docs: expand SciPy guard guidance

README.md

@@ -6,14 +6,23 @@ The `toptek/requirements-lite.txt` file pins the scientific stack to keep it
 compatible with the bundled scikit-learn release:
 
 - `scikit-learn==1.3.2`
-- `numpy>=1.21.6,<2.0`
+- `numpy>=1.21.6,<1.28`
 - `scipy>=1.7.3,<1.12`
 
 These ranges follow the support window published by scikit-learn 1.3.x and are
 also consumed transitively by `toptek/requirements-streaming.txt` through its
 `-r requirements-lite.txt` include. Installing within these bounds avoids the
 ABI mismatches that occur with the NumPy/SciPy wheels when using newer major
-releases.
+releases. In particular, upgrading NumPy beyond `<1.28` triggers SciPy's
+runtime guard:
+
+```
+A module that was compiled using NumPy 1.x cannot be run in NumPy 2.x…
+downgrade to numpy<2 or rebuild the module.
+```
+
+This surfaces as an `ImportError` when SciPy loads compiled extensions,
+matching the warning already called out in `toptek/README.md`.
 
 ## Verifying the environment
 
@@ -26,7 +35,13 @@ source .venv/bin/activate
 pip install --upgrade pip
 pip install -r toptek/requirements-lite.txt
 pip check
+python - <<'PY'
+import numpy, scipy
+print(f"NumPy {numpy.__version__}, SciPy {scipy.__version__} ready")
+PY
 ```
 
-The final `pip check` call should report "No broken requirements found",
-confirming that the pinned dependency set resolves without conflicts.
+The final `pip check` call should report "No broken requirements found", and
+the import smoke test should print the installed versions without raising
+errors—confirming that the pinned dependency set resolves without conflicts and
+that SciPy can load its compiled modules.