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\subsection{GMC properties}  We characterize the properties of the extracted clouds in the CO data to assess whether we are identifying clouds that can be compared to GMCs seen in the Milky Way, or whether the emission structures in the M83 data are better described as Giant Molecular Associations (GMAs), which are larger scale structures of molecular gas (Rand et al.).   We identify molecular clouds in the the CO emission line data using the CPROPS algorithm (Rosolowsky & Leroy, 2006)\footnote{We use the \texttt{cpropstoo} implementation at \url{http://github.com/akleroy/cpropstoo}}. We utilize their recommended algorithm for identifying GMCs in interferometer data described as follows. The algorithm first calculates a spatially and varying estimate of the noise in the map by calculating the rms ($\sigma(\alpha,\delta)$) of signal-free channels. Emission is then identified as those pixels in the (three-dimensional) data cube that are larger than $4\sigma(\alpha,\delta)$ in two adjacent velocity channels. This emission mask is then extended to include all connected pixels which are larger than $2\sigma(\alpha,\delta)$ in two three  adjacent channels. The masked emission is then divided into individual molecular clouds using a seeded watershed algorithm, with individual clouds being defined by local maxima that are separated by at least XXX pc spatially or XXX km/s in projected velocity. Any pair of local maxima in the same contiguous region of the mask are also required to be at least XXX K above the saddle point of emission connecting those maxima. We determine the macroscopic properties of the GMCs in the system by calculating moments of the emission line data. To account for emission below the edge of the emission mask, the values of the moments are extrapolated as a function of pixel value to the 0 K brightness threshold (see Rosolowsky \& Leroy 2006) for details. This extrapolation is necessary to avoid bias in low signal-to-noise data, but it can introduce substantial uncertainty (up to 100\% for clouds near the signal-to-noise cut). We calculate the CO luminosity of the molecular clouds ($L_{\mathrm{CO}}$) by integrating the emission associated with each cloud, with a quadratic extrapolation. The luminous mass is calculated by scaling by a single CO-to-H$_2$ conversion factor:  \begin{equation}