{ "fetched_at": "2026-10-19T06:28:13Z", "source_url": "https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use/data", "pages": [ { "name": "rules", "content": "### One account per participant\n\nYou cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.\n\n### No private sharing outside teams\n\nPrivately sharing code or data outside of teams is not permitted. It's okay to share code if made available to all participants on the forums.\n\n### Team Mergers\n\nTeam mergers are allowed and can be performed by the team leader. In order to merge, the combined team must have a total submission count less than or equal to the maximum allowed as of the Team Merger Deadline. The maximum allowed is the number of submissions per day multiplied by the number of days the competition has been running.\n\n### Team Limits\n\nThe maximum team size is 5.\n\n### Submission Limits\n\nYou may submit a maximum of 5 entries per day.\n\nYou may select up to 2 final submissions for judging.\n\n### Competition Timeline\n\nCompetition Timeline dates (including Entry Deadline, Final Submission Deadline, Start Date, and Team Merger Deadline, as applicable) are reflected on the competition’s Overview > Timeline page.\n\n### COMPETITION-SPECIFIC TERMS\n\n**COMPETITION TITLE**: Child Mind Institute - Problematic Internet Use\n\n**COMPETITION HOST**: The Child Mind Institute\n\n**COMPETITION SPONSORS**: Dell Technologies, the NVIDIA Corporation, and the California Department of Healthcare Services.\n\n**COMPETITION SPONSOR ADDRESS**: 101 East 56th Street, New York, NY 10022\n\n**COMPETITION WEBSITE**: https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use\n\n**TOTAL PRIZES AVAILABLE: $ 60,000**\n\nFirst Prize: $ 15,000\n\nSecond Prize: $ 10,000\n\nThird Prize: $ 8,000\n \nFourth Prize: $ 7,000\n\nFifth Prize: $ 5,000\n\nSixth Prize: $ 5,000\n\nSeventh Prize: $ 5,000\n\nEighth Prize: $ 5,000\n\n**WINNER LICENSE TYPE**: OPEN SOURCE - LGPL 2.1\n\n**DATA ACCESS AND USE**: Non-Commercial Use, for the purposes of the competition. Re-distribution or re-identification of any data is strictly prohibited.\n\nCompetitions are open to residents of the United States and worldwide, except that if you are a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, North Korea, or are subject to U.S. export controls or sanctions, you may not enter the Competition. Other local rules and regulations may apply to you, so please check your local laws to ensure that you are eligible to participate in skills-based competitions. The Competition Sponsor reserves the right to award alternative Prizes where needed to comply with local laws.\n\n**ENTRY IN THIS COMPETITION CONSTITUTES YOUR ACCEPTANCE OF THESE OFFICIAL COMPETITION RULES.**\n\nThe Competition named above is a skills-based competition to promote and further the field of data science. You must register via the Competition Website to enter. Your competition submissions (\"Submissions\") must conform to the requirements stated on the Competition Website. Your Submissions will be scored based on the evaluation metric described on the Competition Website. Subject to compliance with the Competition Rules, Prizes, if any, will be awarded to participants with the best scores, based on the merits of the data science models submitted. See below for the complete Competition Rules.\n\n### A. COMPETITION-SPECIFIC RULES\n\nIn addition to the provisions of the General Competition Rules below, you understand and agree to these Competition-Specific Rules required by the Competition Sponsor:\n\n\n#### **1. WINNER LICENSE.** \n\nUnder Section 11 (Winners Obligations) of the General Rules below, you hereby grant and will grant Competition Sponsor the following license(s) with respect to your Submission if you are a Competition winner:\n \n*Open Source*: You hereby license and will license your winning Submission and the source code used to generate the Submission under an Open Source Initiative-approved license (see [LGPL 2.1](https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html)). To the extent your Submission makes use of generally commercially available software not owned by you that you used to generate your submission, but that can be procured by the Competition Sponsor without undue expense, you do not grant the license in the preceding sentence to that software.\n \n#### **2. COMPETITION DATA ACCESS AND USE.** \nIn addition to the provisions identified in Section B.7. below, please note the following regarding the Competition Data. No data sources external to those directly shared as a part of this competition that are either copies of, or derived from, the Healthy Brain Network dataset may be used in this competition; such use will result in automatic disqualification from eligibility. Participants with access to the HBN dataset via a Data Usage Agreement (DUA) with the Child Mind Institute may not use any data extracted from this research data for this competition, and participants who are not active DUA holders agree that they will not request access to the dataset for use in unrelated projects for the duration of this competition.\n\n#### **3. AUTOMATED MACHINE LEARNING TOOLS (AMLT).** \n\nIndividual participants and Teams may use automated machine learning tool(s) (“AMLT”) (e.g., Google AutoML, H2O Driverless AI, etc.) to create a Submission, provided that the participant or Team ensures that they have an appropriate license to the AMLT such that they are able to comply with the Competition Rules. \n \nThe following provision is added to the end of Section 11 of the General Competition Rules below: “Individual participants and Teams who create a Submission using an AMLT may win a Prize. However, for clarity, the potential winner’s Submission must still meet the requirements of these Rules, including but not limited to Section A.1 (Winners License), Section B.11 (Winners Obligations), and Section B.17 (Warranty, Indemnity, and Release).” \n\n### B. GENERAL COMPETITION RULES\n#### **1.\tBINDING AGREEMENT.** \n\nTo enter the Competition, you must agree to these Official Competition Rules, which incorporate by reference the provisions and content of the Competition Website and any Specific Competition Rules above (collectively, the \"Rules\"). Please read these Rules carefully before entry to ensure you understand and agree. You further agree that submission of an entry in the Competition constitutes agreement to these Rules. You may not submit an entry to the Competition and are not eligible to receive the prizes associated with this Competition (“Prizes”) unless you agree to these Rules. These Rules form a binding legal agreement between you and the Competition Sponsor with respect to the Competition.\n\n#### **2.\tELIGIBILITY.** \n\nA. To be eligible to enter the Competition, you must be:\n\t(i) a registered account holder at Kaggle.com; \n\t(ii) the older of 18 years old or the age of majority in your jurisdiction of residence (unless otherwise agreed to by Competition Sponsor and appropriate parental/guardian consents have been obtained by Competition Sponsor); \n\t(iii) not a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, or North Korea; and\n\t(iv) not a person or representative of an entity under U.S. export controls or sanctions (see [https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx][1]).\n\nIf you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and the entity you represent or are an employee. If you are acting within the scope of your employment, as an employee, contractor, or agent of another party, you warrant that such party has full knowledge of your actions and has consented thereto, including your potential receipt of a Prize. You further warrant that your actions do not violate your employer's or entity's policies and procedures. \n\nThe Competition Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time. If you provide any false information relating to the Competition concerning your identity, residency, mailing address, telephone number, email address, ownership of right, or information required for entering the Competition, you may be immediately disqualified from the Competition.\n\nB. Unless otherwise stated in the Specific Competition Rules above or prohibited by internal policies of the Competition Entities, full-time employees, volunteers, contractors, officers, sponsors' Kaggle Grand Masters, and directors of Competition Entities may enter and participate in the Competition, but are not eligible to win any Prizes. \"Competition Entities\" means the Competition Sponsor, Competition Host, Kaggle Inc., and their respective parent companies, subsidiaries and affiliates. If you are such a participant from a Competition Entity, you are subject to all applicable internal policies of your employer with respect to your participation.\n\n#### **3.\tSPONSOR AND HOSTING PLATFORM.** \n\nThe Competition is sponsored by Competition Sponsor named above. The Competition is hosted on behalf of Competition Sponsor by Kaggle Inc. (\"Kaggle\"). Kaggle is an independent contractor of Competition Sponsor, and is not a party to this or any agreement between you and Competition Sponsor. You understand that Kaggle has no responsibility with respect to selecting the potential Competition winner(s) or awarding any Prizes. Kaggle will perform certain administrative functions relating to hosting the Competition, and you agree to abide by the provisions relating to Kaggle under these Rules. As a Kaggle.com account holder and user of the Kaggle competition platform, remember you have accepted and are subject to the Kaggle Terms of Service at [www.kaggle.com/terms][2] in addition to these Rules.\n\n#### **4.\tCOMPETITION PERIOD.** \n\nFor the purposes of Prizes, the Competition will run from the Start Date and time to the Final Submission Deadline (such duration the “Competition Period”). The Competition Timeline is subject to change, and Competition Sponsor may introduce additional hurdle deadlines during the Competition Period. Any updated or additional deadlines will be publicized on the Competition Website. It is your responsibility to check the Competition Website regularly to stay informed of any deadline changes. *YOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION.* \n\n#### **5.\tCOMPETITION ENTRY.** \n\nNO PURCHASE NECESSARY TO ENTER OR WIN. To enter the Competition, you must register on the Competition Website prior to the Entry Deadline, and follow the instructions for developing and entering your Submission through the Competition Website. Your Submissions must be made in the manner and format, and in compliance with all other requirements, stated on the Competition Website (the \"Requirements\"). Submissions must be received before any Submission deadlines stated on the Competition Website. Submissions not received by the stated deadlines will not be eligible to receive a Prize.\n\nSubmissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\n\nIf the Competition is a multi-stage competition with temporally separate training and/or test data, one or more valid Submissions may be required during each Competition stage in the manner described on the Competition Website in order for the Submissions to be Prize eligible.\n\nSubmissions are void if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. Competition Sponsor reserves the right to disqualify any entrant who does not follow these Rules, including making a Submission that does not meet the Requirements. \n\n#### **6.\tINDIVIDUALS AND TEAMS.** \n\nA. *Individual Account*. You may make Submissions only under one, unique Kaggle.com account. You will be disqualified if you make Submissions through more than one Kaggle account, or attempt to falsify an account to act as your proxy. You may submit up to the maximum number of Submissions per day as specified on the Competition Website. \n\nB. *Teams*. If permitted under the Competition Website guidelines, multiple individuals may collaborate as a team (a \"Team\"); however, you may join or form only one Team. Each Team member must be a single individual with a separate Kaggle account. You must register individually for the Competition before joining a Team. You must confirm your Team membership to make it official by responding to the Team notification message sent to your Kaggle account. Team membership may not exceed the Maximum Team Size stated on the Competition Website.\n\nC. *Team Merger*. Teams may request to merge via the Competition Website. Team mergers may be allowed provided that: (i) the combined Team does not exceed the Maximum Team Size; (ii) the number of Submissions made by the merging Teams does not exceed the number of Submissions permissible for one Team at the date of the merger request; (iii) the merger is completed before the earlier of: any merger deadline or the Competition deadline; and (iv) the proposed combined Team otherwise meets all the requirements of these Rules. \n\n#### **7.\tCOMPETITION DATA.** \n\n\"Competition Data\" means the data or datasets available from the Competition Website for the purpose of use in the Competition, including any prototype or executable code provided on the Competition Website. The Competition Data will contain private and public test sets. Which data belongs to which set will not be made available to participants. \n\nA. *Data Access and Use*. For the purposes of the competition, you may access and use the Competition Data for non-commercial purposes only, including for participating in the Competition and on Kaggle.com forums, and for academic research and education. Following the challenge's completion, there may be different revisions in licensing terms as determined by the contributing institutions at that time. The Competition Sponsor reserves the right to disqualify any participant who uses the Competition Data other than as permitted by the Competition Website and these Rules.\n\nPhenotypic (e.g., tabular, survey) data used in this Challenge have been contributed by the Healthy Brain Network study and are de-identified patient data, meaning that the contributing institutions have taken reasonable care to remove from them all personally identifiable information. As a participant in the Competition, you agree 1) not to make copies of, or in any way redistribute, any of the data made available to you, 2) not to attempt to re-identify any personal information based on the data, 3) not to attempt to probe the test set's labels, and 4) to notify the Competition organizers of any personally identifiable information you encounter in the data by posting a message to the Kaggle community discussion forums.\n\nIf you reference or use the dataset in any form, include the following citation:\n\n“CMI 2024 Problematic Internet Use Detection Challenge”\n\n\nB. *Data Security*. You agree to use reasonable and suitable measures to prevent persons who have not formally agreed to these Rules from gaining access to the Competition Data. You agree not to transmit, duplicate, publish, redistribute or otherwise provide or make available the Competition Data to any party not participating in the Competition. You agree to notify Kaggle immediately upon learning of any possible unauthorized transmission of or unauthorized access to the Competition Data and agree to work with Kaggle to rectify any unauthorized transmission or access.\n\nC. *External Data*. You may use data other than the Competition Data (“External Data”) to develop and test your Submissions. However, you will ensure the External Data is publicly available and equally accessible to use by all participants of the Competition for purposes of the competition at no cost to the other participants. The ability to use External Data under this Section 7.C (External Data) does not limit your other obligations under these Competition Rules, including but not limited to Section 11 (Winners Obligations). \n\n#### **8.\tSUBMISSION CODE REQUIREMENTS.**\n\nA. *Private Code Sharing*. Unless otherwise specifically permitted under the Competition Website or Competition Specific Rules above, during the Competition Period, you are not allowed to privately share source or executable code developed in connection with or based upon the Competition Data or other source or executable code relevant to the Competition (“Competition Code”). This prohibition includes sharing Competition Code between separate Teams, unless a Team merger occurs. Any such sharing of Competition Code is a breach of these Competition Rules and may result in disqualification.\n\nB. *Public Code Sharing*. You are permitted to publicly share Competition Code, provided that such public sharing does not violate the intellectual property rights of any third party. If you do choose to share Competition Code or other such code, you are required to share it on Kaggle.com on the discussion forum or notebooks associated specifically with the Competition for the benefit of all competitors. By so sharing, you are deemed to have licensed the shared code under an Open Source Initiative-approved license (see [www.opensource.org][3]) that in no event limits commercial use of such Competition Code or model containing or depending on such Competition Code.\n\nC. *Use of Open Source*. Unless otherwise stated in the Specific Competition Rules above, if open source code is used in the model to generate the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see [www.opensource.org][4]) that in no event limits commercial use of such code or model containing or depending on such code.\n\n#### **9.\tDETERMINING WINNERS.** \n\nEach Submission will be scored and ranked by the evaluation metric stated on the Competition Website. During the Competition Period, the current ranking will be visible on the Competition Website's public leaderboard. The potential winner(s) are determined solely by the leaderboard ranking on the private leaderboard, subject to compliance with these Rules. The public leaderboard will be based on the public test set and the private leaderboard will be based on the private test set.\n\nIn the event of a tie, the Submission that was entered first to the Competition will be the winner. In the event a potential winner is disqualified for any reason, the Submission that received the next highest score rank will be chosen as the potential winner.\n\n#### **10.\tNOTIFICATION OF WINNERS & DISQUALIFICATION.**\n\nThe potential winner(s) will be notified by email. \n \nIf a potential winner (i) does not respond to the notification attempt within one (1) week from the first notification attempt or (ii) notifies Kaggle within one week after the Final Submission Deadline that the potential winner does not want to be nominated as a winner or does not want to receive a Prize, then, in each case (i) and (ii) such potential winner will not receive any Prize, and an alternate potential winner will be selected from among all eligible entries received based on the Competition’s judging criteria.\n \nIn case (i) and (ii) above Kaggle may disqualify the participant. However, in case (ii) above, if requested by Kaggle, such potential winner may provide code and documentation to verify the participant’s compliance with these Rules. If the potential winner provides code and documentation to the satisfaction of Kaggle, the participant will not be disqualified pursuant to this paragraph.\n \nCompetition Sponsor reserves the right to disqualify any participant from the Competition if the Competition Sponsor reasonably believes that the participant has attempted to undermine the legitimate operation of the Competition by cheating, deception, or other unfair playing practices or abuses, threatens or harasses any other participants, Competition Sponsor or Kaggle.\n \nA disqualified participant may be removed from the Competition leaderboard, at Kaggle's sole discretion. If a Participant is removed from the Competition Leaderboard, additional winning features associated with the Kaggle competition platform, for example Kaggle points or medals, may also not be awarded.\n \nThe final leaderboard list will be publicly displayed at Kaggle.com. Determinations of Competition Sponsor are final and binding.\n\n#### **11.\tWINNERS OBLIGATIONS.**\n\nAs a condition to being awarded a Prize, a Prize winner must fulfill the following obligations:\n\n(a) deliver to the Competition Sponsor the final model's software code as used to generate the winning Submission and associated documentation. The delivered software code should follow [these documentation guidelines][5], must be capable of generating the winning Submission, and contain a description of resources required to build and/or run the executable code successfully. To the extent that the final model’s software code includes generally commercially available software that is not owned by you, but that can be procured by the Competition Sponsor without undue expense, then instead of delivering the code for that software to the Competition Sponsor, you must identify that software, method for procuring it, and any parameters or other information necessary to replicate the winning Submission;\n\n(b) grant to the Competition Sponsor the license to the winning Submission stated in the Competition Specific Rules above, and represent that you have the unrestricted right to grant that license; \n\n(c) sign and return all Prize acceptance documents as may be required by Competition Sponsor or Kaggle, including without limitation: (i) eligibility certifications; (ii) licenses, releases and other agreements required under the Rules; and (iii) U.S. tax forms (such as IRS Form W-9 if U.S. resident, IRS Form W-8BEN if foreign resident, or future equivalents).\n\n#### **12.\tPRIZES.** \n\nPrize(s) are as described on the Competition Website and are only available for winning during the time period described on the Competition Website. The odds of winning any Prize depends on the number of eligible Submissions received during the Competition Period and the skill of the participants. \n\nAll Prizes are subject to Competition Sponsor's review and verification of the participant’s eligibility and compliance with these Rules, and the compliance of the winning Submissions with the Submissions Requirements. In the event that the Submission demonstrates non-compliance with these Competition Rules, Competition Sponsor may at its discretion take either of the following actions: (i) disqualify the Submission(s); or (ii) require the potential winner to remediate within one week after notice all issues identified in the Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).\n\nA potential winner may decline to be nominated as a Competition winner in accordance with Section 10.\n\nPotential winners must return all required Prize acceptance documents within two (2) weeks following notification of such required documents, or such potential winner will be deemed to have forfeited the prize and another potential winner will be selected. Prize(s) will be awarded within approximately 30 days after receipt by Competition Sponsor or Kaggle of the required Prize acceptance documents. Transfer or assignment of a Prize is not allowed. \n\nYou are not eligible to receive any Prize if you do not meet the Eligibility requirements in Section 2 above.\n\nIf a Team wins a monetary Prize, the Prize money will be allocated in even shares between the eligible Team members, unless the Team unanimously opts for a different Prize split and notifies Kaggle before Prizes are issued.\n\n#### **13.\tTAXES.** \n\nALL TAXES IMPOSED ON PRIZES ARE THE SOLE RESPONSIBILITY OF THE WINNERS. Payments to potential winners are subject to the express requirement that they submit all documentation requested by Competition Sponsor or Kaggle for compliance with applicable state, federal, local and foreign (including provincial) tax reporting and withholding requirements. Prizes will be net of any taxes that Competition Sponsor is required by law to withhold. If a potential winner fails to provide any required documentation or comply with applicable laws, the Prize may be forfeited and Competition Sponsor may select an alternative potential winner. Any winners who are U.S. residents will receive an IRS Form-1099 in the amount of their Prize.\n\n#### **14.\tGENERAL CONDITIONS.**  \n\nAll federal, state, provincial and local laws and regulations apply. \n\n#### **15.\tPUBLICITY.**\n\nYou agree that Competition Sponsor, Kaggle and its affiliates may use your name and likeness for advertising and promotional purposes without additional compensation, unless prohibited by law.\n\n#### **16.\tPRIVACY.**\n\nYou acknowledge and agree that Competition Sponsor and Kaggle may collect, store, share and otherwise use personally identifiable information provided by you during the Kaggle account registration process and the Competition, including but not limited to, name, mailing address, phone number, and email address (“Personal Information”). Kaggle acts as an independent controller with regard to its collection, storage, sharing, and other use of this Personal Information, and will use this Personal Information in accordance with its Privacy Policy <[www.kaggle.com/privacy][6]>, including for administering the Competition. As a Kaggle.com account holder, you have the right to request access to, review, rectification, portability or deletion of any personal data held by Kaggle about you by logging into your account and/or contacting Kaggle Support at <[www.kaggle.com/contact][7]>.\n\n As part of Competition Sponsor performing this contract between you and the Competition Sponsor, Kaggle will transfer your Personal Information to Competition Sponsor, which acts as an independent controller with regard to this Personal Information. As a controller of such Personal Information, Competition Sponsor agrees to comply with all U.S. and foreign data protection obligations with regard to your Personal Information. Kaggle will transfer your Personal Information to Competition Sponsor in the country specified in the Competition Sponsor Address listed above, which may be a country outside the country of your residence. Such country may not have privacy laws and regulations similar to those of the country of your residence.\n\n#### **17.\tWARRANTY, INDEMNITY AND RELEASE.** \n\nYou warrant that your Submission is your own original work and, as such, you are the sole and exclusive owner and rights holder of the Submission, and you have the right to make the Submission and grant all required licenses. You agree not to make any Submission that: (i) infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; or (ii) otherwise violates any applicable U.S. or foreign state or federal law.\n\nTo the maximum extent permitted by law, you indemnify and agree to keep indemnified Competition Entities at all times from and against any liability, claims, demands, losses, damages, costs and expenses resulting from any of your acts, defaults or omissions and/or a breach of any warranty set forth herein. To the maximum extent permitted by law, you agree to defend, indemnify and hold harmless the Competition Entities from and against any and all claims, actions, suits or proceedings, as well as any and all losses, liabilities, damages, costs and expenses (including reasonable attorneys fees) arising out of or accruing from: (a) your Submission or other material uploaded or otherwise provided by you that infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; (b) any misrepresentation made by you in connection with the Competition; (c) any non-compliance by you with these Rules or any applicable U.S. or foreign state or federal law; (d) claims brought by persons or entities other than the parties to these Rules arising from or related to your involvement with the Competition; and (e) your acceptance, possession, misuse or use of any Prize, or your participation in the Competition and any Competition-related activity.\n\nYou hereby release Competition Entities from any liability associated with: (a) any malfunction or other problem with the Competition Website; (b) any error in the collection, processing, or retention of any Submission; or (c) any typographical or other error in the printing, offering or announcement of any Prize or winners.\n\n#### **18.\tINTERNET.** \n\nCompetition Entities are not responsible for any malfunction of the Competition Website or any late, lost, damaged, misdirected, incomplete, illegible, undeliverable, or destroyed Submissions or entry materials due to system errors, failed, incomplete or garbled computer or other telecommunication transmission malfunctions, hardware or software failures of any kind, lost or unavailable network connections, typographical or system/human errors and failures, technical malfunction(s) of any telephone network or lines, cable connections, satellite transmissions, servers or providers, or computer equipment, traffic congestion on the Internet or at the Competition Website, or any combination thereof, which may limit a participant’s ability to participate.\n\n#### **19.\tRIGHT TO CANCEL, MODIFY OR DISQUALIFY.**\n\nIf for any reason the Competition is not capable of running as planned, including infection by computer virus, bugs, tampering, unauthorized intervention, fraud, technical failures, or any other causes which corrupt or affect the administration, security, fairness, integrity, or proper conduct of the Competition, Competition Sponsor reserves the right to cancel, terminate, modify or suspend the Competition. Competition Sponsor further reserves the right to disqualify any participant who tampers with the submission process or any other part of the Competition or Competition Website. Any attempt by a participant to deliberately damage any website, including the Competition Website, or undermine the legitimate operation of the Competition is a violation of criminal and civil laws. Should such an attempt be made, Competition Sponsor and Kaggle each reserves the right to seek damages from any such participant to the fullest extent of the applicable law.\n\n#### **20.\tNOT AN OFFER OR CONTRACT OF EMPLOYMENT.**\n\nUnder no circumstances will the entry of a Submission, the awarding of a Prize, or anything in these Rules be construed as an offer or contract of employment with Competition Sponsor or any of the Competition Entities. You acknowledge that you have submitted your Submission voluntarily and not in confidence or in trust. You acknowledge that no confidential, fiduciary, agency, employment or other similar relationship is created between you and Competition Sponsor or any of the Competition Entities by your acceptance of these Rules or your entry of your Submission.\n\n#### **21.\tGOVERNING LAW.** \n\nUnless otherwise provided in the Competition Specific Rules above, all claims arising out of or relating to these Rules will be governed by California law, excluding its conflict of laws rules, and will be litigated exclusively in the Federal or State courts of Santa Clara County, California, USA. The parties consent to personal jurisdiction in those courts. If any provision of these Rules is held to be invalid or unenforceable, all remaining provisions of the Rules will remain in full force and effect.\n\n\n [1]: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx\n [2]: http://www.kaggle.com/terms\n [3]: http://www.opensource.org\n [4]: http://www.opensource.org\n [5]: https://www.kaggle.com/WinningModelDocumentationGuidelines\n [6]: http://www.kaggle.com/privacy\n [7]: http://www.kaggle.com/contact", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "In today’s digital age, problematic internet use among children and adolescents is a growing concern. Better understanding this issue is crucial for addressing mental health problems such as depression and anxiety. \n\n\nCurrent methods for measuring problematic internet use in children and adolescents are often complex and require professional assessments. This creates access, cultural, and linguistic barriers for many families. Due to these limitations, problematic internet use is often not measured directly, but is instead associated with issues such as depression and anxiety in youth. \n\nConversely, physical & fitness measures are extremely accessible and widely available with minimal intervention or clinical expertise. Changes in physical habits, such as poorer posture, irregular diet, and reduced physical activity, are common in excessive technology users. We propose using these easily obtainable physical fitness indicators as proxies for identifying problematic internet use, especially in contexts lacking clinical expertise or suitable assessment tools.\n\nThis competition challenges you to develop a predictive model capable of analyzing children's physical activity data to detect early indicators of problematic internet and technology use. This will enable prompt interventions aimed at promoting healthier digital habits.\n\nYour work will contribute to a healthier, happier future where children are better equipped to navigate the digital landscape responsibly.\n\n### Acknowledgments\n\nThe data used for this competition was provided by the [Healthy Brain Network](https://healthybrainnetwork.org/), a landmark mental health study based in New York City that will help children around the world. In the Healthy Brain Network, families, community leaders, and supporters are partnering with the Child Mind Institute to unlock the secrets of the developing brain. In addition to the generous support provided by the Kaggle team, financial support has been provided by the California Department of Health Care Services (DHCS) as part of the Children and Youth Behavioral Health Initiative (CYBHI).\n\n![Health Care Services Logo](https://storage.googleapis.com/kaggle-media/Images/HCS-logo.png =280x137) \n\n### Sponsorship\n\n**Dell Technologies** and **NVIDIA** are thrilled to partner with the Child Mind Institute, recognizing the profound impact this collaboration will have on advancing mental health support for children and adolescents. This partnership aligns perfectly with our commitment to leveraging technology for social good and fostering a healthier, more inclusive future.\n\n**Dell Technologies** AI solutions from desktop to datacenter to cloud. **NVIDIA** pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society.\n\n
\"Dell \"NVIDIA\"
\n\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Evaluation", "content": "Submissions are scored based on the quadratic weighted kappa, which measures the agreement between two outcomes. This metric typically varies from 0 (random agreement) to 1 (complete agreement). In the event that there is less agreement than expected by chance, the metric may go below 0.\n\nTo compute the quadratic weighted kappa, we construct three matrices, \\\\(O\\\\), \\\\(W\\\\), and \\\\(E\\\\), with \\\\(N\\\\) the number of distinct labels.\n\nThe matrix \\\\(O\\\\) is an \\\\(N \\times N\\\\) histogram matrix such that \\\\(O_{i,j}\\\\) corresponds to the number of instances that have an actual value \\\\(i\\\\) and a predicted value \\\\(j\\\\).\n\nThe matrix \\\\(W\\\\) is an \\\\(N \\times N\\\\) matrix of weights, calculated based on the squared difference between actual and predicted values:\n\n$$W_{i,j} = \\frac{\\left(i-j\\right)^2}{\\left(N-1\\right)^2}$$\n\nThe matrix \\\\(E\\\\) is an \\\\(N \\times N\\\\) histogram matrix of expected outcomes, calculated assuming that there is no correlation between values. This is calculated as the outer product between the actual histogram vector of outcomes and the predicted histogram vector, normalized such that \\\\(E\\\\) and \\\\(O\\\\) have the same sum.\n\nFrom these three matrices, the quadratic weighted kappa is calculated as: \n\n$$\\kappa=1-\\frac{\\sum\\_{i,j}W\\_{i,j}O\\_{i,j}}{\\sum\\_{i,j}W\\_{i,j}E\\_{i,j}}.$$\n\n## Submission File\nFor each `id` in the test set, you must predict the corresponding `sii` (described on the [Data](https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use/data) page). The file should contain a header and have the following format:\n\n```\nid,sii\n000046df,0\n000089ff,1\n00012558,2\n00017ccd,3\n...\n```", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "* **September 19, 2024** - Start Date.\n\n* **${competition.ProhibitNewEntrantsExplicitDeadline}** - Entry Deadline. You must accept the competition rules before this date in order to compete.\n\n* **${competition.TeamMergerExplicitDeadline}** - Team Merger Deadline. This is the last day participants may join or merge teams.\n\n* **${competition.Deadline}** - Final Submission Deadline.\n\nAll deadlines are at 11:59 PM UTC on the corresponding day unless otherwise noted. The competition organizers reserve the right to update the contest timeline if they deem it necessary.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "data-description", "content": "The Healthy Brain Network (HBN) dataset is a clinical sample of about five-thousand 5-22 year-olds who have undergone both clinical and research screenings. The objective of the HBN study is to find biological markers that will improve the diagnosis and treatment of mental health and learning disorders from an objective biological perspective. Two elements of this study are being used for this competition: physical activity data (wrist-worn accelerometer data, fitness assessments and questionnaires) and internet usage behavior data. The goal of this competition is to predict from this data a participant's **Severity Impairment Index** (`sii`), a standard measure of problematic internet use.\n\nNote that this is a [**Code Competition**](https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use/overview/code-requirements), in which the actual test set is hidden. In this public version, we give some sample data in the correct format to help you author your solutions. The full test set comprises about 3800 instances.\n\nThe competition data is compiled into two sources, `parquet` files containing the accelerometer (actigraphy) series and `csv` files containing the remaining tabular data. The majority of measures are missing for most participants. In particular, the target `sii` is missing for a portion of the participants in the training set. You may wish to apply non-supervised learning techniques to this data. The `sii` value is present for all instances in the test set.\n\n## HBN Instruments\n\nThe tabular data in **train.csv** and **test.csv** comprises measurements from a variety of instruments. The fields within each instrument are described in **data_dictionary.csv**. These instruments are:\n\n- `Demographics` - Information about age and sex of participants.\n- `Internet Use` - Number of hours of using computer/internet per day.\n- `Children's Global Assessment Scale` - Numeric scale used by mental health clinicians to rate the general functioning of youths under the age of 18. \n- `Physical Measures` - Collection of blood pressure, heart rate, height, weight and waist, and hip measurements.\n- `FitnessGram Vitals and Treadmill` - Measurements of cardiovascular fitness assessed using the NHANES treadmill protocol.\n- `FitnessGram Child` - Health related physical fitness assessment measuring five different parameters including aerobic capacity, muscular strength, muscular endurance, flexibility, and body composition. \n- `Bio-electric Impedance Analysis` - Measure of key body composition elements, including BMI, fat, muscle, and water content.\n- `Physical Activity Questionnaire` - Information about children's participation in vigorous activities over the last 7 days. \n- `Sleep Disturbance Scale` - Scale to categorize sleep disorders in children. \n- `Actigraphy` - Objective measure of ecological physical activity through a research-grade biotracker.\n- `Parent-Child Internet Addiction Test` - 20-item scale that measures characteristics and behaviors associated with compulsive use of the Internet including compulsivity, escapism, and dependency. \n\nNote in particular the field `PCIAT-PCIAT_Total`. The target `sii` for this competition is derived from this field as described in the data dictionary: `0` for `None`, `1` for `Mild`, `2` for `Moderate`, and `3` for `Severe`. Additionally, each participant has been assigned a unique identifier `id`.\n\n## Actigraphy Files and Field Descriptions\n\nDuring their participation in the HBN study, some participants were given an accelerometer to wear for up to 30 days continually while at home and going about their regular daily lives.\n\n- **series_{train|test}.parquet/id={id}** - Series to be used as training data, partitioned by `id`. Each series is a continuous recording of accelerometer data for a single subject spanning many days.\n - `id` - The patient identifier corresponding to the `id` field in **train/test.csv**.\n - `step` - An integer timestep for each observation within a series.\n - `X`, `Y`, `Z` - Measure of acceleration, in *g*, experienced by the wrist-worn watch along each standard axis.\n - `enmo` - As calculated and described by the [wristpy package](https://github.com/childmindresearch/wristpy), ENMO is the Euclidean Norm Minus One of all accelerometer signals (along each of the x-, y-, and z-axis, measured in g-force) with negative values rounded to zero. Zero values are indicative of periods of no motion. While no standard measure of acceleration exists in this space, this is one of the several commonly computed features.\n - `anglez` - As calculated and described by the [wristpy package](https://github.com/childmindresearch/wristpy), Angle-Z is a metric derived from individual accelerometer components and refers to the angle of the arm relative to the horizontal plane.\n - `non-wear_flag` - A flag (0: watch is being worn, 1: the watch is not worn) to help determine periods when the watch has been removed, based on the [GGIR](https://wadpac.github.io/GGIR/articles/chapter3_QualityAssessment.html#non-wear-detection) definition, which uses the standard deviation and range of the accelerometer data.\n - `light` - Measure of ambient light in *lux*. See [​​here](https://actigraphcorp.my.site.com/support/s/article/Lux-Measurements) for details.\n - `battery_voltage` - A measure of the battery voltage in *mV*.\n - `time_of_day` - Time of day representing the start of a 5s window that the data has been sampled over, with format `%H:%M:%S.%9f`.\n - `weekday` - The day of the week, coded as an integer with 1 being Monday and 7 being Sunday.\n - `quarter` - The quarter of the year, an integer from 1 to 4.\n - `relative_date_PCIAT` - The number of days (integer) since the PCIAT test was administered (negative days indicate that the actigraphy data has been collected before the test was administered).\n\n- **sample_submission.csv** - A sample submission file in the correct format. See the [**Evaluation**](https://www.kaggle.com/competitions/child-mind-institute-problematic-internet-use/overview/evaluation) page for more details.\n\n\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "* 1st Place - $ 15,000\n* 2nd Place - $ 10,000\n* 3rd Place - $ 8,000\n* 4th Place - $ 7,000\n* 5th Place - $ 5,000\n* 6th Place - $ 5,000\n* 7th Place - $ 5,000\n* 8th Place - $ 5,000", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Code Requirements", "content": "\n\n### This is a Code Competition\n\nSubmissions to this competition must be made through Notebooks. In order for the \"Submit\" button to be active after a commit, the following conditions must be met:\n\n- CPU Notebook <= 9 hours run-time\n- GPU Notebook <= 9 hours run-time\n- Internet access disabled\n- Freely & publicly available external data is allowed, including pre-trained models\n- Submission file must be named `submission.csv`\n\nPlease see the [Code Competition FAQ](https://www.kaggle.com/docs/competitions#notebooks-only-FAQ) for more information on how to submit. And review the [code debugging doc](https://www.kaggle.com/code-competition-debugging) if you are encountering submission errors.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "abstract", "content": "Can you predict the level of problematic internet usage exhibited by children and adolescents, based on their physical activity? The goal of this competition is to develop a predictive model that analyzes children's physical activity and fitness data to identify early signs of problematic internet use. Identifying these patterns can help trigger interventions to encourage healthier digital habits.\n\n\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Competition Sponsors", "content": "**Dell Technologies** and **NVIDIA** are excited to sponsor this Kaggle competition, inviting data scientists from around the world to showcase their skills and creativity. Participants are encouraged to leverage NVIDIA’s powerful toolkits and libraries, such as RAPIDS cuDF pandas, and RAPIDS suite, to significantly accelerate their data pre-processing and machine learning workflows.\n\nThese tools, combined with Dell’s high-performance Precision workstations powered by NVIDIA RTX™ Ada Generation GPUs, provide an optimal environment for tackling complex data science challenges.\n\nYou aren’t required to use these advanced technologies for your final solutions, however, please support our sponsors Dell Technologies and NVIDIA by familiarizing yourself with their technology listed below.\n\n**Dell AI-ready Precision workstations**\n\nDell Precision workstations are high-performance computing solutions designed for professionals in fields such as computer-aided design, architecture, and data science. These workstations are available in both desktop and mobile forms, offering powerful processors, NVIDIA RTX Ada Generation GPUs, and substantial memory and storage capacities. They are engineered for reliability and optimized for demanding applications, making them ideal for data science tasks.\n\n[Dell Precision 7960 Tower Workstation](https://www.dell.com/en-us/shop/desktop-computers/precision-7960-tower-workstation/spd/precision-t7960-workstation#features_section)\n\n[Dell Precision 5860 Tower Workstation](https://www.dell.com/en-us/shop/desktop-computers/precision-5860-tower/spd/precision-5860-workstation#features_section)\n\n[Dell Precision 7780 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-17-7780-laptop#features_section)\n\n[Dell Precision 7680 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-16-7680-laptop#features_section)\n\n[Dell Precision 5690 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-16-5690-laptop#features_section)\n\n**NVIDIA RTX Ada Generation GPUs**\n\nNVIDIA RTX Ada Generation GPUs, powered by the Ada Lovelace architecture, are designed to deliver exceptional performance for professional visualization, AI, graphics, and data science workloads. These GPUs feature advanced technologies such as third-generation RT Cores for enhanced ray tracing, fourth-generation Tensor Cores for accelerated AI computations, and CUDA cores for improved single-precision floating-point operations. With substantial memory capacity and efficient processing capabilities, RTX Ada GPUs can handle large datasets and complex models, making them ideal for data science tasks. Their ability to accelerate AI and data processing workflows significantly reduces computation time, enabling data scientists to achieve faster insights and more efficient analyses.\n\nLearn More - [https://www.nvidia.com/en-us/technologies/ada-architecture/](https://www.nvidia.com/en-us/technologies/ada-architecture/)\n\n**NVIDIA RAPIDS** - [https://www.nvidia.com/en-au/deep-learning-ai/software/rapids/](https://www.nvidia.com/en-au/deep-learning-ai/software/rapids/)\n\nNVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and AI libraries designed to enhance the performance of data science workflows. By leveraging the power of GPUs, RAPIDS accelerates data manipulation, machine learning, and graph analytics, significantly reducing the time required for data processing and model training. It integrates seamlessly with popular data science tools like Pandas, scikit-learn, and Apache Arrow, allowing data scientists to utilize familiar APIs while benefiting from substantial speedups. RAPIDS is particularly valuable for data science because it enables faster experimentation, leading to quicker insights and more efficient model development. This acceleration is crucial in handling large datasets and complex computations, making RAPIDS an essential tool for modern data science projects.\n\nGet Started - [https://developer.nvidia.com/rapids](https://developer.nvidia.com/rapids)\n\n**NVIDIA cuDF pandas** - [https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/](https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/)\n\nNVIDIA cuDF pandas is a GPU DataFrame library that provides a pandas-like API for loading, joining, aggregating, filtering, and manipulating data. By leveraging the power of GPUs, cuDF accelerates data processing tasks, making it up to 110x significantly faster than traditional CPU-based methods. This acceleration is particularly beneficial for data scientists working with large datasets, as it reduces the time required for data manipulation and analysis. cuDF pandas integrates seamlessly with other RAPIDS libraries and popular data science tools, allowing users to maintain their existing workflows while benefiting from enhanced performance. Its ability to handle complex computations efficiently makes cuDF pandas an essential tool for modern data science projects.\n\nGet Started - https://github.com/rapidsai/cudf\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }