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Documentation Index

Fetch the complete documentation index at: https://cors-lau.vercel.app/docs/llms.txt

Use this file to discover all available pages before exploring further.

The Dashboard is the first screen you see when you open CORS. It surfaces the four most important system metrics as KPI cards, provides a direct entry point to the Recommendation Engine, and shows live system status — confirming the platform is running and ready before you begin academic planning.

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KPI cards

The top row of the Dashboard displays four metric cards that summarize the current state of your institutional data and ML model.
Shows the total number of validated courses currently registered in the academic year catalog. The badge reads Active, confirming that the catalog has been successfully loaded and is ready for analysis.
Displays the total number of enrollment records that have been processed across all departments. A larger record count gives the ML model more signal to work with, improving prediction reliability. The badge reads Sync to indicate the records are up to date.
Reports the Area Under the ROC Curve as a percentage — a measure of how well the ML model discriminates between courses that should be offered and those that should not. A higher percentage indicates stronger model discrimination power.
Before you run your first analysis, this card shows N/A with a Pending badge. The value populates automatically after you execute an analysis from the Recommendation Engine.
Shows the historical percentage of failing grades recorded across all course offerings in the dataset. This global baseline is one of the inputs the model uses when estimating future course difficulty and demand.

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System status indicator

In the top-right corner of the page header, a pulsing green dot and the label System Operational confirms that the backend API and database are reachable and all services are running normally.
If the system status indicator is absent or shows an error state, check that the CORS backend API is running and accessible before attempting an analysis.

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Action banner

Below the KPI cards, a full-width banner titled “Predictive Academic Planning for the Next Semester” summarizes the purpose of the platform and provides a single-click entry point to start the planning workflow.
1

Review KPI cards

Confirm that the Course Catalog and Historical Data counts look correct for your institution. These numbers directly affect prediction quality.
2

Check model status

If the Model ROC-AUC card shows N/A / Pending, you will need to run an analysis at least once before the metric appears.
3

Click 'Initiate Recommendation'

Press the button in the action banner to navigate directly to the Recommendation Engine and begin configuring your next-semester predictions.
The lower section of the Dashboard contains quick-navigation cards for every major section of CORS. You can reach the Recommendation Engine, Prerequisite Topology viewer, and Timetable Orchestration scheduler directly from here without using the sidebar.