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Grading rubrics for AI output quality
39 documents available**AI for Social Good Hackathon – SUST 2026**
module_title: Data Science and Machine Learning
**Team Name:** BC Hub
This document defines the scoring criteria for evaluating Reddit post/rumour virality potential. Each attribute is scored from **0.0 (no presence)** to **1.0 (very strong)**. These scores are used by the LLM to grade injected rumours before simulation.
This rubric defines a **standardised metric** for evaluating how well a software repository implements core **kernel** and **operating‑system (OS)** primitives. It is based on the function manifest and status report from the Echo.Kern project and draws on general operating‑system principles ([Wikipedia: Kernel](https://en.wikipedia.org/wiki/Kernel_(operating_system)#:~:text=operating%20system%20%20that%20always,for%20the%20central%20processing%20unit)). The goal is to provide a repeatable method
The goal of a Qualifying Exam ("qual") is for a student to *effectively demonstrate that they have the knowledge and skills that will be needed to conduct meaningful research in their chosen subfield*. There are a number of key phrases in this sentence:
**Team Name:** [Byte Peeps]
1. **Curiosity Gap (0–2)**
