When using experimental scores for the synthetic dataset, we initially forgot to normalize prize values between 0 and 1. This oversight caused confusion and failures in specific algorithms in SPRAS, because the weights were between 0 and 1000. To prevent this issue and confusion, we should add a validation step that checks whether all wegiht values fall within the [0, 1] range for the networks. If any values fall outside this range, the workflow should halt and return a clear error message indicating the actual minimum and maximum weight values detected (e.g., “Error: Rank values must be in [0, 1] for input networks. Detected range: [x, y]”).