OMB Individually Reported
Predicting Sparse (Geothermal) Resources Availability by using Machine Learning [2024 INV#WO0000000109195]
Low riskExact public inventory row
Description
developing new ML metrics for evaluating model performance that work with sparse natural resources, addressing the extreme mathematical sparsity of these resources at the regional scale, and engineering new evidence layers to inform modeling workflows
Detailed example
new ML metrics for evaluating model performance
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
increasing the explainability, reproducibility, and accessibility of the assessment modeling process
Controls / human review
ATO: No; PIA: Not published