# OFFICIAL RULES – Predict Planet Settlement Success

**ENTRY IN THIS COMPETITION CONSTITUTES ACCEPTANCE OF THESE RULES.**

**Predict Planet Settlement Success** is a skills-based data science competition hosted on Kaggle for educational purposes. Participation is open to the public. Students enrolled in **T81-558** and **T81-559: Applications of Generative Artificial Intelligence** at Washington University in St. Louis may use this competition to fulfill course requirements.

By registering for and submitting to this Competition, you agree to these Official Competition Rules and Kaggle’s platform terms.

**No monetary prizes are offered.**

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# 1. Competition Information

## Competition Title  
Predict Planet Settlement Success

## Host  
Jeff Heaton  
Washington University in St. Louis  

Courses:
- T81-558  
- T81-559: Applications of Generative Artificial Intelligence  

## Competition Website  
https://www.kaggle.com/competitions/[INSERT]

## Purpose  

This competition is designed to develop and assess:

- Predictive modeling skills  
- Reproducible machine learning workflows  
- Responsible use of external data and AI tools  
- Clear methodological documentation  

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# 2. Eligibility

The Competition is open to the public.

Students enrolled in T81-558 or T81-559 may participate individually or in teams consistent with course policies.

Only enrolled students will receive academic credit.

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# 3. Team Rules

- Maximum team size: Five (5) participants.  
- Students may not participate on multiple teams.  
- Public participants are not subject to university grading policies but must follow all Competition rules.  
- Team mergers must comply with Kaggle platform limits and timeline deadlines.  

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# 4. Submission Limits

- Maximum of five (5) submissions per day.  
- Up to two (2) final submissions may be selected.  
- The public leaderboard reflects interim performance.  
- Final evaluation may use a private leaderboard.  

For enrolled students, leaderboard ranking alone does **not** determine course grade.

Grading may additionally consider:

- Code quality  
- Documentation clarity  
- Reproducibility  
- Methodological rigor  
- Written analysis submitted via Canvas  

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# 5. Competition Data

## A. Data Use

Competition Data may be used for:

- Participation in this Competition  
- Academic coursework  
- Research or portfolio purposes  

Participants may not:

- Share hidden test labels  
- Attempt to reverse engineer private evaluation data  
- Exploit data leakage  

## B. Data Security

Participants agree not to redistribute raw Competition Data in violation of Kaggle’s platform policies.

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# 6. External Data and AI Tools

External data is permitted.

Participants may use:

- Public datasets  
- Pretrained models  
- Large language models  
- AutoML systems  
- Cloud computing platforms  
- Any AI tools  

There are **no restrictions on AI usage** in this Competition.

However:

- All external data sources must be disclosed.  
- Usage must comply with applicable licenses.  
- No proprietary or illegally obtained data may be used.  
- Submissions must remain reproducible.  

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# 7. Reproducibility Requirement (For Enrolled Students)

Students enrolled in T81-558 or T81-559 must submit via Canvas:

- Complete source code  
- Clear training and inference instructions  
- Description of model architecture and methodology  
- Disclosure of all external data and tools used  

Submissions that cannot be reasonably reproduced may receive reduced credit regardless of leaderboard score.

Public participants are encouraged, but not required, to provide reproducibility materials.

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# 8. Academic Integrity (Washington University Students)

Students enrolled at Washington University in St. Louis are subject to the University’s academic integrity policies:

https://students.wustl.edu/academic-integrity/

Violations may result in:

- Disqualification for grading purposes  
- Course penalties  
- Referral under University academic misconduct procedures  

Public participants are not subject to university disciplinary processes but must follow Kaggle’s platform rules.

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# 9. Intellectual Property

Participants retain ownership of their submissions.

By participating, you grant the Host a non-exclusive right to:

- Review submissions for grading purposes  
- Retain submissions for academic evaluation  
- Use anonymized results for teaching or demonstration purposes  

No commercial rights are claimed.

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# 10. Disqualification

The Host reserves the right to disqualify submissions for:

- Data leakage  
- Fraudulent leaderboard manipulation  
- Rule violations  
- Violations of Kaggle platform policies  

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# 11. Rule Modifications

The Host may clarify or modify rules during the Competition if necessary to preserve fairness or educational integrity.