{
  "id": 465806,
  "title": "Recap of Competition - Congratulations to the Winners!",
  "url": "/competitions/UBC-OCEAN/discussion/465806",
  "author_name": "Anju Kandru",
  "post_date": "2024-01-05T17:25:18.926000",
  "votes": 6,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Hi Kagglers,</p>\n<p>We’re happy to announce the conclusion of the UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN) competition. Thank you everyone for your participation!</p>\n<p>This competition ended with 9247 registrations and 1772 participants on 1326 teams. We had 35279 submissions from 82 countries. For 468 users (including 49 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!  </p>\n<p>The top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.</p>\n<p>We've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact <a href=\"https://www.kaggle.com/compliance\" target=\"_blank\">compliance</a>. Please fill in all the fields honestly.</p>\n<p>We highly encourage you to post a solution write-up about your approach and solution in the forums (see <a href=\"https://www.kaggle.com/discussions/product-feedback/373153\" target=\"_blank\">instructions</a>). You may also refer to <a href=\"https://www.kaggle.com/solution-write-up-documentation\" target=\"_blank\">Kaggle Solution Write-Up Documentation</a> for guidance. </p>\n<p>Thanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!</p>\n<p>Happy Modeling!<br>\nKaggle Team</p>",
  "messages": [
    {
      "id": 2588733,
      "postDate": "2024-01-05T17:25:18.927Z",
      "content": "<p>Hi Kagglers,</p>\n<p>We’re happy to announce the conclusion of the UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN) competition. Thank you everyone for your participation!</p>\n<p>This competition ended with 9247 registrations and 1772 participants on 1326 teams. We had 35279 submissions from 82 countries. For 468 users (including 49 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!  </p>\n<p>The top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.</p>\n<p>We've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact <a href=\"https://www.kaggle.com/compliance\" target=\"_blank\">compliance</a>. Please fill in all the fields honestly.</p>\n<p>We highly encourage you to post a solution write-up about your approach and solution in the forums (see <a href=\"https://www.kaggle.com/discussions/product-feedback/373153\" target=\"_blank\">instructions</a>). You may also refer to <a href=\"https://www.kaggle.com/solution-write-up-documentation\" target=\"_blank\">Kaggle Solution Write-Up Documentation</a> for guidance. </p>\n<p>Thanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!</p>\n<p>Happy Modeling!<br>\nKaggle Team</p>",
      "rawMarkdown": "Hi Kagglers,\n\nWe’re happy to announce the conclusion of the UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN) competition. Thank you everyone for your participation!\n\nThis competition ended with 9247 registrations and 1772 participants on 1326 teams. We had 35279 submissions from 82 countries. For 468 users (including 49 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!  \n\nThe top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nWe highly encourage you to post a solution write-up about your approach and solution in the forums (see [instructions](https://www.kaggle.com/discussions/product-feedback/373153)). You may also refer to [Kaggle Solution Write-Up Documentation](https://www.kaggle.com/solution-write-up-documentation) for guidance. \n\nThanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!\n\nHappy Modeling!\nKaggle Team\n\n",
      "votes": 6
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2588733": "Hi Kagglers,\n\nWe’re happy to announce the conclusion of the UBC Ovarian Cancer Subtype Classification and Outlier Detection (UBC-OCEAN) competition. Thank you everyone for your participation!\n\nThis competition ended with 9247 registrations and 1772 participants on 1326 teams. We had 35279 submissions from 82 countries. For 468 users (including 49 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!  \n\nThe top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nWe highly encourage you to post a solution write-up about your approach and solution in the forums (see [instructions](https://www.kaggle.com/discussions/product-feedback/373153)). You may also refer to [Kaggle Solution Write-Up Documentation](https://www.kaggle.com/solution-write-up-documentation) for guidance. \n\nThanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!\n\nHappy Modeling!\nKaggle Team\n\n"
  }
}