Perturbation screens often rank genes by effect size, so a gene that changes many transcripts can be mistaken for one that actually controls cell state. We built T-CTRL, an auditable workflow that computes ISCI, our Immune-State Controllability Index, and asks whether functional direction and cross-donor repeatability add information after effect magnitude is already known. In the Marson CD4+ T-cell Perturb-seq screen, the pre-specified full-sample M→M+C test improved recovery of known regulators by +0.357 AUPRC (95% CI [+0.117,+0.538]). A separate, stricter, fully refit leakage-free out-of-fold estimate was +0.215 ([+0.074,+0.560], permutation p=0.010). These are distinct measurements, and we report both. Stress tests deliberately bound the claim. A broad external functional-regulator set fails (ΔAUPRC −0.281); the CAR-T clinical-prediction analysis is NULL; and scGPT corroboration is NOT-EVALUABLE because required inputs were unavailable. Marson CD4+ passes, Schmidt CD4+ and THP-1 are near-misses, and non-immune K562/RPE1 systems fail. The result is therefore a tested scope map, not a universal controller score or target list. T-CTRL ships as a Python CLI, reusable DatasetSpec framework, executable notebook, interactive demo, claim ledger and provenance-bound evidence package, with 151 tests and 21/21 automated release gates.
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