{"version":"1.0","type":"rich","title":"Gist 6fba698cb515db3002754ec29f820b5c","description":"This example demonstrates a workflow for validating musical data extracted from a MusicXML file against a manually created analysis CSV. The visualization compares four representations of a 12-bar trumpet melody—the original MusicXML score, a manual note/dynamics/slur analysis, an extracted text file, and a final JSON—to identify missing notes or performance details. A Python script parses the MusicXML into simplified text, and the JSON is prepared as control data for an AI sound-generation model. The gist highlights discrepancies between the files, treating the manual CSV as the reference, and invites feedback on ambiguities in the JSON annotations.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-6fba698cb515db3002754ec29f820b5c?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}