Your question is Model Validation With Scarce Data. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you validate a model when ground truth data is scarce or noisy?
Explain a practical evaluation strategy that separates model quality from label uncertainty. Address validation design, uncertainty estimation, error analysis, monitoring, and how you would decide whether the model is ready for deployment.
