Overview
The VRIFY Prospectivity Score (VPS) is a core output of a DORA Prediction Map. It represents the AI model’s calculated probability of finding your desired commodity, at your specified grades, within the Area of Interest (AOI). The VPS helps geoscientists visually interpret mineral potential across a project site, supporting data-driven exploration decisions.
How the VPS Works
To generate a VPS, you must complete the six-step Prediction Map workflow in DORA.
The VPS is then visualized as a heatmap in the view panel, showing a gradient of scores across the AOI:
Higher VPS values indicate stronger patterns consistent with known mineral systems.
Lower VPS values suggest barren ground or areas with minimal exploration potential.
VPS values range from 0 to 1:
Above 0.5 = potential mineralized ground (positive prediction)
Below 0.5 = likely barren ground (negative prediction
Interpreting the VPS in the Map View
In the final Identify Targets step, the VPS is used to generate and display exploration targets. You can refine how these scores are displayed using the Target VPS Threshold slider in the lower left of the screen:
Slide right to filter and highlight only the highest scoring zones (ideal for pinpointing top exploration targets)
Slide left to include areas with moderate scores (helpful for a broader, more inclusive view of mineral potential)
The VPS map may also include color-coded target clusters, which group high-scoring zones based on spatial and data-driven relationships. These clusters can help you see how different data types (e.g., geophysics, geochemistry, structural features) influence predictions in different zones of your AOI.
It’s important to note that VPS results will vary based on:
The quality and quantity of your input data
The commodity and grade thresholds selected
How the Prediction Map is configured
In some cases, the VPS will highlight clear, actionable targets. In others, it may surface areas for further investigation (even outside known zones) based on the AI’s analysis of available data.
Adjusting Target Settings
You can further refine how VPS results are grouped into targets using these parameters:
Minimum Group Size: Controls the spatial extent needed to form a target cluster.
Minimum Number of Points in Group: Sets how many high-scoring points are required to validate a cluster as a target.
Adjusting these settings helps tailor the target detection process to your project's scale and exploration strategy.
Collaborative Use and Variability
Multiple Prediction Maps and their VPS outputs can be compared on a single Prediction Map with the Compare Experiments option. This enables multiple hypotheses to be tested across various configurations.
Learn More
Still Have Questions?
Reach out to your dedicated VRIFY contact or email support@VRIFY.com for more information.