Verifier-Faithful In-Kernel Machine Learning for Network Intrusion Detection: generated results data

The data generated in the study Verifier-Faithful In-Kernel Machine Learning for Network Intrusion Detection: the per-configuration result summaries and raw per-trial outputs underlying every figure and table in the article, together with the locked content-hashed (SHA-256) experiment calibration under which they were produced. Every value regenerates end to end from the study's open implementation under this calibration and the recorded per-cell random seeds. The seven public benchmark datasets used as input (NSL-KDD, UNSW-NB15, CIC-IDS2017, CIC-IDS2018, 5G-NIDD, ToN-IoT, NF-UNSW-NB15-v2) are listed with their canonical sources in the article's Data availability statement.