We report the results of $EasyCritics$, a fully automated algorithm for the efficient search of strong-lensing (SL) regions in wide-field surveys, applied to the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). By using only the photometric information of the brightest elliptical galaxies distributed over a wide redshift range ($smash{0.2 lesssim z lesssim 0.9}$) and without requiring the identification of arcs, our algorithm produces lensing potential models and catalogs of critical curves of the entire survey area. We explore several parameter set configurations in order to test the efficiency of our approach. In a specific configuration, $EasyCritics$ generates only $sim1200$ possibly super-critical regions in the CFHTLS area, drastically reducing the effective area for inspection from $154$ sq. deg to $sim0.623$ sq. deg, $i.e.$ by more than two orders of magnitude. Among the pre-selected SL regions, we identify 32 of the 44 previously known lenses on the group and cluster scale, and discover 9 new promising lens candidates. The detection rate can be easily improved to $sim82%$ by a simple modification in the parameter set, but at the expense of increasing the total number of possible SL candidates. Note that $EasyCritics$ is fully complementary to other arc-finders since we characterize lenses instead of directly identifying arcs. Although future comparisons against numerical simulations are required for fully assessing the efficiency of $EasyCritics$, the algorithm seems very promising for upcoming surveys covering $smash{10^{4}}$ sq. deg, such as the $Euclid$ mission and $LSST$, where the pre-selection of candidates for any kind of SL analysis will be indispensable due to the expected enormous data volume.
Download