Dimension Elicitor

Menu path: Hellixia > Dimension Elicitor

What it does

Identifies relevant dimensions of a subject and can add them as nodes with comments and classes.

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

• Keyword-based exploration
• Survey-item ideation
• Semantic scaffolding

Inputs

• Keywords
• Optional selected nodes
• Optional General Context

Outputs

• Dimension nodes
• Node comments
• Optional classes

Step-by-Step Workflow

1. Prepare the network, source material, selected nodes, selected arcs, or Knowledge Files required by the function.
2. Confirm that Hellixia provider settings and model access are configured.
3. Open Hellixia > Dimension Elicitor.
4. Review the available options and add General Context when the model needs domain-specific guidance.
5. Run the function and inspect the generated graph, comments, priors, embeddings, translations, or images.
6. 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.

Related Functions

• Embedding Generator
• Semantic Variable Clustering
• Automatic Semantic Network Generator

Examples

• Animals — Dimension elicitation, Semantic Network, or enriched comments
• Tutorials and Webinars — Multiple Hellixia artifacts