Causal Semantic Diagram Generator
Menu path: Hellixia > Causal Semantic Diagram Generator
What it does
Builds a graph of causal semantic relationships from selected model text or contextual material.
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 mechanism sketches
- pre-model causal diagrams
- hypothesis generation
Inputs
- Selected node names, long names, comments, or supplied text
- optional General Context
Outputs
- Causal Semantic Diagram
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 Semantic Diagram 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.