Responsible AI
Responsible use means keeping AI assistance, graph analytics, and human interpretation visibly separate.
Human Review
AI-assisted coding or interpretation must remain reviewable by researchers. Unreviewed AI-coded evidence should stay flagged and should not support strong contribution or assessment claims.
Method Limits
A_fusion is a typed adjacency object for observed relations. It is not a causal model, an automatic learner assessment, or proof that visual distances are statistically interpretable.
Evidence Traceability
Every figure or export used for research interpretation should carry model parameters, normalization, runtime provenance, evidence snippets, coding reliability status, and claim-readiness status.
Fair Use of Outputs
Use SENA outputs to support researcher reflection and transparent analysis, not to label students, rank participants across types, or replace contextual educational judgment.