Model Validation Metrics
Transparency and EvidenceEssentialAppliedNeeds source verification
Definition
The set of performance measurements used to evaluate a model, including accuracy, recall, precision, f1-score, ROC AUC, and others.
Context
Researchers
Example
We must review all model validation metrics before deciding on model deployment
Professional scenario
A clinical team checks sensitivity and false-alert burden before using a risk score.
Governance implication
Use metrics relevant to clinical harms and deployment context.
Question to ask
What errors matter most for our patients and workflow?
Relevant to
AI / IT, Data Scientist, Healthcare Leader, ML Engineer, Nurse, Pharmacist, Physician, Researcher (Suggested — not reviewed)
Source: Excel column 2; ubitiquos_lang.pdf
Verification: Not independently verified
Version 0.1-draft · AI-GLOSS-0178