This example shows the prediction results of a machine learning model that classifies paper abstracts into IEEE Vis conference tracks (InfoVis, SciVis, VAST, or Vis). The interface displays the predicted category, the model’s accuracy, and bar charts for macro and weighted average precision, recall, and F1-score. The charts include an uncertainty value derived from the accuracy metric. Built with a Flask and Jinja backend, the page uses D3.js with a custom `uvis.barChart()` API that applies a gradient type, while the classification report is passed from Python’s scikit-learn into JavaScript for rendering.