Utility Wildfire Risk — Model Workspace

Query Explorer Pathway Decomposer Markov Blanket CPT Explorer

Start here

Open the recommended scenario for this case
Adjust observed evidence or intervention settings
Move to a second tool without losing context
Compare obs() versus do() where available
Inspect paths, blankets, or CPT structure to explain the shift

Tools

Why this query explorer matters

Association tells you what tends to go together. Intervention tells you what would happen if you forced a change. Counterfactual tells you what would have happened for a specific case under different circumstances. These are three distinct questions — and they have three distinct answers, even on the same data and the same model.

Rung 1 (obs) leaves all back-door paths open: the model conditions on the evidence and propagates in all directions, mixing causal signal with selection bias. Rung 2 (do) severs the incoming edges to the intervention node, isolating the downstream causal mechanism and eliminating confounding. Comparing the two bars directly quantifies the bias that would arise from treating observational data as causal. Use the tools in the tab bar above to decompose the pathways, quantify the gap, and inspect individual-level background factors.

Model notes

Query setup

Target node

Intervention node

Choose one node to cut and set with do().

Intervention state

Compare target state

Used for the obs() vs do() gap summary.

Observed evidence

Prior target marginal

Observed posterior

Interventional posterior

Gap summary

Network marginals