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  "source_url": "https://www.kaggle.com/competitions/beta-beta-decay-identification/data",
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      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>TBA</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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      "content": "## File descriptions\n- **data_train.csv.gz** - the training set\n- **data_test.csv.gz** - the testing set\n- **labels_train.csv.gz** - labels for the training set\n- **cnn_benchmark.ipynb** - the benchmark solution based on CNN\n- **submission.csv.gz** - a submission file example\n\n## data_train.csv.gz,  data_test.csv.gz\n- **EventID** - event identifier\n- **Theta** - theta coordinate of photons in spherical coordinate system\n- **Phi** - phi coordinate of photons in spherical coordinate system\n- **Time** - time when a photon was registered\n\n## labels_train.csv.gz\n- **EventID** - event identifier\n- **Label** - true label of an event. 1 means signal, 0 means background\n\n## submission.csv.gz\n- **EventID** - event identifier\n- **Proba** - predicted probability to be a signal",
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      "name": "Description",
      "content": "The goal of this competition is to identify double beta decays in a Kiloton-Scale Liquid Scintillator Detector. Background events are produced by neutrino interactions due to decays in the sun.\n\nThe detector has spherical form and registers photons on its surface. Each event is described by coordinates and time of registered photons. There are two types of photons in an event. Cherenkov photons fly in a cone and are produced by a particle due to Cherenkov effect. Scintillation photons fly in all directions and are produced due to interactions of photons and electrons with scintillator of the detector. \n\n\nUseful materials:\n\n- [Separating Double-Beta Decay Events from Solar Neutrino Interactions in a Kiloton-Scale Liquid Scintillator Detector By Fast Timing][1]\n\n- [Measuring Directionality in Double-Beta Decay and Neutrino Interactions with Kiloton-Scale Scintillation Detectors][2]\n\n- [Applying Machine Learning for Beta-Beta-decay Identification][3]\n\n<h2>Collaboration</h2>\n\nResults of this competition potentially will be used in a real experiment. Participants have opportunity to contribute to particle physics. \n\nWe encourage participants to share their solutions with each other. \n\nThe competition is supported by Laboratory of Methods for Big Data Analysis (Lambda) of National Research University Higher School of Economics. Contact us for collaboration.\n\n\n<h2>Acknowledgements</h2>\nWe thank Research Assistant Professor Andrey Elagin from University of Chicago for providing this dataset, solution and materials.\n\n<h2>Contacts</h2>\n\n- Mikhail Hushchyn (Lambda): mikhail.hushchyn@cern.ch\n- Andrey Elagin: elagin@hep.uchicago.edu\n\n\n  [1]: https://arxiv.org/abs/1609.09865\n  [2]: https://arxiv.org/abs/1307.5813\n  [3]: https://indico.cern.ch/event/704343/contributions/2960167/attachments/1633170/2604623/AElagin_for_THEIA_at_UCDavis_v5.pdf",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is ROC AUC.\n\n\n<h2>Submission Format</h2>\nSubmission files should contain two columns: EventID and Proba. Proba contains predicted probabilities that an event is signal.\n<p>The file should contain a header and have the following format:</p>\n<pre>EventID, Proba<br />0, 0.21<br /><span style=\"font-size: 14px; line-height: 1.4em;\">1, 0.99<br />4, 0.74<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">7, 0.01<br /></span><span style=\"font-size: 14px; line-height: 1.4em;\">etc.</span>\n</pre>",
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