Causal Network Generator
Menu path: Hellixia > Causal Network Generator
What it does
Generates a Causal Bayesian Network or Risk-Centric Causal Network from the current context.
Treat Hellixia output as a structured starting point for analyst review, expert refinement, learning, inference, or communication. Generated causal directions and quantification should be checked before they are used operationally.
When to use it
- Causal model bootstrapping
- risk-centric model generation
Inputs
- Prompt, selected nodes, or General Context
Outputs
- Nodes
- causal arcs
- causal effects
- conditional probability tables
- root priors
Step-by-Step Workflow
- Prepare the network, source material, selected nodes, selected arcs, or Knowledge Files required by the function.
- Confirm that Hellixia provider settings and model access are configured.
- Open
Hellixia > Causal Network Generator. - Review the available options and add General Context when the model needs domain-specific guidance.
- Run the function and inspect the generated graph, comments, priors, embeddings, translations, or images.
- Edit the output in BayesiaLab before using it for analysis, publication, or decision support.
Review Guidance
Check whether the generated labels, relationships, comments, classes, probabilities, or causal effects match the source material and expert understanding. For causal outputs, verify that the proposed direction and mechanism are plausible and that no important confounder or alternative explanation has been hidden by the generated structure.