  This work analyses the present-day mass function (PDMF) of 93~star clusters
utilizing Gaia DR3 data, with membership determined by the StarGo machine
learning algorithm. The impact of unresolved binary systems on mass estimation
is rigorously assessed, adopting three mass ratio profiles for correction. The
PDMF is characterized by the power-law index, $\alpha$, derived through a
robust maximum likelihood method that avoids biases associated with data
binning. The value of $\alpha$ for stars between the completeness limited mass
of Gaia with a mean 0.3 $M_\odot$ for our cluster samples and 2 $M_\odot$,
exhibits stability for clusters younger than 200 Myr, decreasing for older
clusters, particularly when considering stars within the half-mass radius. The
PDMF of these star clusters is consistent with a dynamically evolved Kroupa IMF
via the loss of low-mass stars. Cluster morphology shows a correlation with
$\alpha$, as $\alpha$ values exhibit a decreasing trend from filamentary to
tidal-tail clusters, mirroring the sequence of increasing cluster age. The
dependence of $\alpha$ on total cluster mass is weak, with a subtle increase
for higher-mass clusters, especially outside the half-mass radius. We do not
observe a correlation between $\alpha$ and the mean metallicity of the
clusters. Younger clusters have lower metallicity compared to their older
counterparts, which indicates that the older clusters might have migrated to
the solar neighbourhood from the inner disk. A comparison with numerical models
incorporating a black hole population suggests the need for observations of
distant, older, massive open clusters to determine whether or not they contain
black holes.
