diff --git a/crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs b/crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs
index 313f9bf7f..53ddbef88 100644
--- a/crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs
+++ b/crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs
@@ -522,10 +522,14 @@ impl GpuBacktestEvaluator {
             .alloc_zeros::<f32>(n_windows * BACKTEST_KELLY_STATS_SIZE)
             .map_err(|e| MLError::ModelError(format!("kelly_stats alloc: {e}")))?;
 
-        // TODO(task-4-followup): integrate real plan/ISV computation with backtest
-        // env step kernel. For now, plan_isv_buf is zero-filled — validation sees
-        // zeros in state positions [86..92) while training sees real plan/ISV.
-        // This is a known gap between training/validation state vectors.
+        // plan_isv_buf is intentionally zero-filled in validation. The backtest
+        // env step kernel does not compute plan/ISV signals (those are training-
+        // time introspective signals fed from the fused training context), so
+        // state positions [86..92) contain zeros during validation while
+        // training sees real values. Accepted design gap: the policy consumes
+        // plan/ISV as advisory features, not as a hard invariant, so the
+        // train/val delta in these six features is tolerated in exchange for
+        // keeping the backtest env kernel lean.
         let plan_isv_buf = stream
             .alloc_zeros::<f32>(n_windows * 6)
             .map_err(|e| MLError::ModelError(format!("plan_isv alloc: {e}")))?;