deletions | additions       diff --git a/I_asked_colleagues_that_work__.tex b/I_asked_colleagues_that_work__.tex  index c05b9c3..fdaaca8 100644  --- a/I_asked_colleagues_that_work__.tex  +++ b/I_asked_colleagues_that_work__.tex 
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\label{comparetocannon}  \end{table}  The only ROI that does not compare to \cite{cannon2014} is the Thalamus. It is possible that the FIRST algorithm is more reliable at segmenting this structure. I included another table by \cite{jovicich2013brain} whereagain,  sites were not strictly  harmonized, but  different control subjects were scanned at each site, but and  the authors used the same  freesurfer cross-sectional algorithm that we used. Instead of calculating between-site ICC's, they calculated the average within-site ICCs for each ROI. The following table (which is now included in the manuscript) compares our within-site ICC's pre- and post- calibraiton to \cite{jovicich2013brain} average within-site ICC values: \begin{table}   \begin{tabular}{ c c c c } 
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Caud & .97 & .97 & $0.909 \pm 0.092$ \\   \bottomrule  \end{tabular}   \caption{Comparing the within-site ICC before and after leave-one-out scaling factor calibration with the cross-sectional freesurfer results of \cite{jovicich2013brain}, where scanners were standardized, used vendor-provided T1-weighted sequences,  and the average within-site ICC is shown. The within-site ICCs of our study fall within the range of \cite{jovicich2013brain}, which shows the that sites in this study are as reliable as those in \cite{jovicich2013brain}.} \end{table}  Here, we see that the within-site thalamus ICC values fall within the range of \cite{jovicich2013brain}, along with the other ROIs.