<h3>MVL Output Overview</h3>

The MVL tool generates a **Summary Table** and an **Improvement Table** for each unique Scope × Response combination:

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<summary><strong>▶ Summary Table</strong></summary>

Displays MVL score and lower-level metrics that contribute to it (i.e., Fidelity, Referent Authority, and Scope Coverage)

<ul>
<li><strong>MVL:</strong> The Model Validation Level of the model for a given response and scope. This is the main output of the MVL tool</li>
<li><strong>MVL~a~:</strong>  An "accuracy only” MVL which only accounts for the accuracy element of fidelity</li>
<li><strong>MVL~v~:</strong> A “variability only” MVL which only accounts for the variability element of fidelity</li>
<li><strong>No. of Validation Points:</strong> The number of distinct combinations of factor settings which contain sufficient data to calculate fidelity and validate the model</li>
<li><strong>Average Fidelity:</strong> The average fidelity score among validation points, on a scale from 0 to 1</li>
<li><strong>Average f~a~:</strong> The average “accuracy only” fidelity score among validation points, on a scale from 0 to 1</li>
<li><strong>Average f~v~:</strong> The average “variability only” fidelity score among validation points, on a scale from 0 to 1</li>
<li><strong>Average Authority Level:</strong> The average authority level among validation points, on a 9 point scale</li>
<li><strong>Coverage:</strong> The coverage score of the model, on a scale from 0 to 1</li>
<li><strong>C~V~:</strong>  The volume component of the model’s coverage score, on a scale from 0 to 1. Reported only when all factors are continuous</li>
<li><strong>C~D~:</strong> The density component of the model’s coverage score, on a scale from 0 to 1. Reported only when all factors are continuous</li>
<li><strong>C~t~:</strong> The categorical coverage for t-way combinations. E.g., C2 reports the fraction of 2-way categorical combinations that are covered with validation points. Reported when any factors are categorical</li>
<li><strong>Average C~V~:</strong>  : The average of C~V~ scores calculated for each categorical combination, on a scale from 0 to 1. Reported only when factors are a mix of continuous and categorical</li>
<li><strong>Average C~D~:</strong> The average of C~D~ scores calculated for each categorical combination, on a scale from 0 to 1. Reported only when factors are a mix of continuous and categorical</li>
</ul>
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<summary><strong>▶ Improvement Table</strong></summary>

Displays:
  1. Maximum achievable MVL score if a metric were “perfect”
  2. Improvement relative to current MVL results

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<summary><strong>▶ Frequently Asked Questions</strong></summary>

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<summary>▶ Why is MVL = 0?</summary>

- **No validation points were found**  
  Check that factor and response names match exactly across all input files
  
- **Fidelity is zero**  
If fidelity is zero, there may be very poor accuracy or match in variability

- **Coverage is zero**  
  The validation points found do not sufficiently cover the scope

- **Model variability is missing**  
  Consider running an Accuracy-Only MVL (MVLa) instead

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<summary>▶ Why is MVL = NaN?</summary>

- This is typically a "divide by zero" error when the tool cannot calculate referent variability (e.g., no replicates or standard deviation provided).  
- If `fa` is a number but `fv` is `NaN`, run an Accuracy-Only MVL (MVL~a~) instead

</details>

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For further guidance on MVL output interpretation, please reference the User Guide