CISR24 / docs /SHORTCUT_AUDIT.md
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CISR24 shortcut audit protocol

The shortcut audit is a risk disclosure, not proof that no shortcut exists. It reports non-trivial low-dimensional predictability even when it remains insufficient for the full 24-class task.

Fixed protocol

  • deterministic audit seed 20260722;
  • train-to-test evaluation with no test-time tuning;
  • 100 records per class/SNR from train and test;
  • 50,400 train and 50,400 test records over all 21 SNR levels;
  • hash-ranked sampling, never the first manifest rows;
  • class and superclass accuracy, balanced accuracy, and macro-F1;
  • aggregate and per-SNR metrics;
  • nearest centroid, multinomial logistic regression, and shallow random forest;
  • normalized mutual information with 200 label permutations.

Feature views

record-only uses only the complete 1024-sample I/Q record. Manifest fields are used for labels and grouping, never as classifier inputs.

metadata-assisted uses true active support and active-len. It is explicitly reported as a privileged-information upper bound, not a realistic model input. Separate metadata-only lookups report active-len and [start-offset, active-len] leakage across train and test.

Published artifacts

The release contains compressed per-sample features, exact train/test caches, model metrics, per-SNR metrics, confusion matrices, mutual information, class/superclass distribution summaries, and PNG/PDF figures under audit/shortcut/. Chance baselines are 1/24 for fine classes and 1/3 for balanced superclass accuracy; raw superclass majority accuracy is 10/24.

High observable-feature accuracy is disclosed rather than hidden because bandwidth, envelope, and spectral peaks are genuine waveform properties. The predeclared active-support thresholds remain quality-control gates; other shortcut metrics are reported as risk evidence and must not be summarized only as "insufficient to solve."