Update docs/source/tutorials/datalab/workflows.ipynb

Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com>

docs/source/tutorials/datalab/workflows.ipynb

@@ -325,11 +325,11 @@
    "metadata": {},
    "source": [
     "### 4. (Optional) Visualize Data Valuation Scores\n",
-    "Finally, we will visualize the data valuation scores using a strip plot to understand the distribution across different labels.\n",
+    "Let's visualize the data valuation scores across our dataset.\n",
     "\n",
-    "A score below 0.5 indicates a negative contribution to the model's training performance, while a score above 0.5 indicates a positive contribution.\n",
+    "Cleanlab's Shapely scores are transformed to lie between 0 and 1 such that: a score below 0.5 indicates a negative contribution to the model's training performance, while a score above 0.5 indicates a positive contribution.\n",
     "\n",
-    "By examining the scores across different labels, we can identify whether positive or negative contributions are disproportionately concentrated in a single class. This can help us detect potential biases in the training data."
+    "By examining the scores across different classes, we can identify whether positive or negative contributions are disproportionately concentrated in a single class. This can help detect biases in the training data."
    ]
   },
   {