{"version":"1.0","type":"rich","title":"Gist 0efb8d4b7f4538ca9efc78832536d0c3","description":"This visualization compares MRIQC automated quality metrics with manual voting results for T1-weighted brain scans. It processes JSON vote data from multiple raters, consolidating their quality assessments into a pandas DataFrame. The example demonstrates how to aggregate and inspect manual quality-control annotations alongside automated MRIQC scores, using pandas for data manipulation and matplotlib for inline plotting in a Jupyter notebook.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-0efb8d4b7f4538ca9efc78832536d0c3?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}