diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml
index c9f5aa1f73..2cc2948a16 100644
--- a/.github/workflows/ci.yaml
+++ b/.github/workflows/ci.yaml
@@ -41,7 +41,7 @@ jobs:
           miniforge-version: latest
           python-version: ${{ matrix.python-version }}
           activate-environment: test-environment
-          mamba-version: "*"
+          mamba-version: "1.5.10"
           channels: conda-forge
 
       - name: Set cache environment variables
diff --git a/satpy/readers/seviri_base.py b/satpy/readers/seviri_base.py
index ace63e3f12..1a98dda098 100644
--- a/satpy/readers/seviri_base.py
+++ b/satpy/readers/seviri_base.py
@@ -153,9 +153,21 @@
       scn['IR_108']['y'] = mi
       scn['IR_108'].sel(time=np.datetime64('2019-03-01T12:06:13.052000000'))
 
-* Raw metadata from the file header can be included by setting the reader
-  argument ``include_raw_metadata=True`` (HRIT and Native format only). Note
-  that this comes with a performance penalty of up to 10% if raw metadata from
+* HRIT and Native readers can add raw metadata from the file header, such
+  as calibration coefficients, to dataset attributes. Use the reader keyword
+  argument ``include_raw_metadata``. Here's an example for extracting
+  calibration coefficients from Native files.
+
+  .. code-block:: python
+
+       scene = satpy.Scene(filenames,
+                           reader='seviri_l1b_native',
+                           reader_kwargs={'include_raw_metadata': True})
+       scene.load(["IR_108"])
+       mda = scene["IR_108"].attrs["raw_metadata"]
+       coefs = mda["15_DATA_HEADER"]["RadiometricProcessing"]["Level15ImageCalibration"]
+
+  Note that this comes with a performance penalty of up to 10% if raw metadata from
   multiple segments or scans need to be combined. By default, arrays with more
   than 100 elements are excluded to limit the performance penalty. This
   threshold can be adjusted using the ``mda_max_array_size`` reader keyword
@@ -164,8 +176,8 @@
   .. code-block:: python
 
        scene = satpy.Scene(filenames,
-                          reader='seviri_l1b_hrit/native',
-                          reader_kwargs={'include_raw_metadata': True,
+                           reader='seviri_l1b_native',
+                           reader_kwargs={'include_raw_metadata': True,
                                          'mda_max_array_size': 1000})
 
 References: