tokens: NRAO Astronomical Image Processing System 17 17 http://www.aips.nrao.edu/ package. In order to avoid false associations of radio matches, we downloaded the images from DSS1 and DSS2, which are digitized versions of several photographic astronomical surveys, in addition to radio maps, which can be found at the ESO archive. 18 18 http://archive.eso.org/dss/dss Comparison of radio and optical sources on maps from both domains, together with the NASA/IPAC Extragalactic Database, 19 19 https://ned.ipac.caltech.edu/ enabled us to distinguish incorrect matches. As some sources turned out to have extremely extended, i.e., beyond 3′, radio structures we were gradually increasing the radio search by 1′ as long as the association for the whole structure was found. Once the whole radio-emitting region was identified, the radio flux of each of the components was summed up and assigned to the given source. For sources lacking radio detections, we assigned them upper limits corresponding to the value of the sensitivity of the survey that contains the source in its footprint. While the sensitivity of NVSS and SUMSS is the same, for objects located in the area covered by both NVSS and FIRST, we decided on FIRST upper limits, as its sensitivity is lower than that of NVSS. Because the radio catalogs we used were conducted at two different frequencies, the radio fluxes at 843 MHz were recalibrated to 1.4 GHz using a radio spectral index of α r = 0.8 (with the convention of F ν ∝ ν − α ) so that the rest of our calculations are consistent. A.2. Mid-infrared Data The mid-infrared measurements were taken from the AllWISE Data Release (Cutri et al. 2013 ) which, by combining data from the cryogenic WISE (Wright et al. 2010 ) and post-cryogenic NEOWISE (“near-Earth object + WISE,” Mainzer et al. 2011 ) survey phases, resulted in a comprehensive view of the mid-infrared sky. Out of four available bands (at 3.4, 4.6, 12, and 22 μ m, corresponding to the W1, W2, W3, and W4 bands, respectively), we decided to make use of the W3 band, which was driven by the fact that at this specific wavelength the dusty torus is transparent enough to observe radiation coming directly from the central region of an AGN. At the shorter wavelengths of the W1 and W2 bands, the dusty, circumnuclear tori are optically thick and radiate anisotropically (Hönig et al. 2011 ; Netzer 2015 ). At the longer wavelengths of the W4 band, the dusty torus becomes even more transparent, but its measurements are affected by much larger errors than in W3 because (1) the W4 band traces the warm dust continuum at 22 μ m and can be contributed to by starbursts (Ichikawa et al. 2019 ); (2) the sensitivity in the W4 band is much lower than in the W3 band and its signal-to-noise ratio is the lowest of all the WISE channels, resulting in a lower detected fraction for the objects in our sample; and (3) the resolution of W4 images is worse than in other bands (e.g., 12′′ in W4 versus 65 in W3), so for some of our
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