[Fix] mathjax in metric explanation

app.py

@@ -78,7 +78,7 @@ with gr.Blocks(title="LLM Similarity Analyzer", css=app_util.custom_css) as demo
     )
 
     gr.Markdown("## Information")
-    gr.Markdown("""We propose Chance Adjusted Probabilistic Agreement (\(\operatorname{CAPA}\), or \(\kappa_p\)), a novel metric \
+    gr.Markdown(r"""We propose Chance Adjusted Probabilistic Agreement (\(\operatorname{CAPA}\), or \(\kappa_p\)), a novel metric \
 for model similarity which adjusts for chance agreement due to accuracy. Using CAPA, we find: (1) LLM-as-a-judge scores are \
 biased towards more similar models controlling for the model's capability. (2) Gain from training strong models on annotations \
 of weak supervisors (weak-to-strong generalization) is higher when the two models are more different. (3) Concerningly, model \