diff --git a/fault_injection_async25.tex b/fault_injection_async25.tex
index 724ab9b..2f7f20c 100644
--- a/fault_injection_async25.tex
+++ b/fault_injection_async25.tex
@@ -390,7 +390,7 @@ The simulation configuration shown in this graph assumed a lower hit-probability
 
 \cref{fig:res/deviation_num_sims_dims,fig:res/deviation_num_sims_nclx} show how observed failure mode distribution changes when the number of injections per signal is decreased. We observe that for both logic styles deviation is less than a single percentage point when going from over 20000 simulations down to about 3000.
 
-\textcolor{red}{ST: Probably more interesting would be a comparison of 4x4 and 8x8 multiplier, as these have}
+\textcolor{red}{ST: Probably more interesting would be a comparison of 4x4 and 8x8 multiplier, as these have largel}
 
 As a similar exercise, we established another baseline test for varying the percentage of signals to be targeted. For this, we configured the injection-engine to select all signals, then gradually lowered the percentage of selected signals (see Figure~\ref{fig:res/deviation_sel_signals_dims} and \ref{fig:res/deviation_sel_signals_nclx}). While not as stable as number of simulations, deviation still stayed within limits down to about 50\%, with the number of glitches observed in \acs{nclx} deviating by about $2.9$ points.