Simple Scikit-learn Models Outperform Jev with 37% Lower Error

Using cheap embedding models paired with sklearn classifiers on labeled data achieves a 37% error reduction compared to Jev. This approach leverages supervised learning to outperform zero-shot decision models in tasks where labeled data is available.