{
  "fetched_at": "2026-10-20T04:18:36Z",
  "source_url": "https://www.kaggle.com/competitions/electrance-predicting-superconductivity-peaks/data",
  "pages": [
    {
      "name": "data-description",
      "content": "The dataset consists of a collection of superconductors, each characterized by a set of parameters. These parameters include atomic mass, entropy atomic mass, the number of elements, atomic radius, density, electron affinity, fusion heat, thermal conductivity, and valence. Participants will use this information to train their machine learning models to find the critical temperature of superconductors.",
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    {
      "name": "Description",
      "content": "Problem Statement:\nPredict the critical temperature for the materials using the given parameters.\n\nSubmit a CSV file, with the predicted values for each test case (using the 'Id' column to denote the case).\n\n",
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    {
      "name": "Evaluation",
      "content": "The performance of your models will be evaluated using the RMSE between your predictions and the actual critical temperatures. The closer your predictions align with reality, the higher your chances of claiming victory.",
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    {
      "name": "rules",
      "content": " Follow competition rules, instructions, and deadlines strictly\n\n - Submit your own work; avoid plagiarism and unauthorized data use!\n - Apply yourself!\n - Have fun!",
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    {
      "name": "abstract",
      "content": "Superconductivity is a phenomenon observed in certain materials at extremely low temperatures where electrical resistance drops to zero. This property has transformative implications for various technological applications, such as energy transmission, magnetic resonance imaging (MRI), and high-speed transportation. The critical temperature is the temperature at which a material transitions from a normal to a superconducting state. Predicting this critical temperature is crucial for identifying materials with desirable superconducting properties. Accurate predictions facilitate the discovery of new materials and contribute to the development of more efficient and practical superconductors for real-world applications.\n",
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