churn.py emits a seed-deterministic kill/spawn schedule (pure data — no real VM
spin/kill; the live fabric half stays gated by the containment law). selector.py
consumes the schedule and rebuilds a circuit whenever a kill drops one of its
hops, across static | random | agent strategies; the paid frontier-model agent
arm (GOAL envelope (c)) is human-gated and NOT wired — the agent strategy here is
a local stability heuristic that spends nothing. analysis/metrics.py aggregates
the four DV families (RQ1 correlation AUC, RQ2 entropy bits, RQ3 throughput
retention + rebuild-classifier AUC) into a schema-valid, write-once metrics.json.
Acceptance check green: under a fixed churn seed the selector rebuilds every
dropped circuit (every_drop_rebuilt, all strategies) and metrics.json is
produced. Python R7 selector suite 11 passed; full SOR suite 92 passed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Land only the offline-validatable half of R7 (instrument-validation gate items
3 and 4): the detectors the gate calibrates on synthetic fixtures, never on
confirmatory-cell data. Pure stdlib functions over in-memory series — no pcaps,
no engine, no traffic, no VM fabric.
- analysis/detectors.py: shannon_entropy_bits (RQ2 anonymity-set entropy),
pearson/score_matrix/auc/linkage_auc, bridge_correlation_auc (RQ1
linkability scorer), and synthetic_bridge_fixture (seed-deterministic
known-linked / known-unlinked ground truth via the R1 SorRng).
Calibration green: entropy returns exactly log2(N) for N equiprobable senders
(gate item 4); a known-linked control pair scores AUC=1.0 and the unlinked
estimator is unbiased at chance (ensemble mean over 40 seeds = 0.498 ~ 0.5,
gate item 3). Detectors are calibrated on synthetic fixtures only — no fitting.
The traffic-moving R7 pieces (churn.py VM spin/kill, live selector rebuild loop,
metrics.json emission) are HELD for R4/R6 + a live grid and are absent here.
Python SOR suite 66 passed.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
leetcrypt