  We want to characterize the properties of the cold dust clumps in the Carina
Nebula Complex (CNC), which shows a very high level of massive star feedback.
We derive the Clump Mass Function (ClMF), explore the reliability of different
clump extraction algorithms, and investigate the influence of the temperatures
within the clouds on the resulting shape of the ClMF.
  We analyze a 1.25x1.25 deg^2 wide-field sub-mm map obtained with LABOCA
(APEX), which provides the first spatially complete survey of the clouds in the
CNC. We use the three clump-finding algorithms CLUMPFIND (CF), GAUSSCLUMPS (GC)
and SExtractor (SE) to identify individual clumps and determine their total
fluxes. In addition to assuming a common `typical' temperature for all clouds,
we also employ an empirical relation between cloud column densities and
temperature to determine an estimate of the individual clump temperatures, and
use this to determine individual clump masses.
  While the ClMF based on the CF extraction is very well described by a
power-law, the ClMFs based on GC and SE are better represented by a log-normal
distribution. We also find that the use of individual clump temperatures leads
to a shallower ClMF slope than the assumption of a common temperature (e.g. 20
K) of all clumps.
  The power-law of dN/dM \propto M^-1.95 we find for the CF sample is in good
agreement with ClMF slopes found in previous studies of other regions. The
dependence of the ClMF shape (power-law vs. log-normal distribution) on the
employed extraction method suggests that observational determinations of the
ClMF shape yields only very limited information about the true structure of the
cloud. Interpretations of log-normal ClMF shape as a signature of turbulent
pre-stellar clouds vs. power-law ClMFs as a signature of star-forming clouds
may be taken with caution for a single extraction algorithm without additional
information.
