Once your Prediction Map is generated, the VRIFY Prospectivity Score (VPS) helps you identify and evaluate areas of potential mineralization across your AOI.

This article explains how to interpret VPS values and use them to define and refine exploration targets.

The VPS is a probability score ranging from 0 to 1.0, displayed as a heatmap across the AOI. Higher values indicate stronger similarity to known mineralization patterns, while lower values indicate weaker similarity.

As a general guideline:

These thresholds are not fixed and should be interpreted in the context of your project and data.

Before adjusting the threshold or generating target groups, consider toggling your learning points back on and overlaying them with the VPS map. Your known mineralized (positive) points should sit within the highest-scoring areas of the VPS. This gives you confidence that the model is correctly identifying its training data.

Areas of high VPS with no learning points nearby could potentially be exploration targets — the model is identifying areas that share characteristics with your known mineralization, but that you haven't yet sampled or drilled. As an additional check, you can cross-reference these areas against any historical mineral occurrences or workings that weren't included as learning points to help assess whether the results are geologically meaningful.

Use the VPS threshold slider in the lower left of the map to control which areas are highlighted. You can switch between the Surface VPS and Sub-surface VPS:

This allows you to move between selective targeting (area of higher confidence) and exploratory analysis (broader coverage).

Use the Create Target Groups tool to organize high-VPS areas into clusters.

This helps you identify coherent zones of prospectivity, organize targets across your project area, and understand which features are driving each group.

You can adjust grouping parameters to match your project scale and exploration strategy.

Use the Compare Experiments tool to evaluate how VPS results change across different model configurations.

This helps you test geological hypotheses, compare feature selections, and assess the impact of different inputs.
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Reach out to your dedicated DORA contact or email support@VRIFY.com for more information.