diff --git a/tests/dsl_constant_derived.rs b/tests/dsl_constant_derived.rs
index 295ea377..9ac6989d 100644
--- a/tests/dsl_constant_derived.rs
+++ b/tests/dsl_constant_derived.rs
@@ -1,5 +1,6 @@
 //! A derived assignment whose value folds to a compile-time constant must still
-//! be materialised, because other statements read it by slot.
+//! be materialised, because other statements read it by slot, and it must be
+//! read back as a real whether the reader is an output or a derivative.
 
 #![cfg(feature = "dsl")]
 
@@ -22,6 +23,31 @@ fn prediction(
     Ok(predictions.predictions()[0].prediction())
 }
 
+// The subject must carry an observation at the model start (`t = 0`) for the
+// integration to be anchored there, matching the single-point helper above.
+fn predictions_at(
+    model_source: &str,
+    params: &[(&str, f64)],
+    times: &[f64],
+) -> Result<Vec<f64>, Box<dyn std::error::Error>> {
+    let model = compile_module_source_to_runtime(model_source, Some("const_derived"), |_, _| {})?;
+    let support_point = Parameters::with_model(&model, params.iter().copied())?;
+    let mut builder = Subject::builder("const_derived");
+    for time in times {
+        builder = builder.missing_observation(*time, "cp");
+    }
+    let subject = builder.build();
+    let predictions = model
+        .estimate_predictions(&subject, &support_point)?
+        .into_subject()
+        .ok_or("expected subject predictions")?;
+    Ok(predictions
+        .predictions()
+        .iter()
+        .map(|prediction| prediction.prediction())
+        .collect())
+}
+
 const CONSTANT_DERIVED: &str = r#"
 name = const_derived
 kind = ode
@@ -126,3 +152,83 @@ fn constant_branch_conditional_is_read_correctly() -> Result<(), Box<dyn std::er
     assert!((value - 1.0).abs() < 1e-9, "got {value}");
     Ok(())
 }
+
+// A whole-number derived value read by a derivative, not by an output: the
+// rate constant must stay 1.0 rather than the bit pattern of 1.0.
+const WHOLE_NUMBER_DERIVED_RATE: &str = r#"
+name = const_derived
+kind = ode
+
+params = p1, p2
+states = central
+outputs = cp
+
+z1 = 1.0
+
+init(central) = 2.0
+
+dx(central) = -z1 * central
+
+out(cp) = central
+"#;
+
+// The reported shape: whole-number derived branches feeding a conditional that
+// scales a derivative.
+const WHOLE_NUMBER_DERIVED_IN_CONDITIONAL: &str = r#"
+name = const_derived
+kind = ode
+
+params = p1, p2
+states = central, effector
+outputs = cp
+
+max_r = 1.0
+min_r = 0.001
+r = if (central > 0.0) max_r else min_r
+
+init(central) = 2.0
+init(effector) = 0.0
+
+dx(central) = 0.0
+dx(effector) = r * central - effector
+
+out(cp) = effector
+"#;
+
+#[test]
+fn whole_number_derived_scales_a_derivative_correctly() -> Result<(), Box<dyn std::error::Error>> {
+    let values = predictions_at(
+        WHOLE_NUMBER_DERIVED_RATE,
+        &[("p1", 4.25), ("p2", 1.0)],
+        &[0.0, 1.0, 2.0],
+    )?;
+    for (value, time) in values.iter().zip([0.0f64, 1.0, 2.0]) {
+        let expected = 2.0 * (-time).exp();
+        assert!(
+            (value - expected).abs() < 1e-4,
+            "got {value}, expected {expected}"
+        );
+    }
+    Ok(())
+}
+
+#[test]
+fn whole_number_derived_in_a_conditional_scales_a_derivative_correctly(
+) -> Result<(), Box<dyn std::error::Error>> {
+    let values = predictions_at(
+        WHOLE_NUMBER_DERIVED_IN_CONDITIONAL,
+        &[("p1", 4.25), ("p2", 1.0)],
+        &[0.0, 1.0, 2.0],
+    )?;
+    // `central` is held at 2.0 and the conditional selects `max_r` (1.0), so
+    // `effector(t) = 2 * (1 - exp(-t))`. A bit-pattern read would put `max_r`
+    // at 4.607e18 and drive `effector` there instead.
+    for (value, time) in values.iter().zip([0.0f64, 1.0, 2.0]) {
+        let expected = 2.0 * (1.0 - (-time).exp());
+        assert!(
+            (value - expected).abs() < 1e-4,
+            "got {value}, expected {expected}"
+        );
+    }
+    Ok(())
+}