We should rethink the way we publish academic output. Best practices in open-source software development may hold important keys.
When run 'in the wild' by the community, high-level music descriptors may not perform the way they did in the lab.
To what extent can we trust 'ground truth' in supervised machine learning to be a reliable oracle?