2e65-4fae-a436-5f2ddb39855d', wins=3), Node(metadata={'uid': '39151159', 'Title': 'A Theory and Evidence-Informed e-Cycling Intervention for Individuals Diagnosed With Cancer: Development Study.', 'Published': '2024-08-16', 'Copyright Information': '©Jessica E Bourne, Paul Kelly, Miranda E G Armstrong. Originally published in JMIR Cancer (https://cancer.jmir.org), 16.08.2024.'}, page_content='BACKGROUND: Physical activity engagement following a cancer diagnosis is positively associated with survival, reduced risk of disease recurrence, and reduced cancer-specific and all-cause mortality. However, rates of physical activity engagement are low among individuals diagnosed with and being treated for breast cancer or prostate cancer.\\nOBJECTIVE: The purpose of this study was to describe the systematic process of developing an e-cycling intervention aimed at increasing physical activity among individuals living with prostate cancer or breast cancer and outline the key components to be implemented.\\nMETHODS: The Medical Research Council guidance for developing complex interventions and the Behaviour Change Wheel were used to guide intervention development. Information was gathered from the literature and through discussions with end users to understand factors influencing e-cycling. These factors were mapped onto the Theoretical Domains Framework to identify potential mechanisms of action. Behavior change techniques were selected from theory and evidence to develop intervention content. Interested parties, including cycling instructors, end users, and behavior change experts, reviewed and refined the intervention.\\nRESULTS: Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework. A total of 23 behavior change techniques were selected to target these domains over 4 one-to-one e-cycling sessions delivered by trained cycling instructors in the community. Cycling instructors were provided a 3-hour classroom training session on delivering the intervention and a 3-hour practical session with feedback. The outcome of this work is a theory and evidence-informed intervention aimed at promoting e-cycling behavior among individuals being treated for breast cancer or prostate cancer, which is currently being implemented and evaluated.\\nCONCLUSIONS: Transparent intervention development and reporting of content is important for comprehensively examining intervention implementation. The implementation of this intervention package is currently being evaluated in a pilot randomized controlled trial. If the intervention is found to be effective and the content and delivery are acceptable, this intervention will form a basis for the development of e-cycling interventions in other survivors of cancer.\\nTRIAL REGISTRATION: ISRCTN Registry ISRCTN39112034 https://www.isrctn.com/ISRCTN39112034; and IRSCTN Registry ISRCTN42852156; https://www.isrctn.com/ISRCTN42852156.', doc_id='9e0a0939-3745-467d-af19-4c2c896c7f21', wins=4), Node(metadata={'uid': '39151149', 'Title': 'The Importance of Digital Lung Tomosynthesis in Overcoming Computed-Tomography-to-Body Divergence During Bronchoscopic Biopsies of Peripheral Lung Nodules.', 'Published': '2024-08-16', 'Copyright Information': ''}, page_content='The advent of robotic bronchoscopy coupled with electromagnetic navigation bronchoscopy (EMN) and shape-sensing technology have increased diagnostic yields for peripheral pulmonary nodules compared to traditional bronchoscopy. Yet, diagnostic yields from these bronchoscopic platforms still fall short of where they should be. This shortfall is in large part due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD). Digital lung tomosynthesis (DLT) is an advanced imaging modality that helps overcome CTBD during bronchoscopic biopsies of lung nodules. DLT is a quasi-3D imaging technique, which reconstructs tomographic images of the lung from a series of 2D fluoroscopic projection images. These images can be acquired either using a digital flat panel fluoroscopy machine or a fluoroscopy machine with a more traditional image-intensifier present in most standard bronchoscopy suites. This review aims to explain the mechanisms of both CTBD and DLT to help diagnose early-stage lung cancer more effectively.', doc_id='e11630fc-2ac1-4b4c-a688-572c3f2c9314', wins=4)], node_embeddings_list=[[-0.05047006905078888, -0.00924971979111433, -0.00739614712074399, 0.02004431001842022, 0.011683718301355839, 0.009978670626878738, 0.030250925570726395, 0.0163064394146204, -0.0038162439595907927, 0.006354234647005796, 0.012460996396839619, -0.042679011821746826, -0.0026807961985468864, 0.03216209262609482, -0.041874513030052185, -0.030076732859015465, 0.013745746575295925, 0.0013136559864506125, -0.020289437845349312, 0.03476591035723686, -0.021849509328603745, 0.0075844088569283485, 0.003509526839479804, -0.02352146990597248, 0.03303378075361252, 0.0015063644386827946, -0.0027288079727441072, -0.04188613221049309, -0.04691840708255768, -0.22518204152584076, -0.014538468793034554, -0.051185205578804016, 0.024983318522572517, -0.002390797482803464, -0.02867944911122322, 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0.05768139660358429, 0.06953182816505432]], node_map={'9c84e86d-9230-47a2-9f83-6f9d0b1faa2b': Node(metadata={'uid': '39151210', 'Title': 'External validation of the Khorana score for the prediction of venous thromboembolism in cancer patients: A systematic review and meta-analysis.', 'Published': '2024-07-31', 'Copyright Information': 'Copyright © 2024 Elsevier Ltd. All rights reserved.'}, page_content=\"BACKGROUND: Venous thromboembolism is the leading cause of death in cancer patients, second only to tumor progression. The Khorana score is recommended by clinical guidelines for identifying ambulatory cancer patients at high risk of venous thromboembolism during chemotherapy. However, its predictive performance is debated among cancer patients.\\nOBJECTIVES: To map the applicability of the Khorana score in cancer patients and to assess its predictive performance across various cancer types, providing guidance for clinicians and nurses to use it more appropriately.\\nDESIGN: Systematic review and meta-analysis.\\nMETHODS: A comprehensive literature search of the electronic database was first conducted on August 30, 2023, and updated on May 20, 2024. Studies examining the Khorana score's predictive performance (including but not limited to the areas under the curve, C-index, and calibration plot) in cancer patients were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was applied to evaluate the methodological quality of the included studies. Data synthesis was achieved via random-effects meta-analysis using the R studio software. The subgroup analysis was performed according to the study design, clinical setting, cancer type, anti-cancer treatment stage, and country.\\nRESULTS: The review incorporated 67 studies, including 58 observational studies and nine randomized controlled trials. All included studies assessed the Khorana score's discrimination, with the C-index ranging from 0.40 to 0.84. The pooled C-index for randomized controlled trials was 0.61 (95\\u202f% CI 0.51-0.70), while observational studies showed a pooled C-index of 0.59 (95\\u202f% CI 0.57-0.60). Subgroup analyses revealed the pooled C-index for lung cancer, lymphoma, gastrointestinal cancer, and mixed cancer patients as 0.60 (95\\u202f% CI 0.53-0.67), 0.56 (95\\u202f% CI 0.51-0.61), 0.59 (95\\u202f% CI 0.39-0.76), and 0.60 (95\\u202f% CI 0.58-0.61), respectively. Inpatient and outpatient settings had the pooled C-index of 0.60 (95\\u202f% CI 0.58-0.63) and 0.58 (95\\u202f% CI 0.55-0.61), respectively. Calibration was assessed in only four studies. All included studies were identified to have a high risk of bias according to PROBAST.\\nCONCLUSION: The Khorana score has been widely validated in various types of cancer patients; however, it exhibited poor capability (pooled C-index<0.7) in accurately discriminating VTE risk among most types of cancer patients either in inpatient or outpatient settings. The Khorana score should be used with caution, and high-quality studies are needed to further validate its predictive performance.\\nREGISTRATION: The protocol for this study is registered with PROSPERO (registration number: CRD42023470320).\", doc_id='9c84e86d-9230-47a2-9f83-6f9d0b1faa2b', wins=3), '9de57b32-e0dd-4e1a-88e5-25f748a5380b': Node(metadata={'uid': '39151209', 'Title': 'Phase angle as a potential tool to evaluate chronic inflammatory state and predict quality of life deterioration in women with breast cancer and obesity: A narrative review.', 'Published': '2024-06-26', 'Copyright Information': 'Copyright © 2024 Elsevier Inc. All rights reserved.'}, page_content='The interaction between lifestyle--defined more specifically in health care as the personal exposome--and its implications on obesity and breast cancer development highlights the critical role of body composition and inflammation in these patients. There is clear evidence that the personal and internal exposome triggers biochemical, inflammatory, and metabolic reprogramming, which might favor ectopic lipid accumulation within the body, such as muscles. Additionally, the presence of excessive adipose tissue exacerbates these alterations in the internal exposome, resulting in cell damage and modifying body composition. Understanding the nexus between these lifestyle-induced exposome modifications, such as inflammation, and the resultant changes in body composition is crucial to assess the association with breast cancer progression and treatment responses. Various techniques can be used to evaluate body composition; one of those most used currently is bioelectrical impedance analysis. This analysis provides parameters, including phase angle (PhA), by which cellular health and metabolic activity can be assessed. In addition, PhA is a potential indicator of nutritional status and disease prognosis, as it has been linked to survival and quality of life in patients with cancer. Therefore, PhA might be used in daily oncology practice to implement an accurate nutritional intervention, reducing side effects and complications of oncology management, and improving quality of life during treatment and survival, even in patients with breast cancer with obesity or overweight. The aim of this review is to analyze the existing information on the current application of PhA in patients with breast cancer and its potential use as a tool to assess inflammatory response, identify malnutrition, and predict the deterioration of quality of life so that it could be proposed as an early indicator for nutritional interventions in this group of patients.', doc_id='9de57b32-e0dd-4e1a-88e5-25f748a5380b', wins=2), '7ca56bd7-2e65-4fae-a436-5f2ddb39855d': Node(metadata={'uid': '39151183', 'Title': 'High-Risk Histopathological Features of Retinoblastoma following Primary Enucleation: A Global Study of 1426 Patients from 5 Continents.', 'Published': '2024-08-14', 'Copyright Information': 'Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Opthalmic Communications Society, Inc.'}, page_content='PURPOSE: To evaluate high-risk histopathological features (HRHF) following primary enucleation of eyes with retinoblastoma (RB) and assess the patient outcomes across continents.\\nMETHODS: Retrospective study of 1426 primarily enucleated RB eyes from five continents.\\nRESULTS: Of all, 923 (65%) were from Asia (AS), 27 (2%) from Australia (AUS), 120 (8%) from Europe (EUR), 162 (11%) from North America (NA), and 194 (14%) from South America (SA). Based on the continent (AS vs. AUS vs. EUR vs. NA vs. SA), the histopathology features included massive choroidal invasion (31% vs. 7% vs. 13% vs. 19% vs. 27%, p=0.001), post-laminar optic nerve invasion (27% vs. 0% vs. 16% vs. 21% vs. 19%, p=0.0006), scleral infiltration (5% vs. 0% vs. 4% vs. 2% vs. 7%, p=0.13), and microscopic extrascleral infiltration (4% vs. 0% vs. <1% vs. <1% vs. 4%, p=0.68). Adjuvant chemotherapy with/without orbital radiotherapy was given in 761 (53%) patients. Based on Kaplan-Meier estimates in different continents (AS vs. AUS vs. EUR vs. NA vs. SA), the 6-year risk of orbital tumor recurrence was 5% vs. 2% vs. 0% vs. 0% vs. 12% (p<0.001), systemic metastasis was reported in 8% vs. 5% vs. 2% vs. 0% vs. 13% (p=0.001), and death in 10% vs. 3% vs. 2% vs. 0% vs. 11% (p<0.001) patients.\\nCONCLUSION: There is a wide variation in the infiltrative histopathology features of RB across continents, resulting in variable outcomes. SA and AS had a higher risk of orbital tumor recurrence, systemic metastasis, and death compared to AUS, EUR, and NA.', doc_id='7ca56bd7-2e65-4fae-a436-5f2ddb39855d', wins=3), '9e0a0939-3745-467d-af19-4c2c896c7f21': Node(metadata={'uid': '39151159', 'Title': 'A Theory and Evidence-Informed e-Cycling Intervention for Individuals Diagnosed With Cancer: Development Study.', 'Published': '2024-08-16', 'Copyright Information': '©Jessica E Bourne, Paul Kelly, Miranda E G Armstrong. Originally published in JMIR Cancer (https://cancer.jmir.org), 16.08.2024.'}, page_content='BACKGROUND: Physical activity engagement following a cancer diagnosis is positively associated with survival, reduced risk of disease recurrence, and reduced cancer-specific and all-cause mortality. However, rates of physical activity engagement are low among individuals diagnosed with and being treated for breast cancer or prostate cancer.\\nOBJECTIVE: The purpose of this study was to describe the systematic process of developing an e-cycling intervention aimed at increasing physical activity among individuals living with prostate cancer or breast cancer and outline the key components to be implemented.\\nMETHODS: The Medical Research Council guidance for developing complex interventions and the Behaviour Change Wheel were used to guide intervention development. Information was gathered from the literature and through discussions with end users to understand factors influencing e-cycling. These factors were mapped onto the Theoretical Domains Framework to identify potential mechanisms of action. Behavior change techniques were selected from theory and evidence to develop intervention content. Interested parties, including cycling instructors, end users, and behavior change experts, reviewed and refined the intervention.\\nRESULTS: Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework. A total of 23 behavior change techniques were selected to target these domains over 4 one-to-one e-cycling sessions delivered by trained cycling instructors in the community. Cycling instructors were provided a 3-hour classroom training session on delivering the intervention and a 3-hour practical session with feedback. The outcome of this work is a theory and evidence-informed intervention aimed at promoting e-cycling behavior among individuals being treated for breast cancer or prostate cancer, which is currently being implemented and evaluated.\\nCONCLUSIONS: Transparent intervention development and reporting of content is important for comprehensively examining intervention implementation. The implementation of this intervention package is currently being evaluated in a pilot randomized controlled trial. If the intervention is found to be effective and the content and delivery are acceptable, this intervention will form a basis for the development of e-cycling interventions in other survivors of cancer.\\nTRIAL REGISTRATION: ISRCTN Registry ISRCTN39112034 https://www.isrctn.com/ISRCTN39112034; and IRSCTN Registry ISRCTN42852156; https://www.isrctn.com/ISRCTN42852156.', doc_id='9e0a0939-3745-467d-af19-4c2c896c7f21', wins=4), 'e11630fc-2ac1-4b4c-a688-572c3f2c9314': Node(metadata={'uid': '39151149', 'Title': 'The Importance of Digital Lung Tomosynthesis in Overcoming Computed-Tomography-to-Body Divergence During Bronchoscopic Biopsies of Peripheral Lung Nodules.', 'Published': '2024-08-16', 'Copyright Information': ''}, page_content='The advent of robotic bronchoscopy coupled with electromagnetic navigation bronchoscopy (EMN) and shape-sensing technology have increased diagnostic yields for peripheral pulmonary nodules compared to traditional bronchoscopy. Yet, diagnostic yields from these bronchoscopic platforms still fall short of where they should be. This shortfall is in large part due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD). Digital lung tomosynthesis (DLT) is an advanced imaging modality that helps overcome CTBD during bronchoscopic biopsies of lung nodules. DLT is a quasi-3D imaging technique, which reconstructs tomographic images of the lung from a series of 2D fluoroscopic projection images. These images can be acquired either using a digital flat panel fluoroscopy machine or a fluoroscopy machine with a more traditional image-intensifier present in most standard bronchoscopy suites. This review aims to explain the mechanisms of both CTBD and DLT to help diagnose early-stage lung cancer more effectively.', doc_id='e11630fc-2ac1-4b4c-a688-572c3f2c9314', wins=4)}, run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), node_filter=NodeFilter(llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), threshold=1.5, context_scoring_prompt=Prompt(name='score_context', instruction='\\n    Given a context, perform the following task and output the answer in VALID JSON format: Assess the provided context and assign a numerical score of 1 (Low), 2 (Medium), or 3 (High) for each of the following criteria in your JSON response:\\n\\nclarity: Evaluate the precision and understandability of the information presented. High scores (3) are reserved for contexts that are both precise in their information and easy to understand. Low scores (1) are for contexts where the information is vague or hard to comprehend.\\ndepth: Determine the level of detailed examination and the inclusion of innovative insights within the context. A high score indicates a comprehensive and insightful analysis, while a low score suggests a superficial treatment of the topic.\\nstructure: Assess how well the content is organized and whether it flows logically. High scores are awarded to contexts that demonstrate coherent organization and logical progression, whereas low scores indicate a lack of structure or clarity in progression.\\nrelevance: Judge the pertinence of the content to the main topic, awarding high scores to contexts tightly focused on the subject without unnecessary digressions, and low scores to those that are cluttered with irrelevant information.\\nStructure your JSON output to reflect these criteria as keys with their corresponding scores as values\\n    ', output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"clarity\": {\"title\": \"Clarity\", \"type\": \"integer\"}, \"depth\": {\"title\": \"Depth\", \"type\": \"integer\"}, \"structure\": {\"title\": \"Structure\", \"type\": \"integer\"}, \"relevance\": {\"title\": \"Relevance\", \"type\": \"integer\"}}, \"required\": [\"clarity\", \"depth\", \"structure\", \"relevance\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'context': 'The Pythagorean theorem is a fundamental principle in geometry. It states that in a right-angled triangle, the square of the length of the hypotenuse (the side opposite the right angle) is equal to the sum of the squares of the lengths of the other two sides. This can be written as a^2 + b^2 = c^2 where c represents the length of the hypotenuse, and a and b represent the lengths of the other two sides.', 'output': {'clarity': 3, 'depth': 1, 'structure': 3, 'relevance': 3}}, {'context': 'Albert Einstein (14 March 1879 - 18 April 1955) was a German-born theoretical physicist who is widely held to be one of the greatest and most influential scientists of all time.', 'output': {'clarity': 3, 'depth': 2, 'structure': 3, 'relevance': 3}}, {'context': \"I love chocolate. It's really tasty. Oh, and by the way, the earth orbits the sun, not the other way around. Also, my favorite color is blue.\", 'output': {'clarity': 2, 'depth': 1, 'structure': 1, 'relevance': 1}}], input_keys=['context'], output_key='output', output_type='json', language='english')), question_filter=QuestionFilter(llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), filter_question_prompt=Prompt(name='filter_question', instruction='\\nAsses the given question for clarity and answerability given enough domain knowledge, consider the following criteria:\\n1.Independence: Can the question be understood and answered without needing additional context or access to external references not provided within the question itself? Questions should be self-contained, meaning they do not rely on specific documents, tables, or prior knowledge not shared within the question.\\n2.Clear Intent: Is it clear what type of answer or information the question seeks? The question should convey its purpose without ambiguity, allowing for a direct and relevant response.\\nBased on these criteria, assign a verdict of \"1\" if a question is specific, independent, and has a clear intent, making it understandable and answerable based on the details provided. Assign \"0\" if it fails to meet one or more of these criteria due to vagueness, reliance on external references, or ambiguity in intent.\\nProvide feedback and a verdict in JSON format, including suggestions for improvement if the question is deemed unclear. Highlight aspects of the question that contribute to its clarity or lack thereof, and offer advice on how it could be reframed or detailed for better understanding and answerability.\\n', output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"feedback\": {\"title\": \"Feedback\", \"type\": \"string\"}, \"verdict\": {\"title\": \"Verdict\", \"type\": \"integer\"}}, \"required\": [\"feedback\", \"verdict\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'question': 'What is the discovery about space?', 'output': {'feedback': \"The question is too vague and broad, asking for a 'discovery about space' without specifying any particular aspect, time frame, or context of interest. This could refer to a wide range of topics, from the discovery of new celestial bodies to advancements in space travel technology. To improve clarity and answerability, the question could specify the type of discovery (e.g., astronomical, technological), the time frame (e.g., recent, historical), or the context (e.g., within a specific research study or space mission).\", 'verdict': 0}}, {'question': \"How does ALMA-13B-R perform compared to other translation models in the WMT'23 study, based on the results in context1 and context2?\", 'output': {'feedback': \"This question asks for a comparison of the ALMA-13B-R model's performance against other translation models within the WMT'23 study, specifically referring to results in 'context1' and 'context2'. While it clearly specifies the model of interest (ALMA-13B-R) and the study (WMT'23), it assumes access to and understanding of 'context1' and 'context2' without explaining what these contexts entail. This makes the question unclear for those not familiar with the WMT'23 study or these specific contexts. To improve clarity and answerability for a broader audience, the question could benefit from defining or describing 'context1' and 'context2' or explaining the criteria used for comparison in these contexts.\", 'verdict': 0}}, {'question': 'How do KIWI-XXL and XCOMET compare to the gold standard references in Table 1 in terms of evaluation scores, translation model performance, and success rate in surpassing the references?', 'output': {'feedback': \"The question requests a comparison between KIWI-XXL and XCOMET models and gold standard references in 'Table 1', focusing on evaluation scores, translation model performance, and success rates in surpassing the references. It specifies the models and criteria for comparison, making the intent clear. However, the question assumes access to 'Table 1' without providing its content or context, making it unclear for those without direct access to the source material. To be clearer and more answerable for a general audience, the question could include a brief description of the content or key findings of 'Table 1', or alternatively, frame the question in a way that does not rely on specific, unpublished documents.\", 'verdict': 0}}, {'question': 'What is the configuration of UL2 training objective in OpenMoE and why is it a better choice for pre-training?', 'output': {'feedback': 'The question asks for the configuration of the UL2 training objective within the OpenMoE framework and the rationale behind its suitability for pre-training. It is clear in specifying the topic of interest (UL2 training objective, OpenMoE) and seeks detailed information on both the configuration and the reasons for its effectiveness in pre-training. However, the question might be challenging for those unfamiliar with the specific terminology or the context of OpenMoE and UL2. For broader clarity and answerability, it would be helpful if the question included a brief explanation or context about OpenMoE and the UL2 training objective, or clarified the aspects of pre-training effectiveness it refers to (e.g., efficiency, accuracy, generalization).', 'verdict': 1}}, {'question': 'What is the detailed configuration of the UL2 training objective in OpenMoE, based on the provided context?', 'output': {'feedback': \"The question seeks detailed information on the UL2 training objective's configuration within the OpenMoE framework, mentioning 'the provided context' without actually including or describing this context within the query. This makes the question unclear for those who do not have access to the unspecified context. For the question to be clear and answerable, it needs to either include the relevant context directly within the question or be framed in a way that does not require external information. Detailing the specific aspects of the configuration of interest (e.g., loss functions, data augmentation techniques) could also help clarify the query.\", 'verdict': 0}}], input_keys=['question'], output_key='output', output_type='json', language='english')), question_answer_prompt=Prompt(name='answer_formulate', instruction=\"Answer the question using the information from the given context. Output verdict as '1' if answer is present '-1' if answer is not present in the context.\", output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"answer\": {\"title\": \"Answer\", \"type\": \"string\"}, \"verdict\": {\"title\": \"Verdict\", \"type\": \"integer\"}}, \"required\": [\"answer\", \"verdict\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'context': 'Climate change is significantly influenced by human activities, notably the emission of greenhouse gases from burning fossil fuels. The increased greenhouse gas concentration in the atmosphere traps more heat, leading to global warming and changes in weather patterns.', 'question': 'How do human activities contribute to climate change?', 'answer': {'answer': 'Human activities contribute to climate change primarily through the emission of greenhouse gases from burning fossil fuels. These emissions increase the concentration of greenhouse gases in the atmosphere, which traps more heat and leads to global warming and altered weather patterns.', 'verdict': 1}}, {'context': 'The concept of artificial intelligence (AI) has evolved over time, but it fundamentally refers to machines designed to mimic human cognitive functions. AI can learn, reason, perceive, and, in some instances, react like humans, making it pivotal in fields ranging from healthcare to autonomous vehicles.', 'question': 'What are the key capabilities of artificial intelligence?', 'answer': {'answer': 'Artificial intelligence is designed to mimic human cognitive functions, with key capabilities including learning, reasoning, perception, and reacting to the environment in a manner similar to humans. These capabilities make AI pivotal in various fields, including healthcare and autonomous driving.', 'verdict': 1}}, {'context': 'The novel \"Pride and Prejudice\" by Jane Austen revolves around the character Elizabeth Bennet and her family. The story is set in the 19th century in rural England and deals with issues of marriage, morality, and misconceptions.', 'question': \"What year was 'Pride and Prejudice' published?\", 'answer': {'answer': 'The answer to given question is not present in context', 'verdict': -1}}], input_keys=['context', 'question'], output_key='answer', output_type='json', language='english'), find_relevant_context_prompt=Prompt(name='find_relevant_context', instruction='Given a question and set of contexts, find the most relevant contexts to answer the question.', output_format_instruction='', examples=[{'question': 'What is the capital of France?', 'contexts': ['1. France is a country in Western Europe. It has several cities, including Paris, Lyon, and Marseille. Paris is not only known for its cultural landmarks like the Eiffel Tower and the Louvre Museum but also as the administrative center.', '2. The capital of France is Paris. It is also the most populous city in France, with a population of over 2 million people. Paris is known for its cultural landmarks like the Eiffel Tower and the Louvre Museum.', '3. Paris is the capital of France. It is also the most populous city in France, with a population of over 2 million people. Paris is known for its cultural landmarks like the Eiffel Tower and the Louvre Museum.'], 'output': {'relevant_contexts': [1, 2]}}, {'question': 'How does caffeine affect the body and what are its common sources?', 'contexts': ['1. Caffeine is a central nervous system stimulant. It can temporarily ward off drowsiness and restore alertness. It primarily affects the brain, where it alters the function of neurotransmitters.', '2. Regular physical activity is essential for maintaining good health. It can help control weight, combat health conditions, boost energy, and promote better sleep.', '3. Common sources of caffeine include coffee, tea, cola, and energy drinks. These beverages are consumed worldwide and are known for providing a quick boost of energy.'], 'output': {'relevant_contexts': [1, 2]}}], input_keys=['question', 'contexts'], output_key='output', output_type='json', language='english'), rewrite_invalid_question_prompt=Prompt(name='rewrite_question', instruction='Given a context, question and feedback, rewrite the question to improve its clarity and answerability based on the feedback provided.', output_format_instruction='', examples=[{'context': \"The Eiffel Tower was constructed using iron and was originally intended as a temporary exhibit for the 1889 World's Fair held in Paris. Despite its initial temporary purpose, the Eiffel Tower quickly became a symbol of Parisian ingenuity and an iconic landmark of the city, attracting millions of visitors each year. The tower's design, created by Gustave Eiffel, was initially met with criticism from some French artists and intellectuals, but it has since been celebrated as a masterpiece of structural engineering and architectural design.\", 'question': 'Who created the design for the Tower?', 'feedback': \"The question asks about the creator of the design for 'the Tower', but it does not specify which tower it refers to. There are many towers worldwide, and without specifying the exact tower, the question is unclear and unanswerable. To improve the question, it should include the name or a clear description of the specific tower in question.\", 'output': 'Who created the design for the Eiffel Tower?'}, {'context': \"'Exploring Zero-Shot Learning in Neural Networks' was published by Smith and Lee in 2021, focusing on the application of zero-shot learning techniques in artificial intelligence.\", 'question': 'What datasets were used for the zero-shot evaluations in this study?', 'feedback': \"The question asks about the datasets used for zero-shot evaluations in 'this study', without specifying or providing any details about the study in question. This makes the question unclear for those who do not have access to or knowledge of the specific study. To improve clarity and answerability, the question should specify the study it refers to, or provide enough context about the study for the question to be understood and answered independently.\", 'output': 'What datasets were used for the zero-shot evaluations Exploring Zero-Shot Learning in Neural Networks paper?'}], input_keys=['context', 'question', 'feedback'], output_key='output', output_type='str', language='english'), max_tries=5, is_async=True, compress_question_prompt=Prompt(name='compress_question', instruction='Rewrite the following question to make it more indirect and shorter while retaining the essence of the original question.\\n    The goal is to create a question that conveys the same meaning but in a less direct manner. The rewritten question should shorter so use abbreviation wherever possible.', output_format_instruction='', examples=[{'question': 'What is the distance between the Earth and the Moon?', 'output': 'How far is the Moon from Earth?'}, {'question': 'What ingredients are required to bake a chocolate cake?', 'output': \"What's needed for a chocolate cake?\"}], input_keys=['question'], output_key='output', output_type='str', language='english'), multi_context_question_prompt=Prompt(name='multi_context_question', instruction=\"\\n    The task is to rewrite and complicate the given question in a way that answering it requires information derived from both context1 and context2. \\n    Follow the rules given below while rewriting the question.\\n        1. The rewritten question should not be very long. Use abbreviation wherever possible.\\n        2. The rewritten question must be reasonable and must be understood and responded by humans.\\n        3. The rewritten question must be fully answerable from information present in context1 and context2. \\n        4. Read and understand both contexts and rewrite the question so that answering requires insight from both context1 and context2.\\n        5. phrases like 'based on the provided context','according to the context?',etc are not allowed to appear in the question.\", output_format_instruction='', examples=[{'question': 'What process turns plants green?', 'context1': 'Chlorophyll is the pigment that gives plants their green color and helps them photosynthesize.', 'context2': 'Photosynthesis in plants typically occurs in the leaves where chloroplasts are concentrated.', 'output': 'In which plant structures does the pigment responsible for their verdancy facilitate energy production?'}, {'question': 'How do you calculate the area of a rectangle?', 'context1': \"The area of a shape is calculated based on the shape's dimensions. For rectangles, this involves multiplying the length and width.\", 'context2': 'Rectangles have four sides with opposite sides being equal in length. They are a type of quadrilateral.', 'output': \"What multiplication involving equal opposites yields a quadrilateral's area?\"}], input_keys=['question', 'context1', 'context2'], output_key='output', output_type='str', language='english'))\n",
            "WARNING:ragas.executor:max retries exceeded for MultiContextEvolution(generator_llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), docstore=InMemoryDocumentStore(splitter=<langchain_text_splitters.base.TokenTextSplitter object at 0x7975f14e2650>, nodes=[Node(metadata={'uid': '39151210', 'Title': 'External validation of the Khorana score for the prediction of venous thromboembolism in cancer patients: A systematic review and meta-analysis.', 'Published': '2024-07-31', 'Copyright Information': 'Copyright © 2024 Elsevier Ltd. All rights reserved.'}, page_content=\"BACKGROUND: Venous thromboembolism is the leading cause of death in cancer patients, second only to tumor progression. The Khorana score is recommended by clinical guidelines for identifying ambulatory cancer patients at high risk of venous thromboembolism during chemotherapy. However, its predictive performance is debated among cancer patients.\\nOBJECTIVES: To map the applicability of the Khorana score in cancer patients and to assess its predictive performance across various cancer types, providing guidance for clinicians and nurses to use it more appropriately.\\nDESIGN: Systematic review and meta-analysis.\\nMETHODS: A comprehensive literature search of the electronic database was first conducted on August 30, 2023, and updated on May 20, 2024. Studies examining the Khorana score's predictive performance (including but not limited to the areas under the curve, C-index, and calibration plot) in cancer patients were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was applied to evaluate the methodological quality of the included studies. Data synthesis was achieved via random-effects meta-analysis using the R studio software. The subgroup analysis was performed according to the study design, clinical setting, cancer type, anti-cancer treatment stage, and country.\\nRESULTS: The review incorporated 67 studies, including 58 observational studies and nine randomized controlled trials. All included studies assessed the Khorana score's discrimination, with the C-index ranging from 0.40 to 0.84. The pooled C-index for randomized controlled trials was 0.61 (95\\u202f% CI 0.51-0.70), while observational studies showed a pooled C-index of 0.59 (95\\u202f% CI 0.57-0.60). Subgroup analyses revealed the pooled C-index for lung cancer, lymphoma, gastrointestinal cancer, and mixed cancer patients as 0.60 (95\\u202f% CI 0.53-0.67), 0.56 (95\\u202f% CI 0.51-0.61), 0.59 (95\\u202f% CI 0.39-0.76), and 0.60 (95\\u202f% CI 0.58-0.61), respectively. Inpatient and outpatient settings had the pooled C-index of 0.60 (95\\u202f% CI 0.58-0.63) and 0.58 (95\\u202f% CI 0.55-0.61), respectively. Calibration was assessed in only four studies. All included studies were identified to have a high risk of bias according to PROBAST.\\nCONCLUSION: The Khorana score has been widely validated in various types of cancer patients; however, it exhibited poor capability (pooled C-index<0.7) in accurately discriminating VTE risk among most types of cancer patients either in inpatient or outpatient settings. The Khorana score should be used with caution, and high-quality studies are needed to further validate its predictive performance.\\nREGISTRATION: The protocol for this study is registered with PROSPERO (registration number: CRD42023470320).\", doc_id='9c84e86d-9230-47a2-9f83-6f9d0b1faa2b', wins=3), Node(metadata={'uid': '39151209', 'Title': 'Phase angle as a potential tool to evaluate chronic inflammatory state and predict quality of life deterioration in women with breast cancer and obesity: A narrative review.', 'Published': '2024-06-26', 'Copyright Information': 'Copyright © 2024 Elsevier Inc. All rights reserved.'}, page_content='The interaction between lifestyle--defined more specifically in health care as the personal exposome--and its implications on obesity and breast cancer development highlights the critical role of body composition and inflammation in these patients. There is clear evidence that the personal and internal exposome triggers biochemical, inflammatory, and metabolic reprogramming, which might favor ectopic lipid accumulation within the body, such as muscles. Additionally, the presence of excessive adipose tissue exacerbates these alterations in the internal exposome, resulting in cell damage and modifying body composition. Understanding the nexus between these lifestyle-induced exposome modifications, such as inflammation, and the resultant changes in body composition is crucial to assess the association with breast cancer progression and treatment responses. Various techniques can be used to evaluate body composition; one of those most used currently is bioelectrical impedance analysis. This analysis provides parameters, including phase angle (PhA), by which cellular health and metabolic activity can be assessed. In addition, PhA is a potential indicator of nutritional status and disease prognosis, as it has been linked to survival and quality of life in patients with cancer. Therefore, PhA might be used in daily oncology practice to implement an accurate nutritional intervention, reducing side effects and complications of oncology management, and improving quality of life during treatment and survival, even in patients with breast cancer with obesity or overweight. The aim of this review is to analyze the existing information on the current application of PhA in patients with breast cancer and its potential use as a tool to assess inflammatory response, identify malnutrition, and predict the deterioration of quality of life so that it could be proposed as an early indicator for nutritional interventions in this group of patients.', doc_id='9de57b32-e0dd-4e1a-88e5-25f748a5380b', wins=2), Node(metadata={'uid': '39151183', 'Title': 'High-Risk Histopathological Features of Retinoblastoma following Primary Enucleation: A Global Study of 1426 Patients from 5 Continents.', 'Published': '2024-08-14', 'Copyright Information': 'Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Opthalmic Communications Society, Inc.'}, page_content='PURPOSE: To evaluate high-risk histopathological features (HRHF) following primary enucleation of eyes with retinoblastoma (RB) and assess the patient outcomes across continents.\\nMETHODS: Retrospective study of 1426 primarily enucleated RB eyes from five continents.\\nRESULTS: Of all, 923 (65%) were from Asia (AS), 27 (2%) from Australia (AUS), 120 (8%) from Europe (EUR), 162 (11%) from North America (NA), and 194 (14%) from South America (SA). Based on the continent (AS vs. AUS vs. EUR vs. NA vs. SA), the histopathology features included massive choroidal invasion (31% vs. 7% vs. 13% vs. 19% vs. 27%, p=0.001), post-laminar optic nerve invasion (27% vs. 0% vs. 16% vs. 21% vs. 19%, p=0.0006), scleral infiltration (5% vs. 0% vs. 4% vs. 2% vs. 7%, p=0.13), and microscopic extrascleral infiltration (4% vs. 0% vs. <1% vs. <1% vs. 4%, p=0.68). Adjuvant chemotherapy with/without orbital radiotherapy was given in 761 (53%) patients. Based on Kaplan-Meier estimates in different continents (AS vs. AUS vs. EUR vs. NA vs. SA), the 6-year risk of orbital tumor recurrence was 5% vs. 2% vs. 0% vs. 0% vs. 12% (p<0.001), systemic metastasis was reported in 8% vs. 5% vs. 2% vs. 0% vs. 13% (p=0.001), and death in 10% vs. 3% vs. 2% vs. 0% vs. 11% (p<0.001) patients.\\nCONCLUSION: There is a wide variation in the infiltrative histopathology features of RB across continents, resulting in variable outcomes. SA and AS had a higher risk of orbital tumor recurrence, systemic metastasis, and death compared to AUS, EUR, and NA.', doc_id='7ca56bd7-2e65-4fae-a436-5f2ddb39855d', wins=3), Node(metadata={'uid': '39151159', 'Title': 'A Theory and Evidence-Informed e-Cycling Intervention for Individuals Diagnosed With Cancer: Development Study.', 'Published': '2024-08-16', 'Copyright Information': '©Jessica E Bourne, Paul Kelly, Miranda E G Armstrong. Originally published in JMIR Cancer (https://cancer.jmir.org), 16.08.2024.'}, page_content='BACKGROUND: Physical activity engagement following a cancer diagnosis is positively associated with survival, reduced risk of disease recurrence, and reduced cancer-specific and all-cause mortality. However, rates of physical activity engagement are low among individuals diagnosed with and being treated for breast cancer or prostate cancer.\\nOBJECTIVE: The purpose of this study was to describe the systematic process of developing an e-cycling intervention aimed at increasing physical activity among individuals living with prostate cancer or breast cancer and outline the key components to be implemented.\\nMETHODS: The Medical Research Council guidance for developing complex interventions and the Behaviour Change Wheel were used to guide intervention development. Information was gathered from the literature and through discussions with end users to understand factors influencing e-cycling. These factors were mapped onto the Theoretical Domains Framework to identify potential mechanisms of action. Behavior change techniques were selected from theory and evidence to develop intervention content. Interested parties, including cycling instructors, end users, and behavior change experts, reviewed and refined the intervention.\\nRESULTS: Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework. A total of 23 behavior change techniques were selected to target these domains over 4 one-to-one e-cycling sessions delivered by trained cycling instructors in the community. Cycling instructors were provided a 3-hour classroom training session on delivering the intervention and a 3-hour practical session with feedback. The outcome of this work is a theory and evidence-informed intervention aimed at promoting e-cycling behavior among individuals being treated for breast cancer or prostate cancer, which is currently being implemented and evaluated.\\nCONCLUSIONS: Transparent intervention development and reporting of content is important for comprehensively examining intervention implementation. The implementation of this intervention package is currently being evaluated in a pilot randomized controlled trial. If the intervention is found to be effective and the content and delivery are acceptable, this intervention will form a basis for the development of e-cycling interventions in other survivors of cancer.\\nTRIAL REGISTRATION: ISRCTN Registry ISRCTN39112034 https://www.isrctn.com/ISRCTN39112034; and IRSCTN Registry ISRCTN42852156; https://www.isrctn.com/ISRCTN42852156.', doc_id='9e0a0939-3745-467d-af19-4c2c896c7f21', wins=5), Node(metadata={'uid': '39151149', 'Title': 'The Importance of Digital Lung Tomosynthesis in Overcoming Computed-Tomography-to-Body Divergence During Bronchoscopic Biopsies of Peripheral Lung Nodules.', 'Published': '2024-08-16', 'Copyright Information': ''}, page_content='The advent of robotic bronchoscopy coupled with electromagnetic navigation bronchoscopy (EMN) and shape-sensing technology have increased diagnostic yields for peripheral pulmonary nodules compared to traditional bronchoscopy. Yet, diagnostic yields from these bronchoscopic platforms still fall short of where they should be. This shortfall is in large part due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD). Digital lung tomosynthesis (DLT) is an advanced imaging modality that helps overcome CTBD during bronchoscopic biopsies of lung nodules. DLT is a quasi-3D imaging technique, which reconstructs tomographic images of the lung from a series of 2D fluoroscopic projection images. These images can be acquired either using a digital flat panel fluoroscopy machine or a fluoroscopy machine with a more traditional image-intensifier present in most standard bronchoscopy suites. This review aims to explain the mechanisms of both CTBD and DLT to help diagnose early-stage lung cancer more effectively.', doc_id='e11630fc-2ac1-4b4c-a688-572c3f2c9314', wins=4)], node_embeddings_list=[[-0.05047006905078888, -0.00924971979111433, -0.00739614712074399, 0.02004431001842022, 0.011683718301355839, 0.009978670626878738, 0.030250925570726395, 0.0163064394146204, -0.0038162439595907927, 0.006354234647005796, 0.012460996396839619, -0.042679011821746826, -0.0026807961985468864, 0.03216209262609482, -0.041874513030052185, -0.030076732859015465, 0.013745746575295925, 0.0013136559864506125, -0.020289437845349312, 0.03476591035723686, -0.021849509328603745, 0.0075844088569283485, 0.003509526839479804, -0.02352146990597248, 0.03303378075361252, 0.0015063644386827946, -0.0027288079727441072, -0.04188613221049309, -0.04691840708255768, -0.22518204152584076, -0.014538468793034554, -0.051185205578804016, 0.024983318522572517, -0.002390797482803464, -0.02867944911122322, 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0.05768139660358429, 0.06953182816505432]], node_map={'9c84e86d-9230-47a2-9f83-6f9d0b1faa2b': Node(metadata={'uid': '39151210', 'Title': 'External validation of the Khorana score for the prediction of venous thromboembolism in cancer patients: A systematic review and meta-analysis.', 'Published': '2024-07-31', 'Copyright Information': 'Copyright © 2024 Elsevier Ltd. All rights reserved.'}, page_content=\"BACKGROUND: Venous thromboembolism is the leading cause of death in cancer patients, second only to tumor progression. The Khorana score is recommended by clinical guidelines for identifying ambulatory cancer patients at high risk of venous thromboembolism during chemotherapy. However, its predictive performance is debated among cancer patients.\\nOBJECTIVES: To map the applicability of the Khorana score in cancer patients and to assess its predictive performance across various cancer types, providing guidance for clinicians and nurses to use it more appropriately.\\nDESIGN: Systematic review and meta-analysis.\\nMETHODS: A comprehensive literature search of the electronic database was first conducted on August 30, 2023, and updated on May 20, 2024. Studies examining the Khorana score's predictive performance (including but not limited to the areas under the curve, C-index, and calibration plot) in cancer patients were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was applied to evaluate the methodological quality of the included studies. Data synthesis was achieved via random-effects meta-analysis using the R studio software. The subgroup analysis was performed according to the study design, clinical setting, cancer type, anti-cancer treatment stage, and country.\\nRESULTS: The review incorporated 67 studies, including 58 observational studies and nine randomized controlled trials. All included studies assessed the Khorana score's discrimination, with the C-index ranging from 0.40 to 0.84. The pooled C-index for randomized controlled trials was 0.61 (95\\u202f% CI 0.51-0.70), while observational studies showed a pooled C-index of 0.59 (95\\u202f% CI 0.57-0.60). Subgroup analyses revealed the pooled C-index for lung cancer, lymphoma, gastrointestinal cancer, and mixed cancer patients as 0.60 (95\\u202f% CI 0.53-0.67), 0.56 (95\\u202f% CI 0.51-0.61), 0.59 (95\\u202f% CI 0.39-0.76), and 0.60 (95\\u202f% CI 0.58-0.61), respectively. Inpatient and outpatient settings had the pooled C-index of 0.60 (95\\u202f% CI 0.58-0.63) and 0.58 (95\\u202f% CI 0.55-0.61), respectively. Calibration was assessed in only four studies. All included studies were identified to have a high risk of bias according to PROBAST.\\nCONCLUSION: The Khorana score has been widely validated in various types of cancer patients; however, it exhibited poor capability (pooled C-index<0.7) in accurately discriminating VTE risk among most types of cancer patients either in inpatient or outpatient settings. The Khorana score should be used with caution, and high-quality studies are needed to further validate its predictive performance.\\nREGISTRATION: The protocol for this study is registered with PROSPERO (registration number: CRD42023470320).\", doc_id='9c84e86d-9230-47a2-9f83-6f9d0b1faa2b', wins=3), '9de57b32-e0dd-4e1a-88e5-25f748a5380b': Node(metadata={'uid': '39151209', 'Title': 'Phase angle as a potential tool to evaluate chronic inflammatory state and predict quality of life deterioration in women with breast cancer and obesity: A narrative review.', 'Published': '2024-06-26', 'Copyright Information': 'Copyright © 2024 Elsevier Inc. All rights reserved.'}, page_content='The interaction between lifestyle--defined more specifically in health care as the personal exposome--and its implications on obesity and breast cancer development highlights the critical role of body composition and inflammation in these patients. There is clear evidence that the personal and internal exposome triggers biochemical, inflammatory, and metabolic reprogramming, which might favor ectopic lipid accumulation within the body, such as muscles. Additionally, the presence of excessive adipose tissue exacerbates these alterations in the internal exposome, resulting in cell damage and modifying body composition. Understanding the nexus between these lifestyle-induced exposome modifications, such as inflammation, and the resultant changes in body composition is crucial to assess the association with breast cancer progression and treatment responses. Various techniques can be used to evaluate body composition; one of those most used currently is bioelectrical impedance analysis. This analysis provides parameters, including phase angle (PhA), by which cellular health and metabolic activity can be assessed. In addition, PhA is a potential indicator of nutritional status and disease prognosis, as it has been linked to survival and quality of life in patients with cancer. Therefore, PhA might be used in daily oncology practice to implement an accurate nutritional intervention, reducing side effects and complications of oncology management, and improving quality of life during treatment and survival, even in patients with breast cancer with obesity or overweight. The aim of this review is to analyze the existing information on the current application of PhA in patients with breast cancer and its potential use as a tool to assess inflammatory response, identify malnutrition, and predict the deterioration of quality of life so that it could be proposed as an early indicator for nutritional interventions in this group of patients.', doc_id='9de57b32-e0dd-4e1a-88e5-25f748a5380b', wins=2), '7ca56bd7-2e65-4fae-a436-5f2ddb39855d': Node(metadata={'uid': '39151183', 'Title': 'High-Risk Histopathological Features of Retinoblastoma following Primary Enucleation: A Global Study of 1426 Patients from 5 Continents.', 'Published': '2024-08-14', 'Copyright Information': 'Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Opthalmic Communications Society, Inc.'}, page_content='PURPOSE: To evaluate high-risk histopathological features (HRHF) following primary enucleation of eyes with retinoblastoma (RB) and assess the patient outcomes across continents.\\nMETHODS: Retrospective study of 1426 primarily enucleated RB eyes from five continents.\\nRESULTS: Of all, 923 (65%) were from Asia (AS), 27 (2%) from Australia (AUS), 120 (8%) from Europe (EUR), 162 (11%) from North America (NA), and 194 (14%) from South America (SA). Based on the continent (AS vs. AUS vs. EUR vs. NA vs. SA), the histopathology features included massive choroidal invasion (31% vs. 7% vs. 13% vs. 19% vs. 27%, p=0.001), post-laminar optic nerve invasion (27% vs. 0% vs. 16% vs. 21% vs. 19%, p=0.0006), scleral infiltration (5% vs. 0% vs. 4% vs. 2% vs. 7%, p=0.13), and microscopic extrascleral infiltration (4% vs. 0% vs. <1% vs. <1% vs. 4%, p=0.68). Adjuvant chemotherapy with/without orbital radiotherapy was given in 761 (53%) patients. Based on Kaplan-Meier estimates in different continents (AS vs. AUS vs. EUR vs. NA vs. SA), the 6-year risk of orbital tumor recurrence was 5% vs. 2% vs. 0% vs. 0% vs. 12% (p<0.001), systemic metastasis was reported in 8% vs. 5% vs. 2% vs. 0% vs. 13% (p=0.001), and death in 10% vs. 3% vs. 2% vs. 0% vs. 11% (p<0.001) patients.\\nCONCLUSION: There is a wide variation in the infiltrative histopathology features of RB across continents, resulting in variable outcomes. SA and AS had a higher risk of orbital tumor recurrence, systemic metastasis, and death compared to AUS, EUR, and NA.', doc_id='7ca56bd7-2e65-4fae-a436-5f2ddb39855d', wins=3), '9e0a0939-3745-467d-af19-4c2c896c7f21': Node(metadata={'uid': '39151159', 'Title': 'A Theory and Evidence-Informed e-Cycling Intervention for Individuals Diagnosed With Cancer: Development Study.', 'Published': '2024-08-16', 'Copyright Information': '©Jessica E Bourne, Paul Kelly, Miranda E G Armstrong. Originally published in JMIR Cancer (https://cancer.jmir.org), 16.08.2024.'}, page_content='BACKGROUND: Physical activity engagement following a cancer diagnosis is positively associated with survival, reduced risk of disease recurrence, and reduced cancer-specific and all-cause mortality. However, rates of physical activity engagement are low among individuals diagnosed with and being treated for breast cancer or prostate cancer.\\nOBJECTIVE: The purpose of this study was to describe the systematic process of developing an e-cycling intervention aimed at increasing physical activity among individuals living with prostate cancer or breast cancer and outline the key components to be implemented.\\nMETHODS: The Medical Research Council guidance for developing complex interventions and the Behaviour Change Wheel were used to guide intervention development. Information was gathered from the literature and through discussions with end users to understand factors influencing e-cycling. These factors were mapped onto the Theoretical Domains Framework to identify potential mechanisms of action. Behavior change techniques were selected from theory and evidence to develop intervention content. Interested parties, including cycling instructors, end users, and behavior change experts, reviewed and refined the intervention.\\nRESULTS: Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework. A total of 23 behavior change techniques were selected to target these domains over 4 one-to-one e-cycling sessions delivered by trained cycling instructors in the community. Cycling instructors were provided a 3-hour classroom training session on delivering the intervention and a 3-hour practical session with feedback. The outcome of this work is a theory and evidence-informed intervention aimed at promoting e-cycling behavior among individuals being treated for breast cancer or prostate cancer, which is currently being implemented and evaluated.\\nCONCLUSIONS: Transparent intervention development and reporting of content is important for comprehensively examining intervention implementation. The implementation of this intervention package is currently being evaluated in a pilot randomized controlled trial. If the intervention is found to be effective and the content and delivery are acceptable, this intervention will form a basis for the development of e-cycling interventions in other survivors of cancer.\\nTRIAL REGISTRATION: ISRCTN Registry ISRCTN39112034 https://www.isrctn.com/ISRCTN39112034; and IRSCTN Registry ISRCTN42852156; https://www.isrctn.com/ISRCTN42852156.', doc_id='9e0a0939-3745-467d-af19-4c2c896c7f21', wins=5), 'e11630fc-2ac1-4b4c-a688-572c3f2c9314': Node(metadata={'uid': '39151149', 'Title': 'The Importance of Digital Lung Tomosynthesis in Overcoming Computed-Tomography-to-Body Divergence During Bronchoscopic Biopsies of Peripheral Lung Nodules.', 'Published': '2024-08-16', 'Copyright Information': ''}, page_content='The advent of robotic bronchoscopy coupled with electromagnetic navigation bronchoscopy (EMN) and shape-sensing technology have increased diagnostic yields for peripheral pulmonary nodules compared to traditional bronchoscopy. Yet, diagnostic yields from these bronchoscopic platforms still fall short of where they should be. This shortfall is in large part due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD). Digital lung tomosynthesis (DLT) is an advanced imaging modality that helps overcome CTBD during bronchoscopic biopsies of lung nodules. DLT is a quasi-3D imaging technique, which reconstructs tomographic images of the lung from a series of 2D fluoroscopic projection images. These images can be acquired either using a digital flat panel fluoroscopy machine or a fluoroscopy machine with a more traditional image-intensifier present in most standard bronchoscopy suites. This review aims to explain the mechanisms of both CTBD and DLT to help diagnose early-stage lung cancer more effectively.', doc_id='e11630fc-2ac1-4b4c-a688-572c3f2c9314', wins=4)}, run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), node_filter=NodeFilter(llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), threshold=1.5, context_scoring_prompt=Prompt(name='score_context', instruction='\\n    Given a context, perform the following task and output the answer in VALID JSON format: Assess the provided context and assign a numerical score of 1 (Low), 2 (Medium), or 3 (High) for each of the following criteria in your JSON response:\\n\\nclarity: Evaluate the precision and understandability of the information presented. High scores (3) are reserved for contexts that are both precise in their information and easy to understand. Low scores (1) are for contexts where the information is vague or hard to comprehend.\\ndepth: Determine the level of detailed examination and the inclusion of innovative insights within the context. A high score indicates a comprehensive and insightful analysis, while a low score suggests a superficial treatment of the topic.\\nstructure: Assess how well the content is organized and whether it flows logically. High scores are awarded to contexts that demonstrate coherent organization and logical progression, whereas low scores indicate a lack of structure or clarity in progression.\\nrelevance: Judge the pertinence of the content to the main topic, awarding high scores to contexts tightly focused on the subject without unnecessary digressions, and low scores to those that are cluttered with irrelevant information.\\nStructure your JSON output to reflect these criteria as keys with their corresponding scores as values\\n    ', output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"clarity\": {\"title\": \"Clarity\", \"type\": \"integer\"}, \"depth\": {\"title\": \"Depth\", \"type\": \"integer\"}, \"structure\": {\"title\": \"Structure\", \"type\": \"integer\"}, \"relevance\": {\"title\": \"Relevance\", \"type\": \"integer\"}}, \"required\": [\"clarity\", \"depth\", \"structure\", \"relevance\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'context': 'The Pythagorean theorem is a fundamental principle in geometry. It states that in a right-angled triangle, the square of the length of the hypotenuse (the side opposite the right angle) is equal to the sum of the squares of the lengths of the other two sides. This can be written as a^2 + b^2 = c^2 where c represents the length of the hypotenuse, and a and b represent the lengths of the other two sides.', 'output': {'clarity': 3, 'depth': 1, 'structure': 3, 'relevance': 3}}, {'context': 'Albert Einstein (14 March 1879 - 18 April 1955) was a German-born theoretical physicist who is widely held to be one of the greatest and most influential scientists of all time.', 'output': {'clarity': 3, 'depth': 2, 'structure': 3, 'relevance': 3}}, {'context': \"I love chocolate. It's really tasty. Oh, and by the way, the earth orbits the sun, not the other way around. Also, my favorite color is blue.\", 'output': {'clarity': 2, 'depth': 1, 'structure': 1, 'relevance': 1}}], input_keys=['context'], output_key='output', output_type='json', language='english')), question_filter=QuestionFilter(llm=LangchainLLMWrapper(run_config=RunConfig(timeout=180, max_retries=15, max_wait=90, max_workers=16, exception_types=(<class 'Exception'>,), log_tenacity=False, seed=42)), filter_question_prompt=Prompt(name='filter_question', instruction='\\nAsses the given question for clarity and answerability given enough domain knowledge, consider the following criteria:\\n1.Independence: Can the question be understood and answered without needing additional context or access to external references not provided within the question itself? Questions should be self-contained, meaning they do not rely on specific documents, tables, or prior knowledge not shared within the question.\\n2.Clear Intent: Is it clear what type of answer or information the question seeks? The question should convey its purpose without ambiguity, allowing for a direct and relevant response.\\nBased on these criteria, assign a verdict of \"1\" if a question is specific, independent, and has a clear intent, making it understandable and answerable based on the details provided. Assign \"0\" if it fails to meet one or more of these criteria due to vagueness, reliance on external references, or ambiguity in intent.\\nProvide feedback and a verdict in JSON format, including suggestions for improvement if the question is deemed unclear. Highlight aspects of the question that contribute to its clarity or lack thereof, and offer advice on how it could be reframed or detailed for better understanding and answerability.\\n', output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"feedback\": {\"title\": \"Feedback\", \"type\": \"string\"}, \"verdict\": {\"title\": \"Verdict\", \"type\": \"integer\"}}, \"required\": [\"feedback\", \"verdict\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'question': 'What is the discovery about space?', 'output': {'feedback': \"The question is too vague and broad, asking for a 'discovery about space' without specifying any particular aspect, time frame, or context of interest. This could refer to a wide range of topics, from the discovery of new celestial bodies to advancements in space travel technology. To improve clarity and answerability, the question could specify the type of discovery (e.g., astronomical, technological), the time frame (e.g., recent, historical), or the context (e.g., within a specific research study or space mission).\", 'verdict': 0}}, {'question': \"How does ALMA-13B-R perform compared to other translation models in the WMT'23 study, based on the results in context1 and context2?\", 'output': {'feedback': \"This question asks for a comparison of the ALMA-13B-R model's performance against other translation models within the WMT'23 study, specifically referring to results in 'context1' and 'context2'. While it clearly specifies the model of interest (ALMA-13B-R) and the study (WMT'23), it assumes access to and understanding of 'context1' and 'context2' without explaining what these contexts entail. This makes the question unclear for those not familiar with the WMT'23 study or these specific contexts. To improve clarity and answerability for a broader audience, the question could benefit from defining or describing 'context1' and 'context2' or explaining the criteria used for comparison in these contexts.\", 'verdict': 0}}, {'question': 'How do KIWI-XXL and XCOMET compare to the gold standard references in Table 1 in terms of evaluation scores, translation model performance, and success rate in surpassing the references?', 'output': {'feedback': \"The question requests a comparison between KIWI-XXL and XCOMET models and gold standard references in 'Table 1', focusing on evaluation scores, translation model performance, and success rates in surpassing the references. It specifies the models and criteria for comparison, making the intent clear. However, the question assumes access to 'Table 1' without providing its content or context, making it unclear for those without direct access to the source material. To be clearer and more answerable for a general audience, the question could include a brief description of the content or key findings of 'Table 1', or alternatively, frame the question in a way that does not rely on specific, unpublished documents.\", 'verdict': 0}}, {'question': 'What is the configuration of UL2 training objective in OpenMoE and why is it a better choice for pre-training?', 'output': {'feedback': 'The question asks for the configuration of the UL2 training objective within the OpenMoE framework and the rationale behind its suitability for pre-training. It is clear in specifying the topic of interest (UL2 training objective, OpenMoE) and seeks detailed information on both the configuration and the reasons for its effectiveness in pre-training. However, the question might be challenging for those unfamiliar with the specific terminology or the context of OpenMoE and UL2. For broader clarity and answerability, it would be helpful if the question included a brief explanation or context about OpenMoE and the UL2 training objective, or clarified the aspects of pre-training effectiveness it refers to (e.g., efficiency, accuracy, generalization).', 'verdict': 1}}, {'question': 'What is the detailed configuration of the UL2 training objective in OpenMoE, based on the provided context?', 'output': {'feedback': \"The question seeks detailed information on the UL2 training objective's configuration within the OpenMoE framework, mentioning 'the provided context' without actually including or describing this context within the query. This makes the question unclear for those who do not have access to the unspecified context. For the question to be clear and answerable, it needs to either include the relevant context directly within the question or be framed in a way that does not require external information. Detailing the specific aspects of the configuration of interest (e.g., loss functions, data augmentation techniques) could also help clarify the query.\", 'verdict': 0}}], input_keys=['question'], output_key='output', output_type='json', language='english')), question_answer_prompt=Prompt(name='answer_formulate', instruction=\"Answer the question using the information from the given context. Output verdict as '1' if answer is present '-1' if answer is not present in the context.\", output_format_instruction='The output should be a well-formatted JSON instance that conforms to the JSON schema below.\\n\\nAs an example, for the schema {\"properties\": {\"foo\": {\"title\": \"Foo\", \"description\": \"a list of strings\", \"type\": \"array\", \"items\": {\"type\": \"string\"}}}, \"required\": [\"foo\"]}\\nthe object {\"foo\": [\"bar\", \"baz\"]} is a well-formatted instance of the schema. The object {\"properties\": {\"foo\": [\"bar\", \"baz\"]}} is not well-formatted.\\n\\nHere is the output JSON schema:\\n```\\n{\"type\": \"object\", \"properties\": {\"answer\": {\"title\": \"Answer\", \"type\": \"string\"}, \"verdict\": {\"title\": \"Verdict\", \"type\": \"integer\"}}, \"required\": [\"answer\", \"verdict\"]}\\n```\\n\\nDo not return any preamble or explanations, return only a pure JSON string surrounded by triple backticks (```).', examples=[{'context': 'Climate change is significantly influenced by human activities, notably the emission of greenhouse gases from burning fossil fuels. The increased greenhouse gas concentration in the atmosphere traps more heat, leading to global warming and changes in weather patterns.', 'question': 'How do human activities contribute to climate change?', 'answer': {'answer': 'Human activities contribute to climate change primarily through the emission of greenhouse gases from burning fossil fuels. These emissions increase the concentration of greenhouse gases in the atmosphere, which traps more heat and leads to global warming and altered weather patterns.', 'verdict': 1}}, {'context': 'The concept of artificial intelligence (AI) has evolved over time, but it fundamentally refers to machines designed to mimic human cognitive functions. AI can learn, reason, perceive, and, in some instances, react like humans, making it pivotal in fields ranging from healthcare to autonomous vehicles.', 'question': 'What are the key capabilities of artificial intelligence?', 'answer': {'answer': 'Artificial intelligence is designed to mimic human cognitive functions, with key capabilities including learning, reasoning, perception, and reacting to the environment in a manner similar to humans. These capabilities make AI pivotal in various fields, including healthcare and autonomous driving.', 'verdict': 1}}, {'context': 'The novel \"Pride and Prejudice\" by Jane Austen revolves around the character Elizabeth Bennet and her family. The story is set in the 19th century in rural England and deals with issues of marriage, morality, and misconceptions.', 'question': \"What year was 'Pride and Prejudice' published?\", 'answer': {'answer': 'The answer to given question is not present in context', 'verdict': -1}}], input_keys=['context', 'question'], output_key='answer', output_type='json', language='english'), find_relevant_context_prompt=Prompt(name='find_relevant_context', instruction='Given a question and set of contexts, find the most relevant contexts to answer the question.', output_format_instruction='', examples=[{'question': 'What is the capital of France?', 'contexts': ['1. France is a country in Western Europe. It has several cities, including Paris, Lyon, and Marseille. Paris is not only known for its cultural landmarks like the Eiffel Tower and the Louvre Museum but also as the administrative center.', '2. The capital of France is Paris. It is also the most populous city in France, with a population of over 2 million people. Paris is known for its cultural landmarks like the Eiffel Tower and the Louvre Museum.', '3. Paris is the capital of France. It is also the most populous city in France, with a population of over 2 million people. Paris is known for its cultural landmarks like the Eiffel Tower and the Louvre Museum.'], 'output': {'relevant_contexts': [1, 2]}}, {'question': 'How does caffeine affect the body and what are its common sources?', 'contexts': ['1. Caffeine is a central nervous system stimulant. It can temporarily ward off drowsiness and restore alertness. It primarily affects the brain, where it alters the function of neurotransmitters.', '2. Regular physical activity is essential for maintaining good health. It can help control weight, combat health conditions, boost energy, and promote better sleep.', '3. Common sources of caffeine include coffee, tea, cola, and energy drinks. These beverages are consumed worldwide and are known for providing a quick boost of energy.'], 'output': {'relevant_contexts': [1, 2]}}], input_keys=['question', 'contexts'], output_key='output', output_type='json', language='english'), rewrite_invalid_question_prompt=Prompt(name='rewrite_question', instruction='Given a context, question and feedback, rewrite the question to improve its clarity and answerability based on the feedback provided.', output_format_instruction='', examples=[{'context': \"The Eiffel Tower was constructed using iron and was originally intended as a temporary exhibit for the 1889 World's Fair held in Paris. Despite its initial temporary purpose, the Eiffel Tower quickly became a symbol of Parisian ingenuity and an iconic landmark of the city, attracting millions of visitors each year. The tower's design, created by Gustave Eiffel, was initially met with criticism from some French artists and intellectuals, but it has since been celebrated as a masterpiece of structural engineering and architectural design.\", 'question': 'Who created the design for the Tower?', 'feedback': \"The question asks about the creator of the design for 'the Tower', but it does not specify which tower it refers to. There are many towers worldwide, and without specifying the exact tower, the question is unclear and unanswerable. To improve the question, it should include the name or a clear description of the specific tower in question.\", 'output': 'Who created the design for the Eiffel Tower?'}, {'context': \"'Exploring Zero-Shot Learning in Neural Networks' was published by Smith and Lee in 2021, focusing on the application of zero-shot learning techniques in artificial intelligence.\", 'question': 'What datasets were used for the zero-shot evaluations in this study?', 'feedback': \"The question asks about the datasets used for zero-shot evaluations in 'this study', without specifying or providing any details about the study in question. This makes the question unclear for those who do not have access to or knowledge of the specific study. To improve clarity and answerability, the question should specify the study it refers to, or provide enough context about the study for the question to be understood and answered independently.\", 'output': 'What datasets were used for the zero-shot evaluations Exploring Zero-Shot Learning in Neural Networks paper?'}], input_keys=['context', 'question', 'feedback'], output_key='output', output_type='str', language='english'), max_tries=5, is_async=True, compress_question_prompt=Prompt(name='compress_question', instruction='Rewrite the following question to make it more indirect and shorter while retaining the essence of the original question.\\n    The goal is to create a question that conveys the same meaning but in a less direct manner. The rewritten question should shorter so use abbreviation wherever possible.', output_format_instruction='', examples=[{'question': 'What is the distance between the Earth and the Moon?', 'output': 'How far is the Moon from Earth?'}, {'question': 'What ingredients are required to bake a chocolate cake?', 'output': \"What's needed for a chocolate cake?\"}], input_keys=['question'], output_key='output', output_type='str', language='english'), multi_context_question_prompt=Prompt(name='multi_context_question', instruction=\"\\n    The task is to rewrite and complicate the given question in a way that answering it requires information derived from both context1 and context2. \\n    Follow the rules given below while rewriting the question.\\n        1. The rewritten question should not be very long. Use abbreviation wherever possible.\\n        2. The rewritten question must be reasonable and must be understood and responded by humans.\\n        3. The rewritten question must be fully answerable from information present in context1 and context2. \\n        4. Read and understand both contexts and rewrite the question so that answering requires insight from both context1 and context2.\\n        5. phrases like 'based on the provided context','according to the context?',etc are not allowed to appear in the question.\", output_format_instruction='', examples=[{'question': 'What process turns plants green?', 'context1': 'Chlorophyll is the pigment that gives plants their green color and helps them photosynthesize.', 'context2': 'Photosynthesis in plants typically occurs in the leaves where chloroplasts are concentrated.', 'output': 'In which plant structures does the pigment responsible for their verdancy facilitate energy production?'}, {'question': 'How do you calculate the area of a rectangle?', 'context1': \"The area of a shape is calculated based on the shape's dimensions. For rectangles, this involves multiplying the length and width.\", 'context2': 'Rectangles have four sides with opposite sides being equal in length. They are a type of quadrilateral.', 'output': \"What multiplication involving equal opposites yields a quadrilateral's area?\"}], input_keys=['question', 'context1', 'context2'], output_key='output', output_type='str', language='english'))\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "test_df = testset.to_pandas()"
      ],
      "metadata": {
        "id": "o8KOhPd3LlOh"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1327
        },
        "id": "roEVtwO4Lqj_",
        "outputId": "893ba089-5ee6-4848-a8bb-44cf6555fd6d"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>[{'uid': '39151149', 'Title': 'The Importance ...</td>\n",
              "      <td>True</td>\n",
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              "      <td>Here is a question that can be fully answered ...</td>\n",
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              "      <td>The domains of the Theoretical Domains Framewo...</td>\n",
              "      <td>simple</td>\n",
              "      <td>[{'uid': '39151159', 'Title': 'A Theory and Ev...</td>\n",
              "      <td>True</td>\n",
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              "    <tr>\n",
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              "      <td>Here is a question that can be fully answered ...</td>\n",
              "      <td>[BACKGROUND: Venous thromboembolism is the lea...</td>\n",
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              "      <td>simple</td>\n",
              "      <td>[{'uid': '39151210', 'Title': 'External valida...</td>\n",
              "      <td>True</td>\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "\n",
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              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "\n",
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              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('test_df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "      (() => {\n",
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              "        document.querySelector('#id_0f947315-6873-4504-855c-28ebdaca5cec button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('test_df');\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "test_df",
              "summary": "{\n  \"name\": \"test_df\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"question\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Here is a question that can be fully answered from the given context:\\n\\n\\\"What is the main limitation in the diagnostic yields of peripheral pulmonary nodules using robotic bronchoscopy and electromagnetic navigation bronchoscopy?\\\"\\n\\nThis question is formed using the keyphrase \\\"Lung cancer diagnosis\\\" and can be answered by referencing the context, which states that \\\"diagnostic yields from these bronchoscopic platforms still fall short of where they should be\\\" due to a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD).\",\n          \"Here is a question that can be fully answered from the given context:\\n\\n\\\"What domains of the Theoretical Domains Framework were used to identify potential mechanisms of action in the development of the e-cycling intervention?\\\"\\n\\nThis question is formed using the topic \\\"Theoretical Domains Framework\\\" and can be answered by referring to the context, specifically the sentence: \\\"Anticipated barriers and facilitators to e-cycling engagement were mapped onto 11 of the 14 domains of the Theoretical Domains Framework.\",\n          \"Here is a question that can be fully answered from the given context:\\n\\n\\\"What is the pooled C-index of the Khorana score in accurately discriminating VTE risk among most types of cancer patients?\\\"\\n\\nThis question is formed using the topic \\\"Predictive performance\\\" and can be answered by referring to the results section of the context, which states that the pooled C-index for most types of cancer patients is less than 0.7.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"contexts\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ground_truth\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"The main limitation in the diagnostic yields of peripheral pulmonary nodules using robotic bronchoscopy and electromagnetic navigation bronchoscopy is a lack of advanced imaging during peripheral bronchoscopy and computed tomography (CT)-to-body divergence (CTBD).\",\n          \"The domains of the Theoretical Domains Framework used to identify potential mechanisms of action in the development of the e-cycling intervention were mapped onto 11 of the 14 domains.\",\n          \"The Khorana score has been widely validated in various types of cancer patients; however, it exhibited poor capability (pooled C-index<0.7) in accurately discriminating VTE risk among most types of cancer patients either in inpatient or outpatient settings.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"evolution_type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"simple\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"metadata\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"episode_done\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          true\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "eGirmE18LsN1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}