diff --git a/docs/source/content/query_strategies/ranked_batch_mode.ipynb b/docs/source/content/query_strategies/ranked_batch_mode.ipynb
index c8fe902..19f3be3 100644
--- a/docs/source/content/query_strategies/ranked_batch_mode.ipynb
+++ b/docs/source/content/query_strategies/ranked_batch_mode.ipynb
@@ -18,7 +18,7 @@
     "\n",
     "$$score = \\alpha(1 - \\Phi(x, X_{labeled})) + (1 - \\alpha) U(x),$$\n",
     "\n",
-    "where $\\alpha = \\frac{|X_{unlabeled}|}{|X_{unlabeled}| + |X_{labeled}|}$, $X_{labeled}$ is the labeled dataset, $U(x)$ is the uncertainty of predictions for $x$, and $\\Phi$ is a so-called similarity function, for instance [cosine similarity](https://en.wikipedia.org/wiki/Cosine_similarity). This latter function measures how well the feature space is explored near $x$. (The lower the better.)\n",
+    "where $\\alpha = \\frac{|X_{labeled}|}{|X_{unlabeled}| + |X_{labeled}|}$, $X_{labeled}$ is the labeled dataset, $U(x)$ is the uncertainty of predictions for $x$, and $\\Phi$ is a so-called similarity function, for instance [cosine similarity](https://en.wikipedia.org/wiki/Cosine_similarity). This latter function measures how well the feature space is explored near $x$. (The lower the better.)\n",
     "\n",
     "After scoring, the highest scored instance is put at the top of a list. The instance is removed from the pool and the score is recalculated until the desired amount of instances are selected."
    ]